From 1312c462e0ddc28f6eed3c8f8647c02d9ec0d85d Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 03:24:02 +0900
Subject: [PATCH 001/399] Add map-airy distribution

---
 include/boost/math/distributions/mapairy.hpp | 4140 ++++++++++++++++++
 test/test_mapairy.cpp                        |  822 ++++
 2 files changed, 4962 insertions(+)
 create mode 100644 include/boost/math/distributions/mapairy.hpp
 create mode 100644 test/test_mapairy.cpp

diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
new file mode 100644
index 0000000000..d7d56ed77f
--- /dev/null
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -0,0 +1,4140 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_STATS_MAPAIRY_HPP
+#define BOOST_STATS_MAPAIRY_HPP
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable : 4127) // conditional expression is constant
+#endif
+
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/distributions/complement.hpp>
+#include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <utility>
+#include <cmath>
+
+namespace boost { namespace math {
+template <class RealType, class Policy>
+class mapairy_distribution;
+
+namespace detail {
+
+template <class RealType>
+inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 3.7591e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(1.97516171847191855610e-1),
+            static_cast<RealType>(3.67488253628465083737e-2),
+            static_cast<RealType>(-9.73242224038828612673e-4),
+            static_cast<RealType>(2.32207514136635673061e-3),
+            static_cast<RealType>(5.69067907423210669037e-5),
+            static_cast<RealType>(-6.02637387141524535193e-5),
+            static_cast<RealType>(1.04960324426666933327e-5),
+            static_cast<RealType>(-6.58470237954242016920e-7),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.09464351647314165710e-1),
+            static_cast<RealType>(3.66413036246461392316e-1),
+            static_cast<RealType>(1.10947882302862241488e-1),
+            static_cast<RealType>(2.65928486676817177159e-2),
+            static_cast<RealType>(3.75507284977386290874e-3),
+            static_cast<RealType>(4.03789594641339005785e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.5996e-20
+        static const RealType P[8] = {
+            static_cast<RealType>(1.06251243013238748252e-1),
+            static_cast<RealType>(1.38178831205785069108e-2),
+            static_cast<RealType>(4.19280374368049006206e-3),
+            static_cast<RealType>(8.54607219684690930289e-4),
+            static_cast<RealType>(-7.46881084120928210702e-5),
+            static_cast<RealType>(1.47110856483345063335e-5),
+            static_cast<RealType>(-1.30090180307471994500e-6),
+            static_cast<RealType>(5.24801123304330014713e-8),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.10853683888611687140e-1),
+            static_cast<RealType>(3.89361261627717143905e-1),
+            static_cast<RealType>(1.15124062681082170577e-1),
+            static_cast<RealType>(2.38803416611949902468e-2),
+            static_cast<RealType>(3.08616898814509065071e-3),
+            static_cast<RealType>(2.43760043942846261876e-4),
+            static_cast<RealType>(1.34538901435238836768e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1592e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(5.33842514891989443409e-2),
+            static_cast<RealType>(1.23301980674903270971e-2),
+            static_cast<RealType>(3.45717831433988631923e-3),
+            static_cast<RealType>(3.27034449923176875761e-4),
+            static_cast<RealType>(1.20406794831890291348e-5),
+            static_cast<RealType>(5.77489170397965604669e-7),
+            static_cast<RealType>(-1.15255267205685159063e-7),
+            static_cast<RealType>(9.15896323073109992939e-9),
+            static_cast<RealType>(-3.14068002815368247985e-10),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.08772985520393226044e-1),
+            static_cast<RealType>(4.26418573702560818267e-1),
+            static_cast<RealType>(1.22033746594868893316e-1),
+            static_cast<RealType>(2.27934009200310243172e-2),
+            static_cast<RealType>(2.60658999011198623962e-3),
+            static_cast<RealType>(1.54461660261435227768e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.2228e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.58950538583133457384e-2),
+            static_cast<RealType>(7.47835440063141601948e-3),
+            static_cast<RealType>(1.81137244353261478410e-3),
+            static_cast<RealType>(2.26935565382135588558e-4),
+            static_cast<RealType>(1.43877113825683795505e-5),
+            static_cast<RealType>(2.08242747557417233626e-7),
+            static_cast<RealType>(-1.54976465724771282989e-9),
+            static_cast<RealType>(1.30762989300333026019e-11),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.95505437381674174441e-1),
+            static_cast<RealType>(4.58882737262511297099e-1),
+            static_cast<RealType>(1.25031310192148865496e-1),
+            static_cast<RealType>(2.15727229249904102247e-2),
+            static_cast<RealType>(2.33597081566665672569e-3),
+            static_cast<RealType>(1.45198998318300328562e-4),
+            static_cast<RealType>(3.87962234445835345676e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0257e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(3.22517551525042172428e-3),
+            static_cast<RealType>(1.12822806030796339659e-3),
+            static_cast<RealType>(1.54489389961322571031e-4),
+            static_cast<RealType>(9.28479992527909796427e-6),
+            static_cast<RealType>(2.06168350199745832262e-7),
+            static_cast<RealType>(9.05110751997021418539e-10),
+            static_cast<RealType>(-2.15498112371756202097e-12),
+            static_cast<RealType>(6.41838355699777435924e-15),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.53390465399680164234e-1),
+            static_cast<RealType>(1.82759048270449018482e-1),
+            static_cast<RealType>(2.80407546367978533849e-2),
+            static_cast<RealType>(2.50853443923476718145e-3),
+            static_cast<RealType>(1.27671852825846245421e-4),
+            static_cast<RealType>(3.28380135691060279203e-6),
+            static_cast<RealType>(3.06545317089055335742e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.0510e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(5.82527663232857270992e-4),
+            static_cast<RealType>(6.89502117025124630567e-5),
+            static_cast<RealType>(2.24909795087265741433e-6),
+            static_cast<RealType>(2.18576787334972903790e-8),
+            static_cast<RealType>(3.39014723444178274435e-11),
+            static_cast<RealType>(-9.74481309265612390297e-15),
+            static_cast<RealType>(-1.13308546492906818388e-16),
+            static_cast<RealType>(5.32472028720777735712e-19),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.74018883667663396766e-1),
+            static_cast<RealType>(2.95901195665990089660e-2),
+            static_cast<RealType>(1.57901733512147920251e-3),
+            static_cast<RealType>(4.24965124147621236633e-5),
+            static_cast<RealType>(5.17522027193205842016e-7),
+            static_cast<RealType>(2.00522219276570039934e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.3294e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(1.03264853379349880039e-4),
+            static_cast<RealType>(5.35256306644392405447e-6),
+            static_cast<RealType>(9.00657716972118816692e-8),
+            static_cast<RealType>(5.34913574042209793720e-10),
+            static_cast<RealType>(6.70752605041678779380e-13),
+            static_cast<RealType>(-5.30089923101856817552e-16),
+            static_cast<RealType>(7.28133811621687143754e-19),
+            static_cast<RealType>(-7.38047553655951666420e-22),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.29920843258164337377e-1),
+            static_cast<RealType>(6.75018577147646502386e-3),
+            static_cast<RealType>(1.77694968039695671819e-4),
+            static_cast<RealType>(2.46428299911920942946e-6),
+            static_cast<RealType>(1.67165053157990942546e-8),
+            static_cast<RealType>(4.19496974141131087116e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x * x * x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6693e-20
+        static const RealType P[5] = {
+            static_cast<RealType>(5.98413420602149016910e-1),
+            static_cast<RealType>(3.14584075817417883086e-5),
+            static_cast<RealType>(1.62977928311793051895e1),
+            static_cast<RealType>(-4.12903117172994371875e-4),
+            static_cast<RealType>(-1.06404478702135751872e2),
+        };
+        static const RealType Q[3] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.25696892802060720079e-5),
+            static_cast<RealType>(4.03600055498020483920e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 7.8308e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97516171847191855609649452292217911973e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17531822787252717270400174744562144891e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85115358761409188259685286269086053296e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18029395189535552537870932989876189597e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77412874842522285996566741532939343827e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77992070255086842672551073580133785334e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.54573264286260796576738952968288691782e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.94764012694602906119831079380500255557e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.97596258932025712802674070104281981323e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45466169112247379589927514614067756956e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.99760415118300349769641418430273526815e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43150486566834492207695241913522311930e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46130347604880355784938321408765318948e-13),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11845869711743584628289654085905424438e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.80391154854347711297249357734993136108e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75628443538173255184583966965162835227e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41016303833742742212624596040074202424e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19142300833563644046500846364541891138e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02421707708633106515934651956262614532e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.03973732602338507411104824853671547615e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35206168908201402570766383018708660819e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.38602606623008690327520130558254165564e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53740175911385378188372963739884519312e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27513004715414297729539702862351044344e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54510493017251997793679126704007098265e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.0723e-35
+        static const RealType P[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06251243013238748252181151646220197947e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92438638323563234519452281479338921158e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83335793178622701784730867677919844599e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.84159075203218824591724451142550478306e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04213732090358859917896442076931334722e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72388220651785798237487005913708387756e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.36099324022668533012286817710272936865e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74483270731217433628720245792741986795e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.56461597064783966758904403291149549559e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28590608939674970691948223694855264817e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81756745849477762773082030302943341729e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.65915115243311285178083515017249358853e-12),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33250387018216706082200927591739589024e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.71707718560216685629188467984384070512e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81316277289673837399162302797006618384e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78475951599121894570443981591530879087e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.16167801098514576400689883575304687623e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19167794366424137722223009369062644830e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20831082064982892777497773490792080382e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27196399162146247210036306870401328410e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79335434374966775903734846875100087590e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30825409557870847168672662674521614782e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97296173230649275943984471731360073540e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48943057909563158917114503727080517958e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.0903e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.33842514891989443409465171800884519331e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53264053296761245408991932692426094424e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23210520807186629205810670362048049836e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.71104271443590027208545022968625306496e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98781446716778138729774954595209697813e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98895829308616657174932023565302947632e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25993639218721804661037829873135732687e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.64669776700609853276056375742089715662e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.11846243382610611156151291892877027869e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.74830086064868141326053648144496072795e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07549997153431643849551871367000763445e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10030596535721362628619523622308581344e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19376016170255697546854583591494809062e-13),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52686177278870816414637961315363468426e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19872083945442288336636376283295310445e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26633866969676511944680471882188527224e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41261867539396133951024374504099977090e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.18852182132645783844766153200510014113e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70152126044106007357033814742158353948e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23810508827493234517751339979902448944e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.96161313274648769113605163816403306967e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06693316156193327359541953619174255726e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.79366356086062616343285660797389238271e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.14585835815353770175366834099001313472e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05314631662369743547568064896403143693e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90325380271096603676911761784650800378e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.36933359079566550212098911224675011839e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5015e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58950538583133457383574346194006716984e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25447644411503971725638816502617490834e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47605882774114100209665040117276675598e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.12224864838900383464124716266085521485e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79164249640537972514574059182421325541e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.89668438166714230032406615413991628135e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44410389750700463263686630222653669837e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.14788978994687095829140113472609739982e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.79821680629333600844514042061772236495e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.49636960435731257154960798035854124639e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70554745768928821263556963261516872171e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.42293994855343109617040824208078534205e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37599287094703195312894833570340165019e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35248179978735448062307216459232932068e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53569375838863862590910010617140120876e-18),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94337325681904859647161946168957959628e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77120402023938328899162557073347121463e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01644685191130734907530007424741314392e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.12479655123720440909164080517207084404e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25556010526357752360439314019567992245e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96143273204038192262150849394970544022e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.50612932318889495209230176354364299236e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.12160918304376427109905628326638480473e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47696044292604039527013647985997661762e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.64067652576843720823459199100800335854e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.00745166063635113130434111509648306420e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05398901239421768403763864060147286105e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05698259572340563109985785513355912114e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19362835269415404005406782719825077472e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15444386779802728200716489787161419304e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02452666470008756043350040893761339083e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0995e-35
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22517551525042172427941302520759668293e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86576974828476461442549217748945498966e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18419822818191546598384139622512477000e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98396184944524020019688823190946146641e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06686400532599396487775148973665625687e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05680178109228687159829475615095925679e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.17554487015345146749705505971350254902e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14774751685364429557883242232797329274e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33266124509168360207594600356349282805e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76332756800842989348756910429214676252e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60639771339252642992277508068105926919e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.41859490403554144799385471141184829903e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77177795293424055655391515546880774987e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76106923344461402353501262620681801053e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68829978902134103249656805130103045021e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42496376687241918803028631991083570963e-26),
+        };
+        static const RealType Q[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19213376162053391168605415200906099633e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65578261958732385181558047087365997878e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30046653564394292929001223763106276016e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48388301731958697028701215596777178117e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.50873786049439122933188684993719288258e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23255654647151798865208394342856435797e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20861791399969402003082323686080041040e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96882049090731653763684812243275884213e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.98669985741073085290012296575736698103e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.03383311816835346577432387682379226740e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.87320682938150375144724980774245810905e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13573468677076838075146150847170057373e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34526045003716422620879156626237175127e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35681579117696161282979297336282783473e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92944288060269290125987728528698476197e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0937e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82527663232857270992129793621400616909e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41696401156754081476312871174198295322e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42036620449365724707919875710197564857e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67076745288708619632303078677641380627e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14278954094278648593125010577441869646e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40092485054621853149602511539550254471e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.17755660009065973828053533035808718033e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.23871371557251644837598540542648782066e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04069998646037977439620128812310273053e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94055978349016208777803296823455779097e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29866428982892883091537921429389750973e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06056281963023929277728535486590256573e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57963857545037466186123981516026589992e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.81390322233700529779563477285232205886e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52190981930441828041102818178755246228e-31),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.70564782441895707961338319466546005093e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47770566490107388849474183308889339231e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29364672385303439788399215507370006639e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.37279274083988250795581105436675097881e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72124151284421794872333348562536468054e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96970247774973902625712414297788402746e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.38395055453444011915661055983937917120e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.19605460410208704830882138883730331113e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76945301389475508747530234950023648137e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33624384932503964160642677987886086890e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01155130710615988897664213446593907596e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03959317021567084067518847978890548086e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78213669817351488671519066803835958715e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75492332026736176991870807903277324902e-22),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.5856e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03264853379349880038687006045193401399e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79539964604630527636184900467871907171e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34840369549460790638336121351837912308e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.73087351972154879439617719914590729748e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51775493325347153520115736204545037264e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60104651860674451546102708885530128768e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90233449697112559539826150932808197444e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06978852724410115655105118663137681992e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.00399855296672416041126220131900937128e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18139748830278263202087699889457673035e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43070756487288399784700274808326343543e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70126687893706466023887757573369648552e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29405234560873665664952418690159194840e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.69069082510020066864633718082941688708e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33468198065176301137949068264633336529e-37),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51951069241510130465691156908893803280e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84647597299970149588010858770320631739e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90239396588176334117512714878489376365e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35551585337774834346900776840459179841e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53375746264539501168763602838029023222e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42421935941736734247914078641324315900e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.23835501607741697737129504173606231513e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.79603272375172813955236187874231935324e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44624821303153251954931367754173356213e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10635081308984534416704147448323126303e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.14627867347129520510628554651739571006e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43792928765659831045040802615903432044e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.79856365207259871336606847582889916798e-25),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x * x * x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.5081e-36
+        static const RealType P[8] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98413420602149016909919089901572802714e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30303835860684077803651094768293625633e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.89097726237252419724261295392691855545e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.12696604472230480273239741428914666511e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84517621403071494824886152940942995151e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.67577378292168927009421205756730205227e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.16343347002845084264982358165052437094e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.59558963351172885545760841064831356701e3),
+        };
+        static const RealType Q[7] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.51965956124978480521462518750569617550e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61700833299761977287211297600922591853e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.94988298508869748383898344668918510537e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.52494213749069142804725453333400335525e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20093079283917759611690534481918040882e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82564796242972192725215815897475246715e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.7525e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(2.76859868856746781256e-1),
+            static_cast<RealType>(1.10489814676299003241e-1),
+            static_cast<RealType>(-6.25690643488236678667e-3),
+            static_cast<RealType>(-1.17905420222527577236e-3),
+            static_cast<RealType>(1.27188963720084274122e-3),
+            static_cast<RealType>(-7.20575105181207907889e-5),
+            static_cast<RealType>(-2.22575633858411851032e-5),
+            static_cast<RealType>(2.94270091008508492304e-6),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.98673671503410894284e-1),
+            static_cast<RealType>(3.15907666864554716291e-1),
+            static_cast<RealType>(8.34463558393629855977e-2),
+            static_cast<RealType>(2.71804643993972494173e-2),
+            static_cast<RealType>(3.52187050938036578406e-3),
+            static_cast<RealType>(7.03072974279509263844e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.0995e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(2.14483832832989822788e-1),
+            static_cast<RealType>(3.72789690317712876663e-1),
+            static_cast<RealType>(1.86473650057086284496e-1),
+            static_cast<RealType>(1.31182724166379598907e-2),
+            static_cast<RealType>(-9.00695064809774432392e-3),
+            static_cast<RealType>(3.46884420664996747052e-4),
+            static_cast<RealType>(4.88651392754189961173e-4),
+            static_cast<RealType>(-6.13516242712196835055e-5),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.06478618107122200489e0),
+            static_cast<RealType>(4.08809060854459518663e-1),
+            static_cast<RealType>(2.66617598099501800866e-1),
+            static_cast<RealType>(4.53526315786051807494e-2),
+            static_cast<RealType>(2.44078693689626940834e-2),
+            static_cast<RealType>(1.52822572478697831870e-3),
+            static_cast<RealType>(8.69480001029742502197e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType s = exp(2 * x * x * x / 27) * sqrt(-x);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.4768e-18
+            static const RealType P[8] = {
+                static_cast<RealType>(2.74308494787955998605e-1),
+                static_cast<RealType>(4.87765991440983416392e-1),
+                static_cast<RealType>(3.84524365110270427617e-1),
+                static_cast<RealType>(1.77409497505926097339e-1),
+                static_cast<RealType>(5.25612864287310961520e-2),
+                static_cast<RealType>(1.01528615034079765421e-2),
+                static_cast<RealType>(1.20417225696161842090e-3),
+                static_cast<RealType>(6.97462693097107007719e-5),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.81256903248465876424e0),
+                static_cast<RealType>(1.43959302060852067876e0),
+                static_cast<RealType>(6.65882284117861804351e-1),
+                static_cast<RealType>(1.97537712781845593211e-1),
+                static_cast<RealType>(3.81732970028510912201e-2),
+                static_cast<RealType>(4.52767489928026542226e-3),
+                static_cast<RealType>(2.62240194911920120003e-4),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -8) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 1.5741e-17
+            static const RealType P[8] = {
+                static_cast<RealType>(2.67391547707456587286e-1),
+                static_cast<RealType>(3.39319035621314371924e-1),
+                static_cast<RealType>(1.85434799940724207230e-1),
+                static_cast<RealType>(5.63667456320679857693e-2),
+                static_cast<RealType>(1.01231164548944177474e-2),
+                static_cast<RealType>(1.02501575174439362864e-3),
+                static_cast<RealType>(4.60769537123286016400e-5),
+                static_cast<RealType>(-4.92754650783224582641e-13),
+            };
+            static const RealType Q[7] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.27271216837333318516e0),
+                static_cast<RealType>(6.96551952883867277759e-1),
+                static_cast<RealType>(2.11871363524516350422e-1),
+                static_cast<RealType>(3.80622887806509632537e-2),
+                static_cast<RealType>(3.85400280812991562328e-3),
+                static_cast<RealType>(1.73246593953823694311e-4),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -16) {
+            RealType t = -x - 8;
+
+            // Rational Approximation
+            // Maximum Relative Error: 4.6579e-17
+            static const RealType P[6] = {
+                static_cast<RealType>(2.66153901932100301337e-1),
+                static_cast<RealType>(1.65767350677458230714e-1),
+                static_cast<RealType>(4.19801402197670061146e-2),
+                static_cast<RealType>(5.39337995172784579558e-3),
+                static_cast<RealType>(3.50811247702301287586e-4),
+                static_cast<RealType>(9.21758454778883157515e-6),
+            };
+            static const RealType Q[6] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(6.23092941554668369107e-1),
+                static_cast<RealType>(1.57829914506366827914e-1),
+                static_cast<RealType>(2.02787979758160988615e-2),
+                static_cast<RealType>(1.31903008994475216511e-3),
+                static_cast<RealType>(3.46575870637847438219e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -32) {
+            RealType t = -x - 16;
+
+            // Rational Approximation
+            // Maximum Relative Error: 5.2014e-17
+            static const RealType P[5] = {
+                static_cast<RealType>(2.65985830928929730672e-1),
+                static_cast<RealType>(7.19655029633308583205e-2),
+                static_cast<RealType>(7.26293125679558421946e-3),
+                static_cast<RealType>(3.24276402295343802262e-4),
+                static_cast<RealType>(5.40508013573989841127e-6),
+            };
+            static const RealType Q[5] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(2.70578525590448009961e-1),
+                static_cast<RealType>(2.73082032706004833847e-2),
+                static_cast<RealType>(1.21926059813954504560e-3),
+                static_cast<RealType>(2.03227900426552177849e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.2870e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76859868856746781256050397658493368372e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13037642242224438972685982606987140111e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.93206268361082760254653961897373271146e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12844418906916902333116398594921450782e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36889326770180267250286619759335338794e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.95272615884641416804001553871108995422e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.53808638264746233799776679481568171506e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.92177790427881393122479399837010657693e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93492737815019893169693306410980499366e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.87510085148730083683110532987841223544e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.28469424017979299382094276157986775969e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83693904015623816528442886551032709693e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77632857558257155545506847333166147492e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00448215148716947837105979735199471601e-11),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.69069814466926608209872727645156315374e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89657828158127300370734997707096744077e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62713433978940724622996782534485162816e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.91600878366366974062522408704458777166e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.89144035500328704769924414014440238441e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35263616916053275381069097012458200491e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49136684724986851824746531490006769036e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65912003138912073317982729161392623277e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65931144405541620572732754508534372034e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40193555853535182510951061797573338442e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43625211359756249232841566256877823039e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33207781577559817130740123609636060998e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1977e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14483832832989822788477500521594411868e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75657192307644021285091474845448102656e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40437358470633234235031852091608646844e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66609942512054705023295445270747546208e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54563774151184610728476161049657676321e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51479057544157089574005315379453615537e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.59853789372610909788599341307719626846e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76919062715142378209907670793921883406e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58572738466179822770103948740437237476e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.66618046393835590932491510543557226290e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.26253044828460469263564567571249315188e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11130363073235247786909976446790746902e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49023728251751416730708805268921994420e-10),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.11919889346080886194925406930280687022e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99082771425048574611745923487528183522e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99525320878512488641033584061027063035e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.20775109959302182467696345673111724657e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67505804311611026128557007926613964162e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.77854913919309273628222660024596583623e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91661599559554233157812211199256222756e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.83924945472605861063053622956144354568e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.84286353909650034923710426843028632590e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57737060659799463556626420070111210218e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76047305116625604109657617040360402976e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86975509621224474718728318687795215895e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71646204381423826495116781730719271111e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30359141441663007574346497273327240071e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType s = exp(2 * x * x * x / 27) * sqrt(-x);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 5.4547e-35
+            static const RealType P[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74308494787955998605105974174143750745e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.56767876568276519015214709629156760546e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23402577465454790961498400214198520261e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09577559351834952074671208183548972395e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.76209118910349927892265971592071407626e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09368637728788364895148841703533651597e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09003822946777310058789032386408519829e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02362804210869367995322279203786166303e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.67210045349462046966360849113168808620e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17170437120510484976042000272825166724e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62068279517157268391045945672600042900e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72238125522303876741011786930129571553e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33906175951716762094473406744654874848e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88118741063309731598638313174835288433e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78908322579081615215057968216358892954e-9),
+            };
+            static const RealType Q[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15777668058369565739250784347385217839e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58275582332060589146223977924181161908e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08890987062755381429904193744273374370e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53062680969750921573862970262146744660e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15983695707064161504470525373678920004e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09120624447001177857109399158887656977e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13566107440776375294261717406754395407e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50716565210262652091950832287627406780e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40417354541359829249609883808591989082e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.09285589734746898623782466689035549135e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.47580156629757526370271002425784456931e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03479533688660179064728081632921439825e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58728676819719406366664644282113323077e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72685000369623096389026353785111272994e-9),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -8) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 1.8813e-35
+            static const RealType P[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67391547707456587286086623414017962238e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.69944730920904699720804320295067934914e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.80384452804523880914883464295008532437e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74832028145199140240423863864148009059e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71728522451977382202061046054643165624e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91023495084678296967637417245526177858e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57730498044529764612538979048001166775e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31940820074475947691746555183209863058e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54175805821840981842505041345112198286e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31350452337838677820161124238784043790e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.52175993144502511705213771924810467309e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.85684239411667243910736588216628677445e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27124210379062272403030391492854565008e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17645475312219452046348851569796494059e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06306499345515479193219487228315566344e-11),
+            };
+            static const RealType Q[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13521398369589479131299586715604029947e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17680254721938920978999949995837883884e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40693619288419980101309080614788657638e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44930162913500531579305526795523256972e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22044272115074113804712893993125987243e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.92745159832354238503828226333417152767e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24766164774700476810039401793119553409e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08325637569571782180723187639357833929e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74954547353553788519997212700557196088e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82800744682204649977844278025855329390e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20210992299988298543034791887173754015e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22996819257926038785424888617824130286e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42340212199922656577943251139931264313e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.75700556749505163188370496864513941614e-11),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -16) {
+            RealType t = -x - 8;
+
+            // Rational Approximation
+            // Maximum Relative Error: 3.7501e-35
+            static const RealType P[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66153901932100301337118653561328446399e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52542079386371212946566450189144670788e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17560936304516198261138159102435548430e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.26792904240601626330507068992045446428e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15418212265160879313643948347460896640e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05247220687656529725024232836519908641e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.64228534097787946289779529645800775231e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.85634097697132464418223150629017524118e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49585420710073223183176764488210189671e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.48871040740917898530270248991342594461e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.42577266655992039477272273926475476183e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19214263302271253341410568192952269518e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36635313919771528255819112450043338510e-12),
+            };
+            static const RealType Q[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32484755553196872705775494679365596205e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17714315014480774542066462899317631393e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10789882607024692577764888497624620277e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09821963157449764169644456445120769215e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52354198870000121894280965999352991441e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12133327236256081067100384182795121111e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20187894923874357333806454001674518211e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69039238999927049119096278882765161803e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.35737444680219098802811205475695127060e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.54403624143647064402264521374546365073e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.24233005893817070145949404296998119469e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.89735152971223120087721392400123727326e-12),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -32) {
+            RealType t = -x - 16;
+
+            // Rational Approximation
+            // Maximum Relative Error: 9.2696e-36
+            static const RealType P[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65985830928929730672052407058361701971e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80409998734303497641108024806388734755e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.49286120625421787109350223436127409819e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.89160491404149422833016337592047445082e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16725811789351893632348469796802834008e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.43438517439595919021069131504449842238e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29058184637190638359623120253986595623e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.03288592271246432030980385908922413497e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.12286831076824535034975676306286388291e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.64563161552001551475186730009447111173e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13183856815615371136129883169639301710e-13),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.02405342795439598418033139109649640085e-35),
+            };
+            static const RealType Q[11] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78286317363568496229516074305435186276e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06519013547074134846431611115576250187e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71907733798006110542919988654989891098e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.38874744033460851257697736304200953873e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.54724289412996188575775800547576856966e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98922099980447626797646560786207812928e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.64352676367403443733555974471752023206e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92616898324742524009679754162620171773e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87471345773127482399498877510153906820e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92954174836731254818376396170511443820e-12),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -64) {
+            RealType t = -x - 32;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.3524e-35
+            static const RealType P[10] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65964563346442080104568381680822923977e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.77958685324702990033291591478515962894e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.56419338083136866686699803771820491401e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.82465178504003399087279098324316458608e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92402911374159755476910533154145918079e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91224450962405933321548581824712789516e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.84063939469145970625490205194192347630e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.15300528698702940691774461674788639801e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.85553643603397817535280932672322232325e-13),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.46207029637607033398822620480584537642e-38),
+            };
+            static const RealType Q[9] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54906717312241693103173902792310528801e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84408124581401290943345932332007045483e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81403744024723164669745491417804917709e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23423244618880845765135047598258754409e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84697524433421334697753031272973192290e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94803525968789587050040294764458613062e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68948879514200831687856703804327184420e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07366525547027105672618224029122809899e-12),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+    if (x >= 0) {
+        return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
+    }
+    else if (x <= 0) {
+        return mapairy_pdf_minus_imp_prec<RealType>(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
+    }
+    else if (x <= 0) {
+        return mapairy_pdf_minus_imp_prec<RealType>(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x) {
+    //
+    // This calculates the pdf of the Map-Airy distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::pdf(mapairy<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = mapairy_pdf_imp_prec(u, tag_type()) / scale;
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 2.9194e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(3.33333333333333333333e-1),
+            static_cast<RealType>(7.49532137610545010591e-2),
+            static_cast<RealType>(9.25326921848155048716e-3),
+            static_cast<RealType>(6.59133092365796208900e-3),
+            static_cast<RealType>(-5.21942678326323374113e-4),
+            static_cast<RealType>(8.22766804917461941348e-5),
+            static_cast<RealType>(-3.97941251650023182117e-6),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.17408156824742736411e-1),
+            static_cast<RealType>(3.57041011418415988268e-1),
+            static_cast<RealType>(1.04580353775369716002e-1),
+            static_cast<RealType>(1.87521616934129432292e-2),
+            static_cast<RealType>(2.33232161135637085535e-3),
+            static_cast<RealType>(7.31285352607895467310e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.1531e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.84196970581015939888e-1),
+            static_cast<RealType>(-1.19398028299089933853e-3),
+            static_cast<RealType>(1.21954054797949597854e-2),
+            static_cast<RealType>(-9.37912675685073154845e-4),
+            static_cast<RealType>(1.66651954077980453212e-4),
+            static_cast<RealType>(-1.33271812303025233648e-5),
+            static_cast<RealType>(5.35982226125013888796e-7),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.70352826101668448273e-1),
+            static_cast<RealType>(1.98852010141232271304e-1),
+            static_cast<RealType>(3.64864882318453496161e-2),
+            static_cast<RealType>(4.22173125405065522298e-3),
+            static_cast<RealType>(1.20079284386796600356e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.8348e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.07409273397524124098e-1),
+            static_cast<RealType>(3.83900318969331880402e-2),
+            static_cast<RealType>(1.17926652359826576790e-2),
+            static_cast<RealType>(1.52181625871479030046e-3),
+            static_cast<RealType>(1.50703424417132565662e-4),
+            static_cast<RealType>(2.10117959279448106308e-6),
+            static_cast<RealType>(1.97360985832285866640e-8),
+            static_cast<RealType>(-1.06076300080048408251e-9),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.54435380513870673497e-1),
+            static_cast<RealType>(3.66021233157880878411e-1),
+            static_cast<RealType>(9.42985570806905160687e-2),
+            static_cast<RealType>(1.54122343653998564507e-2),
+            static_cast<RealType>(1.49849056258932455548e-3),
+            static_cast<RealType>(6.94290406268856211707e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.6624e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(4.70720199535228802538e-2),
+            static_cast<RealType>(2.67200763833749070079e-2),
+            static_cast<RealType>(7.37400551855064729769e-3),
+            static_cast<RealType>(1.10592441765001623699e-3),
+            static_cast<RealType>(9.15846028547400212588e-5),
+            static_cast<RealType>(3.17801522553862136789e-6),
+            static_cast<RealType>(2.03102753319827713542e-8),
+            static_cast<RealType>(-5.16172854149066643529e-11),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.05317644829451086870e-1),
+            static_cast<RealType>(3.73713496637025562492e-1),
+            static_cast<RealType>(8.94434672792094976627e-2),
+            static_cast<RealType>(1.31846542255347106087e-2),
+            static_cast<RealType>(1.16680596342421447100e-3),
+            static_cast<RealType>(5.44719256441278863300e-5),
+            static_cast<RealType>(8.73131209154185067287e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.6243e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.74847564444513000450e-2),
+            static_cast<RealType>(6.00209162595027323742e-3),
+            static_cast<RealType>(7.86550260761375576075e-4),
+            static_cast<RealType>(4.46682547335758521734e-5),
+            static_cast<RealType>(9.51329761417139273391e-7),
+            static_cast<RealType>(4.10313065114362712333e-9),
+            static_cast<RealType>(-9.81286503831545640189e-12),
+            static_cast<RealType>(2.98763969872672156104e-14),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.27732094554221674504e-1),
+            static_cast<RealType>(1.14330643482604301178e-1),
+            static_cast<RealType>(1.27722341942374066265e-2),
+            static_cast<RealType>(7.54563340152441778517e-4),
+            static_cast<RealType>(2.13377039814057925832e-5),
+            static_cast<RealType>(2.09670987094350618690e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.4684e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(6.22684103170563193015e-3),
+            static_cast<RealType>(1.34714356588780958096e-3),
+            static_cast<RealType>(9.51289465377874891896e-5),
+            static_cast<RealType>(2.64918464474843134081e-6),
+            static_cast<RealType>(2.66703857491046795285e-8),
+            static_cast<RealType>(5.42037888457985833156e-11),
+            static_cast<RealType>(-6.18017115447736427379e-14),
+            static_cast<RealType>(9.11626234402148561268e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.09895694991285975774e-1),
+            static_cast<RealType>(3.69874670435930773471e-2),
+            static_cast<RealType>(2.15708854325146400153e-3),
+            static_cast<RealType>(6.35345408451056881884e-5),
+            static_cast<RealType>(8.65722805575670770555e-7),
+            static_cast<RealType>(4.03153189557220023202e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5947e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(2.20357145727036120652e-3),
+            static_cast<RealType>(1.45412555771401325111e-4),
+            static_cast<RealType>(3.27819006009093198652e-6),
+            static_cast<RealType>(2.96786786716623870006e-8),
+            static_cast<RealType>(9.54192199129339742308e-11),
+            static_cast<RealType>(5.71421706870777687254e-14),
+            static_cast<RealType>(-1.48321866072033823195e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.12851983233980279746e-1),
+            static_cast<RealType>(4.94650928817638043712e-3),
+            static_cast<RealType>(1.05447405092956497114e-4),
+            static_cast<RealType>(1.11578464291338271178e-6),
+            static_cast<RealType>(5.27522295397347842625e-9),
+            static_cast<RealType>(7.95786524903707645399e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType x_cube = x * x * x;
+        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.2709e-17
+        static const RealType P[4] = {
+            static_cast<RealType>(3.98942280401432677940e-1),
+            static_cast<RealType>(2.89752186412133782995e-2),
+            static_cast<RealType>(4.67360459917040710474e0),
+            static_cast<RealType>(-1.26770824563800250704e-1),
+        };
+        static const RealType Q[3] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.26301023103568827709e-2),
+            static_cast<RealType>(1.60899894281099149848e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 4.7720e-37
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33333333333333333333333333333333333333e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38519736580901276671338330967060054188e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07012342772403725079487012557507575976e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70163612228825567572185033570526547856e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16393313438726572630782132625753922397e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92141312947853945617138019222992750592e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16513062047959961711747864068554379374e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08850391017085844154857927364247623649e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07060872491334153829857156707699441084e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.56961733740920438026573722084839596926e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93626747947476815631021107726714283086e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32967164823609209711923411113824666288e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.23420723211833268177898025846064230665e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13807083548358335699029971528179486964e-13),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00810772528427939684296334977783425582e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.24383652800043768524894854013745098654e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64696616559657052516796844068580626381e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.62288747679271039067363492752820355369e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19311779292286492714550084942827207241e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48436879303839576521077892946281025894e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.28665316157256311138787387605249076674e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36350302380845433472593647100484547496e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.05835458213330488018147374864403662878e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13919959493955187399856105325181806876e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30960533107704070411766556906543316310e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.6297e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84196970581015939887507434989936103587e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23864910443500344832158256856064580005e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.72066675347648126090497588433854314742e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81712740200456564860442639192891089515e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.39091197181834765859741334477680768031e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.03759464781707198959689175957603165395e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15298069568149410830642785868857309358e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18910514301176322829267019223946392192e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.16851691488007921400221017970691227149e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82031940093536875619655849638573432722e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30042143299959913519747484877532997335e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.19848671456872291336347012756651759817e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00479393063394570750334218362674723065e-13),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24929390929112144560152115661603117364e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.34853762543033883106055186520573363290e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.73783624941936412984356492130276742707e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23224734370942016023173307854505597524e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.11116448823067697039703254343621931158e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.12490054037308798338231679733816982120e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.38701607014856856812627276285445001885e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10075199231657382435402462616587005087e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.43662615015322880941108094510531477066e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37981396630189761210639158952200945512e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55820444854396304928946970937054949160e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.8103e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07409273397524124098315500450332255837e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98373054365213259465522536994638631699e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30851284606709136235419547406278197945e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92686617543233900289721448026065555990e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.18056394312484073294780140350522772329e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07058343449035366484618967963264380933e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71636108080692802684712497501670425230e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13155853034615230731719317488499751231e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00070273388376168880473457782396672044e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35528857373910910704625837069445190727e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.99897218751541535347315078577172104436e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35092090729912631973050415647154137571e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72220647682193638971237255396233171508e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45008884108655511268690849420714428764e-15),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42652074703683973183213296310906006173e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03479786698331153607905223548719296572e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95556520914240562719970700900964416000e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73127917601685318803655745157828471269e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.63007065833918179119250623000791647836e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.70652732923091039268400927316918354628e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60880782675229297981880241245777122866e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09979261868403910549978204036056659380e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12085610111710889118562321318284539217e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59811533082647193392924345081953134304e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37211668706684650035086116219257276925e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62479830409039340826066305367893543134e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22039803134898937546371285610102850458e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.5930e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70720199535228802537946089633331273434e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85220706158476482443562698303252970927e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55090221054465759649629178911450010833e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.70398047783095186291450019612979853708e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11846661331973171721224034349719801691e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83195024406409870789088752469490824640e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.23908312140480103249294791529383548724e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.40765128885655152415228193255890859830e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.14294523267278070539100529759317560119e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26815059429007745850376987481747435820e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.28142945635159623618312928455133399240e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77079683180868753715374495747422819326e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73710011278079325323578951018770847628e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70140037580287364298206334732060874507e-16),
+        };
+        static const RealType Q[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36848014038411798213992770858203510748e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.15373052017549822413011375404872359177e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92705544967513282963463451395766172671e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19899290805598090502434290420047460406e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74002906913724742582773116667380578990e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80632456977494447641985312297971970632e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.53381530665983535467406445749348183915e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.86606180756179817016240556949228031340e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.49594666942152749850479792402078560469e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.25231012522695972983928740617341887334e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34987086926725472733984045599487947378e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.58286136970918021841189712851698747417e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.12238357666199366902936267515573231037e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82464168044335183356132979380360583444e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40073718480172265670072434562833527076e-17),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.3609e-35
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74847564444513000450056174922427854591e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56842503159303803254436983444304764079e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48504629497687889354406208309334148575e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62327083507366120871877936416427790391e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72062210557023828776202679230979309963e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19153025667221102770398900522196418041e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66248482185063262034022017727375829162e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57390218395059632327421809878050974588e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.45520328522839835737631604118833792570e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76327978880339919462910339138428389322e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99700625463451418394515481232159889297e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82943476668680389338853032002472541164e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19415284760817575957617090798914089413e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17080879333540200065368097274334363537e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.09912208206107606750610288716869139753e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98451733054622166748935243139556132704e-26),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08148065380582488495702136465010348576e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42385352331252779422725444021027377277e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66510412535270623169792008730183916611e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47952712144801508762945315513819636452e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.20703092334999244212988997416711617790e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.71658889250345012472529115544710926154e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.63905601023452497974798277091285373919e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76730409484335386334980429532443217982e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19139408077753398896224794522985050607e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.58025872548387600940275201648443410419e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.11369336267349152895272975096509109414e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.56182954522937999103610817174373785571e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35452907177197742692545044913125982311e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23587924912460218189929226092439805175e-17),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.7192e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.22684103170563193014558918295924551173e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55222688816852408105912768186300290291e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60747505331765587662432023547517953629e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80463770266821887100086895337451846880e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19190824169154471000496746227725070963e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40646301571395681364881852739555404287e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15408836734496798091749932018121879724e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.13676779930022341958128426888835497781e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02435098103190516418351075792372986932e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.82018920071479061978244972592746216377e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.26435061215428679536159320644587957335e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05298407883178633891153989998582851270e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61156860101928352010449210760843428372e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.02156808288545876198121127510075217184e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65549196385656698597261688277898043367e-30),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03426141030409708635168766288764563749e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13808987755928828118915442251025992769e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52253239792170999949444502938290297674e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33720936468171204432499390745432338841e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08713980159883984886576124842631646880e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43652846144339754840998823540656399165e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02849693617024492825330133490278326951e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14110017452008167954262319462808192536e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.01462578814695350559338360744897649915e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73495817568046489613308117490508832084e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47445372925844096612021093857581987132e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08200002287534174751275097848899176785e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15305756373406702253187385797525419287e-21),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.7799e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20357145727036120652264700679701054983e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95712324967981162396595365933255312698e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08619492652809635942960438372427086939e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37140224583881547818087260161723208444e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83073777522092069988595553041062506001e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.00473542739040742110568810201412321512e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.47447289601822506789553624164171452120e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70913574957198131397471307249294758738e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36538119628489354953085829178695645929e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00763343664814257170332492241110173166e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62297585950798764290583627210836077239e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15780217054514513493147192853488153246e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31961589164397397724611386366339562789e-28),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26440207646105117747875545474828367516e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27872879091838733280518786463281413334e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34256572873114675776148923422025029494e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13595637397535037957995766856628205747e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33745879863685053883024090247009549434e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41792226523670940279016788831933559977e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.03966147662273388060545199475024100492e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62177951640260313354050335795080248910e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50650165210517365082118441264513277196e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48413283257020741389298806290302772976e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16439276222123152748426700489921412654e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24969602890963356175782126478237865639e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08681155203261739689727004641345513984e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28282024196484688479115133027874255367e-30),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType x_cube = x * x * x;
+        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.5865e-37
+        static const RealType P[8] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12426566605292130233061857505057433291e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91574528280329492283287073127040983832e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69914217884224943794012165979483573091e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30178902028403564086640591437738216288e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96515490341559353794378324810127583810e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44343825578434751356083230369361399507e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07224810408790092272497403739984510394e2),
+        };
+        static const RealType Q[7] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32474438135610721926278423612948794250e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27594461167587027771303292526448542806e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49207539478843628626934249487055017677e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75094412095634602055738687636893575929e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51642534474780515366628648516673270623e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05977615003758056284424652420774587813e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.6964e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(4.23238998449671083670e-1),
+            static_cast<RealType>(4.95353582976475183891e-1),
+            static_cast<RealType>(2.45823281826037784270e-1),
+            static_cast<RealType>(7.29726507468813920788e-2),
+            static_cast<RealType>(1.63332856186819713346e-2),
+            static_cast<RealType>(2.82514634871307516142e-3),
+            static_cast<RealType>(2.66220579589280704089e-4),
+            static_cast<RealType>(3.09442180091323751049e-6),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.16241922223786900600e-1),
+            static_cast<RealType>(2.75690727171711638879e-1),
+            static_cast<RealType>(7.18707184893542884080e-2),
+            static_cast<RealType>(1.87136800286819336797e-2),
+            static_cast<RealType>(2.38383441176345054929e-3),
+            static_cast<RealType>(3.23509126477812051983e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.8303e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.62598955251978523175e-1),
+            static_cast<RealType>(2.30154661502402196205e-1),
+            static_cast<RealType>(1.29233975368291684522e-1),
+            static_cast<RealType>(3.80919553916980965587e-2),
+            static_cast<RealType>(8.17724414618808505948e-3),
+            static_cast<RealType>(1.95816800210481122544e-3),
+            static_cast<RealType>(3.35259917978421935141e-4),
+            static_cast<RealType>(1.22071311320012805777e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.63771793313770952352e-2),
+            static_cast<RealType>(2.23602260938227310054e-1),
+            static_cast<RealType>(9.21944797677283179038e-3),
+            static_cast<RealType>(1.82181136341939651516e-2),
+            static_cast<RealType>(1.11216849284965970458e-4),
+            static_cast<RealType>(5.57446347676836375810e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType s = exp(2 * x * x * x / 27) / sqrt(-x * x * x);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 3.6017e-18
+            static const RealType P[8] = {
+                static_cast<RealType>(8.31806744221966404520e-1),
+                static_cast<RealType>(1.34481067378012055850e0),
+                static_cast<RealType>(9.12139427469494995264e-1),
+                static_cast<RealType>(3.59706159222491124928e-1),
+                static_cast<RealType>(9.48836332725688279299e-2),
+                static_cast<RealType>(1.68259594978853951234e-2),
+                static_cast<RealType>(1.89700733471520162946e-3),
+                static_cast<RealType>(1.13854052826846329787e-4),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.29694286517571741097e0),
+                static_cast<RealType>(7.99686735441213882518e-1),
+                static_cast<RealType>(3.08198207583883597188e-1),
+                static_cast<RealType>(7.97230139795658588972e-2),
+                static_cast<RealType>(1.40742142048849462162e-2),
+                static_cast<RealType>(1.58411440546277691506e-3),
+                static_cast<RealType>(9.51560785730564046338e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -8) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 1.3504e-17
+            static const RealType P[8] = {
+                static_cast<RealType>(1.10294551528734705946e0),
+                static_cast<RealType>(1.26696377028973554615e0),
+                static_cast<RealType>(6.63115985833429688941e-1),
+                static_cast<RealType>(2.06289793717379095832e-1),
+                static_cast<RealType>(4.11977615717846276227e-2),
+                static_cast<RealType>(5.28620928618550859827e-3),
+                static_cast<RealType>(4.04328442334023561279e-4),
+                static_cast<RealType>(1.42364413902075896503e-5),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.09709853682665798542e0),
+                static_cast<RealType>(5.63687797989627787500e-1),
+                static_cast<RealType>(1.73604358560002859604e-1),
+                static_cast<RealType>(3.44985744385890794044e-2),
+                static_cast<RealType>(4.41683993064797272821e-3),
+                static_cast<RealType>(3.37834206192286709492e-4),
+                static_cast<RealType>(1.18951465786445720729e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -16) {
+            RealType t = -x - 8;
+
+            // Rational Approximation
+            // Maximum Relative Error: 8.8272e-18
+            static const RealType P[7] = {
+                static_cast<RealType>(1.18246847255744057280e0),
+                static_cast<RealType>(8.41320657699741240497e-1),
+                static_cast<RealType>(2.55093097377551881478e-1),
+                static_cast<RealType>(4.21261576802732715976e-2),
+                static_cast<RealType>(3.98805044659990523312e-3),
+                static_cast<RealType>(2.04688276265993954527e-4),
+                static_cast<RealType>(4.43354791268634655473e-6),
+            };
+            static const RealType Q[7] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(7.07103973315808077783e-1),
+                static_cast<RealType>(2.13664682181055450396e-1),
+                static_cast<RealType>(3.52218225168465984709e-2),
+                static_cast<RealType>(3.33218664347896435919e-3),
+                static_cast<RealType>(1.71025807471868853268e-4),
+                static_cast<RealType>(3.70441884597642042665e-6),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -32) {
+            RealType t = -x - 16;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.6236e-18
+            static const RealType P[6] = {
+                static_cast<RealType>(1.19497306481411168356e0),
+                static_cast<RealType>(3.90497195765498241356e-1),
+                static_cast<RealType>(5.13120330037626853257e-2),
+                static_cast<RealType>(3.38574023921119491471e-3),
+                static_cast<RealType>(1.12075935888344736993e-4),
+                static_cast<RealType>(1.48743616420183584738e-6),
+            };
+            static const RealType Q[6] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(3.26493785348088598123e-1),
+                static_cast<RealType>(4.28813205161574223713e-2),
+                static_cast<RealType>(2.82893073845390254969e-3),
+                static_cast<RealType>(9.36442365966638579335e-5),
+                static_cast<RealType>(1.24281651532469125315e-6),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0688e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23238998449671083670041452413316011920e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.14900991369455846775267187236501987891e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19132787054572299485638029221977944555e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87295743700300806662745209398368996653e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.41994520703802035725356673887766112213e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78782099629586443747968633412271291734e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05200546520666366552864974572901349343e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.51453477916196630939702866688348310208e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15461354910584918402088506199099270742e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43371674256124419899137414410592359185e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35849788347057186916350200082990102088e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.50359296597872967493549820191745700442e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21838020977580479741299141050400953125e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.46723648594704078875476888175530463986e-12),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.98700317671474659677458220091101276158e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00405631175818416028878082789095587658e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04189939150805562128632256692765842568e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.03621065280443734565418469521814125946e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85722257874304617269018116436650330070e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.24191409213079401989695901900760076094e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.64269032641964601932953114106294883156e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19289631274036494326058240677240511431e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41389309719775603006897751176159931569e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42000309062533491486426399210996541477e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02436961569668743353755318268149636644e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50130875023154569442119099173406269991e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.1815e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62598955251978523174755901843430986522e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08127698872954954678270473317137288772e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70144997468767751317246482211703706086e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49486603823046766249106014234315835102e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07186495389828596786579668258622667573e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98334953533562948674335281457057445421e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.44119017374895211020429143034854620303e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27080759819117162456137826659721634882e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53892796920597912362370019918933112349e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30530442651657077016130554430933607143e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.04837779538527662990102489150650534390e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.94354615171320374997141684442120888127e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30746545799073289786965697800049892311e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41870129065056783732691371215602982173e-9),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.75919235734607601884356783586727272494e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.57656678936617227532275100649989944452e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72617552401870454676736869003112018648e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.59238104942208254162102314312757621047e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06040513359343987972917295603514840777e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26922840063034349024167652148593396307e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25628506630180107357627955876231943531e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81600387497542714853225329159728694926e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08210973846891324886779444820838563800e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.68632477858150229792523037059221563861e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43542789104866782087701759971538600076e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70594730517167328271953424328890849790e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30162314557860623869079601905904538470e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType s = exp(2 * x * x * x / 27) / sqrt(-x * x * x);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 6.4678e-36
+            static const RealType P[16] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.31806744221966404520449104514474066823e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50292887071777664663197915067642779665e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45140067157601150721516139901304901854e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93227973605511286112712730820664209900e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74259108933048973391560053531348126900e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77677252890665602191818487592154553094e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71843197238558832510595724454548089268e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.62811778285151415483649897138119310816e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74127763877120261698596916683136227034e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.24832552591462216226478550702845438540e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.93381036027487259940171548523889481080e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02261328789519398745019578211081412570e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.75409238451885381267277435341417474231e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09526311389365895099871581844304449319e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96371756262605118060185816854433322493e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88472819535099746216179119978362211227e-10),
+            };
+            static const RealType Q[16] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68923525157720774962908922391133419863e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40714902096062779527207435671907059131e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73120596883364361220343183559076165363e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56331267512666685349409906638266569733e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80956276267438042306216894159447642323e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34213468750936211385520570062547991332e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.50081600968590616549654807511166706919e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47297208240850928379158677132220746750e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73392976579560287571141938466202325901e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13858821123741335782695407397784840241e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.04103497389656828224053882850778186433e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81040189127998139689091455192659191796e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42176283104790992634826374270801565123e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64077137545614380065714904794220228239e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08139724991616322332901357866680220241e-10),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -8) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 3.5975e-36
+            static const RealType P[16] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10294551528734705945662709421382590676e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26135857114883288617323671166863478751e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23504465936865651893193560109437792738e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41598983788870071301270649341678962009e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43871304031224174103636568402522086316e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22745720458050596514499383658714367529e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05976431838299244997805790000128175545e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32087500190238014890030606301748111874e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32754445514451500968404092049839985196e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31866016448921762610690552586049011375e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.80197257671079297305525087998125408939e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.44212088947602969374978384512149432847e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.38857170416924025226203571589937286465e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20239999218390467567339789443070294182e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93965060142992479149039624149602039394e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36407983918582149239548869529460234702e-12),
+            };
+            static const RealType Q[16] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99867960957804580209868321228347067213e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94236623527818880544030470097296139679e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21644866845440678050425616384656052588e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48653919287388803523090727546630060490e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88696531788490258477870877792341909659e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11157356307921406032115084386689196255e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11071149696069503480091810333521267753e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95274844731679437274609760294652465905e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77971280158253322431071249000491659536e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18092258028773913076132483326275839950e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87773088535057996947643657676843842076e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99609277781492599950063871899582711550e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00465660598924300723542908245498229301e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29174652982710100418474261697035968379e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31746082236506935340972706820707017875e-12),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -16) {
+            RealType t = -x - 8;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.6792e-35
+            static const RealType P[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18246847255744057280356900905660312795e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77955886026107125189834586992142580148e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24948425302263641813107623611637262126e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42593662659560333324287312162818766556e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62714138002904073145045478360748042164e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56008984285541289474850396553042124777e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84858048549330525583286373950733005244e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30578460156038467943968005946143934751e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.93974868941529258700281962314167648967e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95086664204515648622431580749060079100e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57811968176644056830002158465591081929e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27814751838906948007289825582251221538e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06762893426725920159998333647896590440e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15388861641344998301210173677051088515e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83956842740198388242245209024484381888e-29),
+            };
+            static const RealType Q[14] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50056124032615852703112365430040751173e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05112559537845833793684655693572118348e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.55609497026127521043140534271852131858e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36430652394614121156238070755223942728e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98167215021940993097697777547641188697e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.89418831310297071347013983522734394061e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.10980717618462843498917526227524790487e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.80119618735773019675212434416594954984e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13748676086657187580746476165248613583e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15424395860921826755718081823964568760e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.75228896859720124469916340725146705309e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72759238269315282789451836388878919387e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79966603543593799412565926418879689461e-12),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -32) {
+            RealType t = -x - 16;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.1744e-36
+            static const RealType P[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19497306481411168355692832231058399132e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.15593166681833539521403250736661720488e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54020260738207743315755235213180652303e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76467972857585566189917087631621063058e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.97922795572348613358915532172847895070e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.26998967192207380100354278434037095729e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.32827180395699855050424881575240362199e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50587178182571637802022891868380669565e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78252548290929962236994183546354358888e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01519297007773622283120166415145520855e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29602226691665918537895803270497291716e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53666531487585211574942518181922132884e-14),
+            };
+            static const RealType Q[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.82230649578130958108098853863277631065e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12412482738973738235656376802445565005e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98320116955422615960870363549721494683e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99756654189000467678223166815845628725e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40414942475279981724792023159180203408e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78118445466942812088955228016254912391e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25827002637577602812624580692342616301e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.99604467789028963216078448884632489822e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.48237134334492289420105516726562561260e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08288201960155447241423587030002372229e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.29720612489952110448407063201146274502e-14),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -64) {
+            RealType t = -x - 32;
+
+            // Rational Approximation
+            // Maximum Relative Error: 3.4699e-36
+            static const RealType P[10] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19659414007358083585943280640656311534e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36969140730640253987817932335415532846e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21946928005759888612066397569236165853e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08341720579009422518863704766395201498e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44908614491286780138818989614277172709e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.54172482866925057749338312942859761961e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.49281630950104861570255344237175124548e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27586759709416364899010676712546639820e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00054716479138657682306851175059678989e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48798342894235412426464893852098239746e-14),
+            };
+            static const RealType Q[10] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81588658109851219975949691772676519853e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52583331848892383968186924120872369151e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57644670426430994363913234422346706991e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21080164634428298820141591419770346977e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79484074949580980980061103238709314326e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.93167250146504946763386377338487557826e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06604193118724797924138056151582242604e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35999937789324222934257460080153249173e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91435929481043135336094426837156247599e-14),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+    if (x >= 0) {
+        return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - mapairy_cdf_minus_imp_prec(x, tag) : mapairy_cdf_minus_imp_prec(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - mapairy_cdf_minus_imp_prec(x, tag) : mapairy_cdf_minus_imp_prec(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+    //
+    // This calculates the cdf of the Map-Airy distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::cdf(mapairy<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = mapairy_cdf_imp_prec(u, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.375) {
+        RealType t = p - 0.375;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.5488e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(-1.17326074020471664075e0),
+            static_cast<RealType>(1.51461298154568349598e0),
+            static_cast<RealType>(1.19979368094343490487e1),
+            static_cast<RealType>(-5.94882121521324108164e0),
+            static_cast<RealType>(-2.20619749774447254528e1),
+            static_cast<RealType>(7.17766543775229176131e0),
+            static_cast<RealType>(4.79284243496552841508e0),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.76268072706610602584e0),
+            static_cast<RealType>(-4.88492535243404839734e0),
+            static_cast<RealType>(-5.67524172432687656881e0),
+            static_cast<RealType>(6.83327389947131710596e0),
+            static_cast<RealType>(2.91338085774159042709e0),
+            static_cast<RealType>(-1.41108918944159283950e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.5181e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(-1.63281240925531302762e0),
+            static_cast<RealType>(-4.92351310795930780147e0),
+            static_cast<RealType>(1.43448529253101759409e1),
+            static_cast<RealType>(3.33182629948094299473e1),
+            static_cast<RealType>(-3.06679026539368582747e1),
+            static_cast<RealType>(-2.87298447423841965301e1),
+            static_cast<RealType>(1.31575930750093554120e1),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.38761652244702318296e0),
+            static_cast<RealType>(2.40932080746189543284e0),
+            static_cast<RealType>(-1.69465870062123632126e1),
+            static_cast<RealType>(-6.39998944283654848809e0),
+            static_cast<RealType>(1.27168434054332272391e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.3028e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-2.18765177572396469657e0),
+            static_cast<RealType>(-3.65752788934974426531e1),
+            static_cast<RealType>(-1.81144810822028903904e2),
+            static_cast<RealType>(-1.22434531262312950288e2),
+            static_cast<RealType>(8.99451018491165823831e2),
+            static_cast<RealType>(9.11333307522308410858e2),
+            static_cast<RealType>(-8.76285742384616909177e2),
+            static_cast<RealType>(-2.33786726970025938837e2),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.91797638291395345792e1),
+            static_cast<RealType>(1.24293724082506952768e2),
+            static_cast<RealType>(2.82393116012902543276e2),
+            static_cast<RealType>(-1.80472369158936285558e1),
+            static_cast<RealType>(-5.31764390192922827093e2),
+            static_cast<RealType>(-5.60586018315854885788e1),
+            static_cast<RealType>(1.21284324755968033098e2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.1147e-18
+        static const RealType P[6] = {
+            static_cast<RealType>(-2.18765177572396470773e0),
+            static_cast<RealType>(-2.19887766409334094428e0),
+            static_cast<RealType>(-7.77080107207360785208e-1),
+            static_cast<RealType>(-1.15551765136654549650e-1),
+            static_cast<RealType>(-6.64711321022529990367e-3),
+            static_cast<RealType>(-9.74212491048543799073e-5),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.91919722132624625590e-1),
+            static_cast<RealType>(2.17415447268626558639e-1),
+            static_cast<RealType>(2.41474762519410575392e-2),
+            static_cast<RealType>(9.41084107182696904714e-4),
+            static_cast<RealType>(6.65754108797614202364e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0508e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-2.59822399410385085335e0),
+            static_cast<RealType>(-2.24306757759003016244e0),
+            static_cast<RealType>(-7.36208578161752060979e-1),
+            static_cast<RealType>(-1.15130762650287391576e-1),
+            static_cast<RealType>(-8.77652386123688618995e-3),
+            static_cast<RealType>(-2.96358888256575251437e-4),
+            static_cast<RealType>(-3.33661282483762192446e-6),
+            static_cast<RealType>(-4.19292241201527861927e-9),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.23065798041556418844e-1),
+            static_cast<RealType>(1.96731305131315877264e-1),
+            static_cast<RealType>(2.49952034298034383781e-2),
+            static_cast<RealType>(1.49149568322111062242e-3),
+            static_cast<RealType>(3.66010398525593921460e-5),
+            static_cast<RealType>(2.46857713549279930857e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.1997e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-3.67354365380697580447e0),
+            static_cast<RealType>(-1.52181685844845957618e0),
+            static_cast<RealType>(-2.40883948836320845233e-1),
+            static_cast<RealType>(-1.82424079258401987512e-2),
+            static_cast<RealType>(-6.75844978572417703979e-4),
+            static_cast<RealType>(-1.11273358356809152121e-5),
+            static_cast<RealType>(-6.12797605223700996671e-8),
+            static_cast<RealType>(-3.78061321691170114390e-11),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.57770840766081587688e-1),
+            static_cast<RealType>(4.81290550545412209056e-2),
+            static_cast<RealType>(3.02079969075162071807e-3),
+            static_cast<RealType>(8.89589626547135423615e-5),
+            static_cast<RealType>(1.07618717290978464257e-6),
+            static_cast<RealType>(3.57383804712249921193e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.4331e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-4.92187819510636697128e0),
+            static_cast<RealType>(-9.94924018698264727979e-1),
+            static_cast<RealType>(-7.69914962772717316098e-2),
+            static_cast<RealType>(-2.85558010159310978248e-3),
+            static_cast<RealType>(-5.19022578720207406789e-5),
+            static_cast<RealType>(-4.19975546950263453259e-7),
+            static_cast<RealType>(-1.13886013623971006760e-9),
+            static_cast<RealType>(-3.46758191090170732580e-13),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.77270673840643360017e-1),
+            static_cast<RealType>(1.18099604045834575786e-2),
+            static_cast<RealType>(3.66889581757166584963e-4),
+            static_cast<RealType>(5.34484782554469770841e-6),
+            static_cast<RealType>(3.19694601727035291809e-8),
+            static_cast<RealType>(5.24649233511937214948e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.7742e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-6.41443550638291133784e0),
+            static_cast<RealType>(-6.38369359780748328332e-1),
+            static_cast<RealType>(-2.43420704406734621618e-2),
+            static_cast<RealType>(-4.45274771094277987075e-4),
+            static_cast<RealType>(-3.99529078051262843241e-6),
+            static_cast<RealType>(-1.59758677464731620413e-8),
+            static_cast<RealType>(-2.14338367751477432622e-11),
+            static_cast<RealType>(-3.23343844538964435927e-15),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.79845511272943785289e-2),
+            static_cast<RealType>(2.90839059356197474893e-3),
+            static_cast<RealType>(4.48172838083912540123e-5),
+            static_cast<RealType>(3.23770691025690100895e-7),
+            static_cast<RealType>(9.60156044379859908674e-10),
+            static_cast<RealType>(7.81134095049301988435e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.2451e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-8.23500806363233610938e0),
+            static_cast<RealType>(-4.05652655284908839003e-1),
+            static_cast<RealType>(-7.65978833819859622912e-3),
+            static_cast<RealType>(-6.94194676058731901672e-5),
+            static_cast<RealType>(-3.08771646223818451436e-7),
+            static_cast<RealType>(-6.12443207313641110962e-10),
+            static_cast<RealType>(-4.07882839359528825925e-13),
+            static_cast<RealType>(-3.05720104049292610799e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.37395212065018405474e-2),
+            static_cast<RealType>(7.18654254114820140590e-4),
+            static_cast<RealType>(5.50371158026951899491e-6),
+            static_cast<RealType>(1.97583864365011234715e-8),
+            static_cast<RealType>(2.91169706068202431036e-11),
+            static_cast<RealType>(1.17716830382540977039e-14),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -256) {
+        RealType t = -log2(ldexp(p, 128));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.8732e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-1.04845570631944023913e1),
+            static_cast<RealType>(-2.56502856165700644836e-1),
+            static_cast<RealType>(-2.40615394566347412600e-3),
+            static_cast<RealType>(-1.08364601171893250764e-5),
+            static_cast<RealType>(-2.39603255140022514289e-8),
+            static_cast<RealType>(-2.36344017673944676435e-11),
+            static_cast<RealType>(-7.83146284114485675414e-15),
+            static_cast<RealType>(-2.92218240202835807955e-19),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.17740414929742679904e-2),
+            static_cast<RealType>(1.78084231709097280884e-4),
+            static_cast<RealType>(6.78870668961146609668e-7),
+            static_cast<RealType>(1.21313439060489363960e-9),
+            static_cast<RealType>(8.89917934953781122884e-13),
+            static_cast<RealType>(1.79115540847944524599e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -512) {
+        RealType t = -log2(ldexp(p, 256));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.6946e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-1.32865827226175698181e1),
+            static_cast<RealType>(-1.61802434199627472010e-1),
+            static_cast<RealType>(-7.55642602577784211259e-4),
+            static_cast<RealType>(-1.69457608092375302291e-6),
+            static_cast<RealType>(-1.86612389867293722402e-9),
+            static_cast<RealType>(-9.17015770142364635163e-13),
+            static_cast<RealType>(-1.51422473889348610974e-16),
+            static_cast<RealType>(-2.81661279271583206526e-21),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.08518414679241420227e-2),
+            static_cast<RealType>(4.42335224797004486239e-5),
+            static_cast<RealType>(8.40387821972524402121e-8),
+            static_cast<RealType>(7.48486746424527560620e-11),
+            static_cast<RealType>(2.73676810622938942041e-14),
+            static_cast<RealType>(2.74588200481263214866e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -1024) {
+        RealType t = -log2(ldexp(p, 512));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.7586e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-1.67937186583822375593e1),
+            static_cast<RealType>(-1.01958138247797604098e-1),
+            static_cast<RealType>(-2.37409774265951876695e-4),
+            static_cast<RealType>(-2.65483321307104128810e-7),
+            static_cast<RealType>(-1.45803536947907216594e-10),
+            static_cast<RealType>(-3.57375116523338994342e-14),
+            static_cast<RealType>(-2.94401318006358820268e-18),
+            static_cast<RealType>(-2.73260616170245224789e-23),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.41357843707822974161e-3),
+            static_cast<RealType>(1.10082540037527566536e-5),
+            static_cast<RealType>(1.04338126042963003178e-8),
+            static_cast<RealType>(4.63619608458569600346e-12),
+            static_cast<RealType>(8.45781310395535984099e-16),
+            static_cast<RealType>(4.23432554226506409568e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        result = -std::numeric_limits<RealType>::infinity();
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.4375) {
+        RealType t = p - 0.4375;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.2901e-35
+        static const RealType P[10] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.48344198262277235851026749871350753173e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18249834490570496537675012473572546187e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20191368895639224466285643454767208281e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.88388953372157636908236843798588258539e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.59477796311326067051769635858472572709e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88799146700484120781026039104654730797e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.15708831983930955608517858269193800412e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.01389336086567891484877690859385409842e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.16683694881010716925933071465043323946e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.04356966421177683585461937085598186805e1),
+        };
+        static const RealType Q[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75444066345435020043849341970820565274e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.95105673975812427406540024601734210826e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.20381124524894051002242766595737443257e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48370658634610329590305283520183480026e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.52213602242009530270284305006282822794e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.91028722773916006242187843372209197705e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.76130245344411748356977700519731978720e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30834721900169773543149860814908904224e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.37863084758381651884340710544840951679e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46880981703613838666108664771931239970e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.375) {
+        RealType t = p - 0.375;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.8433e-36
+        static const RealType P[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.17326074020471664204142312429732771661e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23412560010002723970559712941124583385e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83665111310407767293290698145068379130e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.38459476870110655357485107373883403534e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.28751995328228442619291346921055105808e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.31663592034507247231393516167247241037e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13629333446941271397790762651183997586e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.80674058829101054663235662701823250421e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.53226182094253065852552393446365315319e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.14713948941614711932063053969010219677e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62979741122708118776725634304028246971e0),
+        };
+        static const RealType Q[10] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10550060286464202595779024353437346419e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.15893254630199957990897452211066782021e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.58964066823516762861256609311733069353e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73352515261971291505497909338586980605e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.64737859211974163695241658186141083513e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.79137714768236053008878088337762178011e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.71851514659301019977259792564627124877e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.37210093190088984630526671624779422232e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06793750951779308425209267821815264457e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.9072e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63281240925531315038207673147576291783e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72733898245766165408685147762489513406e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.48666841594842113608962500631836790675e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.38711336213357101067420572773139678571e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.19536066931882831915715343914510496760e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70911330354860558400876197129777829223e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46138758869321272507090399082047865434e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.42653825421465476333482312795245170700e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68040069633027903153088221686431049116e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.63017854949929226947577854802720988740e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.57362168966659376351959631576588023516e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.48386631313725080746815524770260451090e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03293129698111279047104766073456412318e1),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29511778027351594854005887702013466376e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66155745848864270109281703659789474448e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25628362783798417463294553777015370203e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.93162726153946899828589402901015679821e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.51582398149308841534372162372276623400e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55512400116480727630652657714109740448e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.11949742749256615588470329024257669470e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28090154738508864776480712360731968283e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.44307717248171941824014971579691790721e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.33595130666758203099507440236958725924e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76156378002782668186592725145930755636e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.70446647862725980215630194019740606935e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.9092e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467019660e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16991481696416567893311341049825218287e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25497491118598918048058751362064598010e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.00259915194411316966036757165146681474e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.20350803730836873687692010728689867756e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.75441278117456011071671644613599089820e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18844967505497310645091822621081741562e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84771867850847121528386231811667556346e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.78112436422992766542256241612018834150e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.82617957794395420193751983521804760378e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.77260227244465268981198741998181334875e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.61918290776044518321561351472048170874e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10309368217936941851272359946015001037e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68917274690585744147547352309416731690e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.96914697182030973966321601422851730384e4),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98063872144867195074924232601423646991e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65911346382127464683324945513128779971e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02451223307009464199634546540152067898e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.12662676019712475980273334769644047369e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.77637305574675655673572303462430608857e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.65900204382557635710258095712789133767e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.61649498173261886264315880770449636676e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.29867325788870863753779283018061152414e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.31375646045453788071216808289409712455e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91053361331987954531162452163243245571e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30917504462260061766689326034981496723e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.95779171217851232246427282884386844906e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.07234815204245866330282860014624832711e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21353269292094971546479026200435095695e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.9653e-35
+        static const RealType P[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467025793e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.94718878144788678915739777385667044494e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.01760622104142726407095836139719210570e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.27585388152893587017559610649258643106e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.26494992809545184138230791849722703452e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.19962820888633928632710264415572027960e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.10249328404135065767844288193594496173e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.94733898567966142295343935527193851633e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.10350856810280579594619259121755788797e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23852908701349250480831167491889740823e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.61008160195204632725691076288641221707e-10),
+        };
+        static const RealType Q[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59109221235949005113322202980300291082e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07119192591092503378838510797916225920e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97313678065269932508447079892684333156e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.85743007214453288049750256975889151838e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21504290861269099964963866156493713716e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00880286431998922077891394903879512720e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78806057460269900288838437267359072282e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15390284861815831078443996558014864171e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09877166004503937701692216421704042881e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01544823753120969225271131241177003165e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.7872e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.59822399410385083283727681965013517187e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.30676107401101401386206170152508285083e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.14999782004905950712290914501961213222e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33941786334132569296061539102765384372e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.67220197146826865151515598496049341734e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.80553562310354708419148501358813792297e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.69365728863553037992854715314245847166e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.66571611322125393586164383361858996769e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.60112572827002965346926427208336150737e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.82368436189138780270310776927920829805e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.53112953085778860983110669544602606343e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.47363651755817041383574210879856850108e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.56959356177318833325064543662295824581e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16259632533790175212174199386945953139e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51102540845397821195190063256442894688e-18),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51733661576324699382035973518172469602e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01435607980568082538278883569729476204e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93274478117803447229185270863587786287e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.79695020433868416640781960667235896490e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64179255575983014759473815411232853821e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88411076775875459504324039642698874213e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47924359965537384942568979646011627522e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.80915944234873904741224397674033111178e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67530059257263142305079790717032648103e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.59778634436027309520742387952911132163e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.45772841855129835242992919296397034883e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40356170422999016176996652783329671363e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31127037096552892520323998665757802862e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.6679e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.67354365380697578246790709817724831418e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.98681625368564496421038758088088788795e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07310677200866436332040539417232353673e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.24429836496456823308103613923194387860e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.02985399190977938381625172095575017346e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.76782196972948240235456454778537838123e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.74449002785643398012450514191731166637e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.59599894044461264694825875303563328822e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.25326249969126313897827328136779597159e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.41714701672521323699602179629851858792e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.43197925999694667433180053594831915164e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.84385683045691486021670951412023644809e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34484740544060627138216383389282372695e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.69717198111130468014375331439613690658e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54464319402577486444841981479085908190e-22),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.56568169258142086426383908572004868200e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52144703581828715720555168887427064424e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87268567039210776554113754014224005739e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.04907480436107533324385788289629535047e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05063218951887755000006493061952858632e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.88707869862323507236241669797692957827e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12876335369047582931728838551780783006e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96657547014655679104867167083078285517e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05799908632250375607393338998205481867e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.26543514080500125624753383852230043206e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02102501711063497529014782040893679505e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91577723105757841509716090936343311518e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13824283239122976911704652025193325941e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.6323e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.92187819510636694694450607724165689649e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97763858433958798529675258052376253402e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51315096979196319830162238831654165509e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.63462872759639470195664268077372442947e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.42843455093529447002457295994721102683e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.09839699044798405685726233251577671229e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.42918585783783247934440868680748693033e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.39927851612709063686969934343256912856e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.08811978806833318962489621493456773153e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.05790315329766847040100971840989677130e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.45479905512618918078640786598987515012e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.26725031195260767541308143946590024995e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.93921283405116349017396651678347306610e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.46989755992471397407520449698676945629e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84098833615882764168840211033822541979e-26),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76933186134913044021577076301874622292e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25794095712489484166470336696962749356e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02367257449622569623375613790000874499e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72422948147678152291655497515112236849e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54841786738844966378222670550160421679e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40690766057741905625149753730480294357e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.57722740290698689456097239435447030950e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12202417878861628530322715231540006386e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.52053248659561670052645118655279630611e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.93156242508301535729374373870786335203e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40767922796889118151219837068812449420e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83472702205100162081157644960354192597e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07575352729625387198150555665307193572e-24),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.8799e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.41443550638291131009585191506467028820e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.27887396494095561461365753577189254063e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12752633002089885479040650194288302309e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.79073355729340068320968150408320521772e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.92104558368762745368896313096467732214e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.31521786147036353766882145733055166296e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.69209485282228501578601478546441260206e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.17440286764020598209076590905417295956e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.24323354132100896221825450145208350291e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53395893728239001663242998169841168859e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.68737623513761169307963299679882178852e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34293243065056704017609034428511365032e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16077944943653158589001897848048630079e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.62195354664281744711336666974567406606e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34400562353945663460416286570988365992e-30),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87838171063584994806998206766890809367e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55395225505766120991458653457272783334e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.45282436421694718640472363162421055686e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29570159526914149727970023744213510609e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75502365627517415214497786524319814617e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.74140267916464056408693097635546173776e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.53554952415602030474322188152855226456e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25818606585833092910042975933757268581e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79945579370700383986587672831350689541e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64188969985517050219881299229805701044e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.59811800080967790439078895802795103852e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28225402720788909349967839966304553864e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.22313199865592821923485268860178384308e-28),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1548e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.23500806363233607692361021471929016922e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16747938711332885952564885548768072606e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.58252672740225210061031286151136185818e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.15477223656783400505701577048140375949e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.51130817987857130928725357067032472382e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68955185187558206711296837951129048907e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.30418343536824247801373327173028702308e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.96029044368524575193330776540736319950e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53259926294848786440686413056632823519e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.09476918795964320022985872737468492126e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.20864569882477440934325776445799604204e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.01321468510611172635388570487951907905e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.45079221107904118975166347269173516170e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.36559452694774774399884349254686988041e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.92396730553947142987611521115040472261e-35),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36599681872296382199486815169747516110e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.86330544720458446620644055149504593514e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.23793435123936109978741252388806998743e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41867848381419339587560909646887411175e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46493580168298395584601073832432583371e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03537470107933172406224278121518518287e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00375884189083338846655326801486182158e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62515041281615938158455493618149216047e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42337949780187570810208014464208536484e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40196890950995648233637422892711654146e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.11894256193449973803773962108906527772e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00900961462911160554915139090711911885e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65825716532665817972751320034032284421e-32),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -256) {
+        RealType t = -log2(ldexp(p, 128));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.3756e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.04845570631944023525776899386112795330e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.18146685146173151383718092529868406030e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.13255476532916847606354932879190731233e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.44228173780288838603949849889291143631e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.18663599891768480607165516401619315227e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.61193813386433438633008774630150180359e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54402603714659392010463991032389692959e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.76816632514967325885563032378775486543e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.22774672528068516513970610441705738842e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47312348271366325243169398780745416279e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.10984325972747808970318612951079014854e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.81620524028936785168005732104270722618e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.03443227423068771484783389914203726108e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.02313300749670214384591200940841254958e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.40321396496046206171642334628524367374e-39),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67292043485384876322219919215413286868e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61652550158809553935603664087740554258e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14722810796821047167211543031044501921e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.78954660078305461714050086730116257387e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52794892087101750452585357544956835504e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59652255206657812422503741672829368618e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84914442937017449248597857220675602148e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23662183613814475007146598734598810102e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.55388618781592901470236982277678753407e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.20418178834057564300014964843066904024e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48606639104883413456676877330419513129e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39845313960416564778273486179935754019e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14538443937605324316706211070799970095e-35),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -512) {
+        RealType t = -log2(ldexp(p, 256));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.6639e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32865827226175697711590794217590458484e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27551166309670994513910580518431041518e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.57161482253140058637495100797888501265e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.26908727392152312216118985392395130974e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.31391169101865809627389212651592902649e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.58926174475498352884244229017384309804e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.97074898765380614681225071978849430802e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.59852103341093122669197704225736036199e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.97287954178083606552531325613580819555e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.57634773176875526612407357244997035312e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34467233210713881817055138794482883359e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.91236170873875898506577053309622472122e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.12220990075567880730037575497818287435e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.20881889651487527801970182542596258873e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56848486878078288956741060120464349537e-43),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33267370502089423930888060969568705647e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39632352029900752622967578086289898150e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42703739831525305516280300008439396218e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45767617531685380458878368024246654652e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40344962756110545138002101382437142038e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.47015258371290492450093115369080460499e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.97280918936580227687603348219414768787e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40441024286579579491205384492088325576e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26130000914236204012152918399995098882e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.03893990417552709151955156348527062863e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12687002255767114781771099969545907763e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74218645918961186861014420578277888513e-35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36897549168687040570349702061165281706e-39),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -1024) {
+        RealType t = -log2(ldexp(p, 512));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0360e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.67937186583822375017526293948703697225e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.06681764321003187068904973985967908140e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12508887240195683379004033347903251977e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.56847823157999127998977939588643284176e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.31281869105767454049413701029676766275e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.01498951390503036399081209706853095793e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.72866867304007090391517734634589972858e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.44819806993104486828983054294866921869e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.91441365806306460165885645136864045231e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.71364347097027340365042558634044496149e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63601648491144929836375956218857970640e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.76948956673676441236280803645598939735e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.47367651137203634311843318915161504046e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.83187517541957887917067558455828915184e-41),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.21480186561579326423946788448005430367e-47),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16494591376838053609854716130343599036e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.97651667629616309497454026431358820357e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77741398674456235952879526959641925087e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.39478109667902532743651043316724748827e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35965905056304225411108295866332882930e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83206524996481183422082802793852630990e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30320324476590103123012385840054658401e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.30322948189714718819437477682869360798e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43729790298535728717477691270336818161e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.89788697114251966298674871919685298106e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43510901856942238937717065880365530871e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38232043389918216652459244727737381677e-38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64599465785019268214108345671361994702e-43),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -2048) {
+        RealType t = -log2(ldexp(p, 1024));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.5130e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.11959316095291435774375635827672517008e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.30292575371366023255165927527306483022e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.54260157439166096303943109715675142318e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.61232819199170639867079290977704351939e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.74481972848503486840161528924694379655e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.98283577906243441829434029827766571263e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90691715740583828769850056130458574520e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.31354728925505346732804698899977180508e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42545288372836698650371589645832759416e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.12901629676328680681102537492164204387e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.99690040253176100731314099573187027309e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07899506956133955785140496937520311210e-35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.88607240095256436460507438213387199067e-40),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.78815984551154095621830792130401294111e-45),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20516030880916148179297554212609531432e-51),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81973541224235020744673910266545976833e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49156990107280109344880219729275939242e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21606730563542176411852745162267260946e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11449329529433741944366607648360521674e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35659138507940819452801802756409587220e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95708516718550485872934856595725983907e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78871290972777009292563576533612002908e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60955318960542258732596447917271198307e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72437581728117963125690670426402194936e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77473938855958487119889840032590783232e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66198494713809467076392278745811981500e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34142897042941614778352280692901008538e-42),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98791658647635156162347063765388728959e-47),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4096) {
+        RealType t = -log2(ldexp(p, 2048));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.1220e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.67307564006689676593687414536012112755e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.21005690250741024744367516466433711478e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.11537345869365655126739041291119096558e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.82910297156061391001507891422501792453e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.51574933516708249049824513935386420692e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56433757960363802088718489136097249753e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.74248235865301086829849817739500215149e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.19151506367084295119369434315371762091e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.98518959000360170320183116510466814569e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.21330422702314763225472001861559380186e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.44346922987964428874014866468161821471e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.59773305152191273570416120169527607421e-39),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.81894412321532723356954669501665983316e-44),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.25766346856943928908756472385992861288e-49),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.44601448994095786447982489957909713982e-55),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90814053669730896497462224007523900520e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72450689508305973756255440356759005330e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76517273086984384225845151573287252506e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31844251885317815627707511621078762352e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22689324865113257769413663010725436393e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27524826460469866934006001123700331335e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39172850948322201614266822896191911031e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40343613937272428197414545004329993769e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.17936773028976355507339458927541970545e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66512598049860260933817550698863263184e-36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.06432209670481882442649684139775366719e-41),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10247886333916820534393624270217678968e-46),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40899321122058714028548211810431871877e-51),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8192) {
+        RealType t = -log2(ldexp(p, 4096));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.8974e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.36960987939726803544369406181770745475e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.17239311695985070524235502979761682692e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51192208811996535244435318068035492922e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.38938553034896173195617671475670860841e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.55156910900732478717648524688116855303e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.14905040433940475292279950923000597280e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.35237464492052939771487320880614968639e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.07937000518607459141766382199896010484e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.42797358100745086706362563988598447929e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.27871637324128856529004325499921407260e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.99553669724530906250814559570819049401e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.04272644552406682186928100080598582627e-42),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.70093315570856725077212325128817808000e-47),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.51767319872105260145583037426067406953e-53),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.87159268409640967747617639113346310759e-59),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45350026842128595165328480395513258721e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.30398532102631290226106936127181928207e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45242264812189519858570105609209495630e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.22745462510042159972414219082495434039e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31834645038348794443252730265421155969e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44590392528760847619123404904356730177e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08436623062305193311891193246627599030e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46542554766048266351202730449796918707e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78672067064478133389628198943161640913e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56573050761582685018467077197376031818e-39),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92145137276530136848088270840255715047e-44),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96933863894082533505471662180541379922e-49),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92661972206232945959915223259585457082e-55),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16384) {
+        RealType t = -log2(ldexp(p, 8192));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8819e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.24662793339079714510108682543625432532e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25841960642102016210295419419373971750e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.10589156998251704634852108689102850747e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18697614924486382142056819421294206504e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.79445222262445726654186491785652765635e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.41847338407338901513049755299049551186e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.44550500540299259432401029904726959214e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.97463434518480676079167684683604645092e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68404349202062958045327516688040625516e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.14018837476359778654965300153810397742e-35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.67726222606571327724434861967972555751e-40),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.48082398191886705229604237754446294033e-45),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.28534456209055262678153908192583037946e-51),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.99466700145428173772768099494881455874e-57),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.43473066278196981345209422626769148425e-63),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26570199429958856038191879713341034013e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32484776300757286079244074394356908390e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31234182027812869096733088981702059020e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13711443044675425837293030288097468867e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.11480036828082409994688474687120865023e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25592803132287127389756949487347562847e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45726006695535760451195102271978072855e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13082170504731110487003517418453709982e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48217827031663836930337143509338210426e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47389053144555736191304002865419453269e-42),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90980968229123572201281013063229644814e-47),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79448544326289688123648457587797649323e-53),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56179793347045575604935927245529360950e-59),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        result = -std::numeric_limits<RealType>::infinity();
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 1.8559e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(4.81512108276093785320e-1),
+            static_cast<RealType>(-2.74296316128959647914e0),
+            static_cast<RealType>(-3.29973875964825685757e1),
+            static_cast<RealType>(-4.87536980816224603581e1),
+            static_cast<RealType>(8.22233203036734027999e1),
+            static_cast<RealType>(1.21654607908452130093e2),
+            static_cast<RealType>(-6.66681853240657307279e1),
+            static_cast<RealType>(-4.28101952511581488588e1),
+        };
+        static const RealType Q[10] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.20189490825315245036e0),
+            static_cast<RealType>(1.63469912146101848441e1),
+            static_cast<RealType>(-1.52740920318273920072e1),
+            static_cast<RealType>(-5.41684560257839409762e1),
+            static_cast<RealType>(6.51733677169299416471e0),
+            static_cast<RealType>(3.93092001388102589237e1),
+            static_cast<RealType>(-9.59983666140749481195e-1),
+            static_cast<RealType>(-9.95648827557655863699e-1),
+            static_cast<RealType>(-1.32007124426778083829e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 4.6019e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.70276979914029733585e0),
+            static_cast<RealType>(2.09991992116646276165e1),
+            static_cast<RealType>(2.26775403775298867998e1),
+            static_cast<RealType>(-4.85384304722129472833e2),
+            static_cast<RealType>(-1.47107146466495573999e3),
+            static_cast<RealType>(-7.08748473959943943929e1),
+            static_cast<RealType>(1.54245210917147215257e3),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.13092357122115486375e1),
+            static_cast<RealType>(1.57318281834689144053e2),
+            static_cast<RealType>(4.42261730187813035957e2),
+            static_cast<RealType>(2.10814431586717588454e2),
+            static_cast<RealType>(-6.36700983439599552504e2),
+            static_cast<RealType>(-2.82923881266630617596e2),
+            static_cast<RealType>(1.36613971025062750340e2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2193e-19
+        static const RealType P[8] = {
+            static_cast<RealType>(4.25692449785074345588e-1),
+            static_cast<RealType>(3.10963501706596356267e-1),
+            static_cast<RealType>(2.91357806215297069863e-2),
+            static_cast<RealType>(2.34716342676849303244e-2),
+            static_cast<RealType>(5.83137296293361915583e-3),
+            static_cast<RealType>(3.71792415497884868748e-4),
+            static_cast<RealType>(1.59538372221030642757e-4),
+            static_cast<RealType>(4.74040834029330213692e-6),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.14801234415100707213e-1),
+            static_cast<RealType>(1.04693730144480856638e-1),
+            static_cast<RealType>(3.81581484862997435076e-2),
+            static_cast<RealType>(8.95334009127358617362e-3),
+            static_cast<RealType>(1.43316686981760147226e-3),
+            static_cast<RealType>(1.81367766024620080990e-4),
+            static_cast<RealType>(1.54779999748286671973e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.4418e-17
+        static const RealType P[11] = {
+            static_cast<RealType>(5.07341098045260541890e-1),
+            static_cast<RealType>(3.11771145411143166935e-1),
+            static_cast<RealType>(1.74515601081894060888e-1),
+            static_cast<RealType>(8.46576990174024231338e-2),
+            static_cast<RealType>(2.57510090204322149315e-2),
+            static_cast<RealType>(8.26605326867021684811e-3),
+            static_cast<RealType>(1.73081423934722046819e-3),
+            static_cast<RealType>(3.36314161099011673569e-4),
+            static_cast<RealType>(4.50990441180388912803e-5),
+            static_cast<RealType>(4.53513191985642134268e-6),
+            static_cast<RealType>(2.62304611053075404923e-7),
+        };
+        static const RealType Q[11] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.28225379952156944029e-1),
+            static_cast<RealType>(3.49662079845715371907e-1),
+            static_cast<RealType>(1.45408903426879603625e-1),
+            static_cast<RealType>(5.06773501409016231879e-2),
+            static_cast<RealType>(1.45385556714043243731e-2),
+            static_cast<RealType>(3.31235831325018043744e-3),
+            static_cast<RealType>(6.06977554525543056050e-4),
+            static_cast<RealType>(8.42406730405209749492e-5),
+            static_cast<RealType>(8.32337989541696717905e-6),
+            static_cast<RealType>(4.84923196546857128337e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.7932e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(5.41774626094491510395e-1),
+            static_cast<RealType>(4.11060141334529017898e-1),
+            static_cast<RealType>(1.48195601801946264526e-1),
+            static_cast<RealType>(3.33881552814492855873e-2),
+            static_cast<RealType>(5.20893974732203890418e-3),
+            static_cast<RealType>(5.84734765774178832854e-4),
+            static_cast<RealType>(4.71028150898133935445e-5),
+            static_cast<RealType>(2.59185739450631464618e-6),
+            static_cast<RealType>(7.77428184258777394627e-8),
+            static_cast<RealType>(2.51255632629650930196e-14),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.58341767924960527280e-1),
+            static_cast<RealType>(2.73511775500642961539e-1),
+            static_cast<RealType>(6.16011987856129890130e-2),
+            static_cast<RealType>(9.61296002312356116021e-3),
+            static_cast<RealType>(1.07890675777726076554e-3),
+            static_cast<RealType>(8.69223632953458271977e-5),
+            static_cast<RealType>(4.78248875031756169279e-6),
+            static_cast<RealType>(1.43460852065144859304e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.0396e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(5.41926067826974905066e-1),
+            static_cast<RealType>(4.86926556246548518715e-1),
+            static_cast<RealType>(2.11963908288176005856e-1),
+            static_cast<RealType>(5.92200639925655576883e-2),
+            static_cast<RealType>(1.18859816815542567438e-2),
+            static_cast<RealType>(1.76833662992855443754e-3),
+            static_cast<RealType>(2.21226152157950219596e-4),
+            static_cast<RealType>(1.50444847316426133872e-5),
+            static_cast<RealType>(1.87458213915373906356e-6),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.98511036742503939380e-1),
+            static_cast<RealType>(3.91130673008184655152e-1),
+            static_cast<RealType>(1.09277016228474605069e-1),
+            static_cast<RealType>(2.19328471889880028208e-2),
+            static_cast<RealType>(3.26305879571349016107e-3),
+            static_cast<RealType>(4.08222014684743492069e-4),
+            static_cast<RealType>(2.77611385768697969181e-5),
+            static_cast<RealType>(3.45911046256304795257e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else {
+        RealType p_square = p * p;
+
+        if (isnormal(p_square)) {
+            result = 1 / cbrt(p_square * constants::two_pi<RealType>());
+        }
+        else if (p > 0) {
+            result = 1 / (cbrt(p) * cbrt(p) * cbrt(constants::two_pi<RealType>()));
+        }
+        else {
+            result = std::numeric_limits<RealType>::infinity();
+        }
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.375) {
+        RealType t = p - 0.375;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 4.0835e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.00474815142578902619056852805926666121e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56422290947427848191079775267512708223e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.70103710180837859003070678080056933649e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08521918131449191445864593768320217287e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29340655781369686013042530147130581054e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.24198237124638368989049118891909723118e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.43382878809828906953609389440800537385e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.45564809127564867825118566276365267035e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75881247317499884393790698530115428373e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.55845932095942777602241134226597158364e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41328261385867825781522154621962338450e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06758225510372847658316203115073730186e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10895417312529385966062255102265009972e0),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88252553879196710256650370298744093367e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54875259600848880869571364891152935969e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.78589587338618424770295921221996471887e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.15356831947775532414727361010652423453e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12951532118504570745988981200579372124e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48163841544376327168780999614703092433e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56786609618056303930232548304847911521e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.25610739352108840474197350343978451729e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27063786175330237448255839666252978603e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.11941093895004369510720986032269722254e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.51487618026728514833542002963603231101e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 5.7633e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81512108276093787175849069715334402323e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24417080443497141096829831516758083481e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.67006165991083501886186268944009973084e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.74402382755828993223083868408545308340e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.49182541725192134610277727922493871787e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.67273564707254788337557775618297381267e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.73476432616329813096120568871900178919e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31235376166262024838125198332476698090e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.59379285677781413393733801325840617522e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.38151434050794836595564739176884302539e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33534676810383673962443893459127818078e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.38110822236764293910895765875742805411e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.42750073722992463087082849671338957023e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.54255748148299874514839812717054396793e2),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64823387375875361292425741663822893626e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02973633484731117050245517938177308809e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71288209768693917630236009171518272534e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23837527610546426062625864735895938014e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.05056816585729983223036277071927165555e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.48087477651935811184913947280572029967e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04631058325147527913398256133791276127e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69813394441679590721342220435891453447e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.92323371456465893290687995174952942311e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68542430563281320943284015587559056621e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.17969051793607842221356465819951568080e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82773308760283383020168853159163391394e2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 2.1140e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70276979914029738186601698003670175907e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63126762626382548478172664328434577553e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04190225271045202674546813475341133174e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.93523974140998850492859698545966806498e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19814006186501010136822066747124777014e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.55931423620290859807616748030589502039e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.78874021192395317496507459296221703565e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.03860533237347587977439662522389465152e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77882648875352690605815508748162607271e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05498612167816258406694194925933958145e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05326361485692298778330190198630232666e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.85827791876754731187453265804790139032e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.93719378006868242377955041137674308589e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56839957539576784391036362196229047625e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95604329277359828898502487252547842378e6),
+        };
+        static const RealType Q[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79208640567193066236912382037923299779e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94775812217734059201656828286490832145e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16467934643564936346029555887148320030e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35525720248600096849901920839060920346e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69760913594243328874861534307039589127e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.32330501005950982838953061458838040612e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.79610639577090112327353399739315606205e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.43314292923292828425630915931385776182e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.97538885038058371436244702169375622661e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.48431896958634429210349441846613832681e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93459449030820736960297236799012798749e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67200014823529787381847745962773726408e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.37035571075060153491151970623824940994e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.22682822001329636071591164177026394518e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09781406768816062486819491582960840983e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1409e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25692449785074345466504245009175450649e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75679137667345136118441108839649360362e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06171803174020856964914440692439080669e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87798066278592051163038122952593080648e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20070543183347459409303407166630392077e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13457391270614708627745403376469848816e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06743974464224003715510181633693539914e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16870984737226212814217822779976770316e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21845093091651861426944931268861694026e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.85357146081877929591916782097540632519e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.19085800299127898508052519062782284785e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41985644250494046067095909812634573318e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30857042700765443668305406695750760693e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10466412567107519640190849286913680449e-10),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31914248618040435028023418981527961171e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.73578090645412656850163531828709850171e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57329813782272411333511950903192234311e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62736127875896578315177123764520823372e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76809643836078823237530990091078867553e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32026948719622983920194944841520771986e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45051018027743807545734050620973716634e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58281707210621813556068724127478674938e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.63884527227517358294732620995363921547e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15973602356223075515067915930205826229e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35069439950884795002182517078104942615e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15454119109586223908613596754794988609e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55273685376557721039847456564342945576e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2521e-35
+        static const RealType P[23] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07341098045260497471001948654506267614e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16518383383878659278973043343250842753e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10029094208424121908983949243560936013e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04771840726172284780129819470963100749e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34173170868011689830672637082451998700e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41990262178664512140746911398264330173e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06779488545758366708787010705581103705e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41892665233583725631482443019441608726e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.20692306716979208762785454648538891867e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.11097906809673639231336894729060830995e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37476591232600886363441107536706973169e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02659053066396720145189153810309784416e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02209877191642023279303996697953314344e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.56663781532392665205516573323950583901e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95655734237060800145227277584749429063e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06357695252098035545383649954315685077e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78759045059235560356343893064681290047e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95881339136963512103591745337914059651e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70156441275519927563064848389865812060e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.99745225746277063516394774908346367811e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.45718440382347867317547921045052714102e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39027665085346558512961348663034579801e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05739751797738770096482688062542436470e-15),
+        };
+        static const RealType Q[23] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43370372582239919321785765900615222895e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52872159582703775260145036441128318159e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28243735290178057451806192890274584778e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.93375398009812888642212045868197435998e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.73364866677217419593129631900708646445e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53645928499107852437053167521160449434e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74280939589407863107682593092148442428e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80095449855178765594835180574448729793e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.65924845456946706158946250220103271334e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52170861715436344002253767944763106994e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87246437551620484806338690322735878649e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88631873230311653853089809596759382095e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84478812152918182782333415475103623486e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47998768403859674841488325856607782853e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82364683269852480160620586102339743788e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.65854316058742127585142691993199177898e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11358340340462071552670838135645042498e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22818744671190957896035448856159685984e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11038729491846772238262374112315536796e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.21355801166652957655438257794658921155e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41278271853370874105923461404291742454e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95100373579692323015092323646110838623e-15),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0703e-35
+        static const RealType P[21] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41774626094491452462664949805613444094e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96383089261273022706449773421031102175e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.16315295073029174376617863024082371446e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65377894193914426949840018839915119410e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33210993830236821503160637845009556016e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69315463529653886947182738378630780083e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09869947341518160436616160018702590834e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44331691052908906654005398143769791881e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13131413925652085071882765653750661678e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64441840437413591336927030249538399459e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78393581596372725434038621824715039765e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50239319821178575427758224587858938204e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92619647697287767235953207451871137149e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26901081456833267780600560830367533351e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12151768312254597726918329997945574766e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36907507996686107513673694597817437197e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31699373909892506279113260845246144240e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.11230682511893290562864133995544214588e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.44627067257461788044784631155226503036e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39869585157420474301450400944478312794e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.82128612844034824876694595066123093042e-27),
+        };
+        static const RealType Q[20] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65414405277042133067228113526697909557e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32179221250476209346757936207079534440e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.74217392682100275524983756207618144313e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45810448055940046896534973720645113799e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.81487408603233765436807980794697048675e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49442843848941402948883852684502731460e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66330842256792791665907478718489013963e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93285292223845804061941359223505045576e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87966347754794288681626114849829710697e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13711644429711675111080150193733607164e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61758862007482013187806625777101452737e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55435556106272558989915248980090731639e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34166571320580242213843747025082914011e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31411360099525131959755145015018410429e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.21684839228785650625270026640716752452e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43021096301255274530428188746599779008e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.58831290247776456235908211620983180005e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74309280855806399632683315923592902203e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58097100528573186098159133443927182780e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.4124e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926067826974814669251179264786585885e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21141529920003643675474888047093566280e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59964592861304582755436075901659426485e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95135112971576806260593571877646426022e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12322024725362032809787183337883163254e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.96758465518847580191799508363466893068e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12389553946694902774213055563291192175e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04599236076217479033545023949602272721e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.16143771174487665823565565218797804931e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38966874413947625866830582082846088427e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02590325514935982607907975481732376204e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44376747400143802055827426602151525955e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82088624006657184426589019067893704020e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95757210706845964048697237729100056232e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.36096213291559182424937062842308387702e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14362780521873256616533770657488533993e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73571098395815275003552523759665474105e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47286214854389274681661944885238913581e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73701196181204039400706651811524874455e-34),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77119890916406072259446489508263892540e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95177888809731859578167185583119074026e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.29131027214559081111011582466619105016e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31442657037887347262737789825299661237e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83928863984637222329515960387531101267e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07389089078167127136964851949662391744e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93013847797006474150589676891548600820e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50600573851533884594030683413819219915e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94539484213971921794449107859541806317e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58360895032645281635534287874266252341e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66414102108217999886628042310332365446e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07411076181287950822375436854492998754e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61224937285582228022463072515935601355e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.89242339209389981530783624934733098598e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11030225010379194015550512905872992373e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20285566539355859922818448335043495666e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71782855576364068752705740544460766362e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.1680e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926070139289008206183757488364846894e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78434820569480998586988738136492447574e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07939171933509333571821660328723436210e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.92438439347811482522082798370060349739e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24288918322433485413615362874371441367e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04437759300344740815274986587186340509e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74063952231188399929705762263485071234e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07228849610363181194047955109059900544e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93120850707001212714821992328252707694e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40911049607879914351205073608184243057e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71898232013947717725198847649536278438e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06963706982203753050300400912657068823e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.79849166632277658631839126599110199710e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74682085785152276503345630444792840850e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09650236336641219916377836114077389212e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97326394822836529817663710792553753811e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.26635728806398747570910072594323836441e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96470010392255781222480229189380065951e-18),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.82841492468725267177870050157374330523e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83703946702662950408034486958999188355e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09320896703777230915306208582393356690e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29346630787642344947323515884281464979e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77242894492599243245354774839232776944e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05722029871614922850936250945431594997e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66920224988248720006255827987385374411e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.40887155754772190509572243444386095560e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44545968319921473942351968892623238920e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17198676140022989760684932594389017027e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97376935482567419865730773801543995320e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06997835790265899882151030367297786861e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06862653266619706928282319356971834957e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02334307903766790059473763725329176667e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.33174535634931487079630169746402085699e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70989324903345102377898775620363767855e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.47067260145014475572799216996976703615e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else {
+        RealType p_square = p * p;
+
+        if (isnormal(p_square)) {
+            result = 1 / cbrt(p_square * constants::two_pi<RealType>());
+        }
+        else if (p > 0) {
+            result = 1 / (cbrt(p) * cbrt(p) * cbrt(constants::two_pi<RealType>()));
+        }
+        else {
+            result = std::numeric_limits<RealType>::infinity();
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+{
+    if (p > 0.5) {
+        return mapairy_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? mapairy_quantile_upper_imp_prec(p, tag) : mapairy_quantile_lower_imp_prec(p, tag);
+}
+
+template <class RealType>
+inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+{
+    if (p > 0.5) {
+        return mapairy_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? mapairy_quantile_upper_imp_prec(p, tag) : mapairy_quantile_lower_imp_prec(p, tag);
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_quantile_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+{
+    // This routine implements the quantile for the Map-Airy distribution,
+    // the value p may be the probability, or its complement if complement=true.
+
+    static const char* function = "boost::math::quantile(mapairy<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_probability(function, p, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = location + scale * mapairy_quantile_imp_prec(p, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>& tag)
+{
+    return static_cast<RealType>(-1.16158727113597068525);
+}
+
+template <class RealType>
+inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>& tag)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.1615872711359706852500000803029112987);
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_mode_imp(const mapairy_distribution<RealType, Policy>& dist)
+{
+    // This implements the mode for the Map-Airy distribution,
+
+    static const char* function = "boost::math::mode(mapairy<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = location + scale * mapairy_mode_imp_prec<RealType>(tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>& tag)
+{
+    return static_cast<RealType>(-0.71671068545502205332);
+}
+
+template <class RealType>
+inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>& tag)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.71671068545502205331700196278067230944440);
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_median_imp(const mapairy_distribution<RealType, Policy>& dist)
+{
+    // This implements the median for the Map-Airy distribution,
+
+    static const char* function = "boost::math::median(mapairy<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = location + scale * mapairy_median_imp_prec<RealType>(tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+{
+    return static_cast<RealType>(2.00727681841065634600);
+}
+
+template <class RealType>
+inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0072768184106563460003025875575283708);
+}
+
+template <class RealType, class Policy>
+inline RealType mapairy_entropy_imp(const mapairy_distribution<RealType, Policy>& dist)
+{
+    // This implements the entropy for the Map-Airy distribution,
+
+    static const char* function = "boost::math::entropy(mapairy<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = mapairy_entropy_imp_prec<RealType>(tag_type()) + log(scale);
+
+    return result;
+}
+
+} // detail
+
+template <class RealType = double, class Policy = policies::policy<> >
+class mapairy_distribution
+{
+    public:
+    typedef RealType value_type;
+    typedef Policy policy_type;
+
+    mapairy_distribution(RealType l_location = 0, RealType l_scale = 1)
+        : mu(l_location), c(l_scale)
+    {
+        static const char* function = "boost::math::mapairy_distribution<%1%>::mapairy_distribution";
+        RealType result = 0;
+        detail::check_location(function, l_location, &result, Policy());
+        detail::check_scale(function, l_scale, &result, Policy());
+    } // mapairy_distribution
+
+    RealType location()const
+    {
+        return mu;
+    }
+    RealType scale()const
+    {
+        return c;
+    }
+
+    private:
+    RealType mu;    // The location parameter.
+    RealType c;     // The scale parameter.
+};
+
+typedef mapairy_distribution<double> mapairy;
+
+#ifdef __cpp_deduction_guides
+template <class RealType>
+mapairy_distribution(RealType) -> mapairy_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+template <class RealType>
+mapairy_distribution(RealType, RealType) -> mapairy_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+#endif
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> range(const mapairy_distribution<RealType, Policy>&)
+{ // Range of permissible values for random variable x.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> support(const mapairy_distribution<RealType, Policy>&)
+{ // Range of supported values for random variable x.
+   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType pdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::mapairy_pdf_imp(dist, x);
+} // pdf
+
+template <class RealType, class Policy>
+inline RealType cdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::mapairy_cdf_imp(dist, x, false);
+} // cdf
+
+template <class RealType, class Policy>
+inline RealType quantile(const mapairy_distribution<RealType, Policy>& dist, const RealType& p)
+{
+    return detail::mapairy_quantile_imp(dist, p, false);
+} // quantile
+
+template <class RealType, class Policy>
+inline RealType cdf(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::mapairy_cdf_imp(c.dist, c.param, true);
+} //  cdf complement
+
+template <class RealType, class Policy>
+inline RealType quantile(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::mapairy_quantile_imp(c.dist, c.param, true);
+} // quantile complement
+
+template <class RealType, class Policy>
+inline RealType mean(const mapairy_distribution<RealType, Policy> &dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType variance(const mapairy_distribution<RealType, Policy>& /*dist*/)
+{
+    return std::numeric_limits<RealType>::infinity();
+}
+
+template <class RealType, class Policy>
+inline RealType mode(const mapairy_distribution<RealType, Policy>& dist)
+{
+    return detail::mapairy_mode_imp(dist);
+}
+
+template <class RealType, class Policy>
+inline RealType median(const mapairy_distribution<RealType, Policy>& dist)
+{
+    return detail::mapairy_median_imp(dist);
+}
+
+template <class RealType, class Policy>
+inline RealType skewness(const mapairy_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no skewness:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::skewness(mapairy<%1%>&)",
+        "The Map-Airy distribution does not have a skewness: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis(const mapairy_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis(mapairy<%1%>&)",
+        "The Map-Airy distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis_excess(const mapairy_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis excess:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis_excess(mapairy<%1%>&)",
+        "The Map-Airy distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType entropy(const mapairy_distribution<RealType, Policy>& dist)
+{
+    return detail::mapairy_entropy_imp(dist);
+}
+
+}} // namespaces
+
+
+#endif // BOOST_STATS_MAPAIRY_HPP
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
new file mode 100644
index 0000000000..8f5b98d587
--- /dev/null
+++ b/test/test_mapairy.cpp
@@ -0,0 +1,822 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_TEST_MODULE StatsMapAiryTest
+#include <boost/test/included/unit_test.hpp>
+#include <boost/multiprecision/cpp_bin_float.hpp>
+
+#include <boost/math/distributions/mapairy.hpp>
+using boost::math::mapairy_distribution;
+using boost::multiprecision::cpp_bin_float_quad;
+
+template<class RealType, int N>
+void do_test_mapairy_pdf(){
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    // Left tail of MapAiry distribution inherently limits accuracy due to the rapid decay of the function value.
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.48902525259161778456663373601227358266560067430936e-4524), tolerance * 10000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.35000261887613150163386664453709286782071190547944e-3558), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.59514743738055878289124765721120558977841779893312e-2741), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.23001358749520957481536587430803343649600724408224e-2059), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.91092696891623714443869745182216876382044809172723e-1501), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07670398427978297595825050147335321586451776148320e-1054), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.75337241594382145623417946757631570270349308241803e-869), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.98271669611043473474221732621841457710581601420544e-707), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.16498740545788718692214006589654128484512724342869e-566), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.49681712247552092430360122510975673204884714780707e-445), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55053727524864779623317373572781282350111182284876e-343), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19590456107919919197512531538035620765530980528894e-258), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.73694941159984922185033097915349420991674156548250e-188), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.81449463353684665334966063303815524281822160159818e-132), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.74974309038596237884318081144949974855326622002492e-109), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.29136035353058491211769990284207292488489027379633e-89), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01585226509378718416615473646349537501789989363229e-71), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37033445628502141399361852883285362383866808742814e-56), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34096664947790338152990789779350354526301978444227e-43), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68877771535989487461767283800177475346958322976577e-33), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.82006696453724258217996541433935771573414304428384e-24), tolerance * 10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54482240843563125964619012431713490038548382437138e-17), tolerance * 10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95446089249867191439127373027848930673014745742088e-14), tolerance * 10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.50933920988971071711086365057147867083089476835078e-12), tolerance * 10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.93525639583557913222186453754518161964863338679333e-10), tolerance * 10);
+
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.34369873917936310843493426518284206307542912325702e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77757355685380561185988935905104213909281485602180e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.67935873875498302175093073530783568485155988744416e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63150314678587224494834533488274597847689803128076e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.66981984951457236403520646020207894651500649740558e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04268591430185285447948956767040247962753669747157e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09373105986325625209096934627967360395341037677581e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.80640911685196781581446750934825559197579090806069e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.30714423198107251239523977966407204142168461729995e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.58842018103237928265884912263898874481595562824878e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34619157601942089113215976120224270739528013289579e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.75682912797714827638251175725141830254079472660215e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14483832832989822788477500521594411868042501441052e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31592413389237158115773602554741285666601187136132e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46510720433737601145589738058516645303764778406120e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.58858272589879457467907897007761708777068403816847e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.68368758744508533942159519264649183356982627934537e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.74896964572402100481706929301679979523752439534115e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78416838013401425639828509948809230256694219667844e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79011912859672711819203848701778087056321687064703e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76859868856746781256050397658493368372419755176282e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.74830251162716136956231178987638601629634664517919e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72213275423897601118140737012980725371274046892426e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69048759814952957802002736887143054018790117979041e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65378566438926186069214998647211849395648980215839e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.61245973171416933849635378258875498386938909727468e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56695079986621470612303095505427278554320952987612e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51770257100814033767420472605045312962380868746169e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46515640532722451246144916562599607636382596292905e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.40974679016952551097229293394786875981693451661862e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.35189734654776422654774161240658760813142609084491e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.29201738275575132039254286232840244115188891902544e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.23049899232453590038819913858072064402640465533782e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16771468279209758359211730425922824067563080471965e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.10401551277763824950435892543895916698505857289016e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03972970763820126963564357339894388732551496850922e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97516171847191855609649452292217911972760948598791e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.91059168530983397246791731314734572731339598377834e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.84627526286757244484016179988853282946752058004097e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78244376604908808362842960720569088074360938826161e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.71930459233559687354598878881397561629142415087483e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65704187907786028551352925788813828181432590627815e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.59581735536596915694662484173754591721771767208970e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53577135041201613422320904399972678346505180911383e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47702392309337834830220258805531647259773671641587e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41967608032785834866384133800904772318199442922830e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36381105516273814949846883397888219175600292125024e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30949561875080790965818583863955676147392613436720e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.25678140366749341891056123744605385205177726623077e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.20570621922063209990039201192595153753061823668443e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.15629534246005614282003528019134390685312636509026e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10856277146400733535248998121026984388464547942987e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06251243013238748252181151646220197947016365256337e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.75430585815861237530788049942964394941727146945119e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94921730852144630624722291210866171228958719672719e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.20763203888240939750507494683136041919542710442553e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.52664687715163418854003417614711690443203995990429e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.90290701026305425949257079944431253582616228954748e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.33278922127799799766017618158404889945497518669482e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.81254742548053622180113078981721846479230408163441e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33842514891989443409465171800884519330814876941244e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.51394330031190703409753192401513286012367671189008e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.83173172055121251708819783948372658040389943407125e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.26731989005960717430587605328985374107046652534330e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79973178629260510506067822703511722927370913396772e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.41138621807489585364575132430814179891782893106309e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.08776953835588218788258294328943072921113243548837e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.81702027546943420543987006667270192025143215867522e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58950538583133457383574346194006716984204842764692e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23449076237421124835496017947109115185689559096654e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.76628876438498186161275834549825153942245265285021e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.85705896089536983465980519032147649251164182381151e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.41725094843861993121315653435763289609915116903808e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.31264184292047732621870128909412110588268320306673e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.45166594303360764259552410935368398129332569193241e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.77078907451534652348813394683088320326083698637357e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22517551525042172427941302520759668293351400085609e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.41981613066309674421788083490352250077859372362907e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86815272152296425461960094149288322349331776254317e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47672748088907799783338276475559452864086595323508e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.19065885055336418361425251181752339740309873019493e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.76274498770011155322885494753359606185503116800378e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.12117840379514058437502004817680010914158504614072e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.84060120900265238260840046704576012273231257957218e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.82527663232857270992129793621400616909426228224712e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.34356222389517260476288187086191333487351565998487e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.33976274743353308671561884595553840397953308913098e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.63275420187782102031440426363742618331512228841827e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.11866107787483058586064754989935066085956111714438e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73477843721978250663679288968512001020601996296490e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44160680253022056601252575834792105383788377162879e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21335317476130403409545135558158224084771179668233e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03264853379349880038687006045193401398742550912390e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.69348218890827802115199892879428047102258557679491e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.91237960791142062915636488977731277854393252956156e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.65910753386639565315739798326227665091960854776722e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.74840664437921635017204117045344765826413564522111e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.06868586281732253998273705361085730421392207516563e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54975706173930172767473002839017573406030702226132e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14583740785288043496760695039190976938266337954109e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.82612140613373038344483207825545571090342007879025e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36036300551703042854867518460643847165588663407845e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04535842750631349697889823754314492592824987833936e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.23732650061248767465314076860143478427557447053122e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.62699739226146233957434830649961751777393343487704e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.42516447612776691413186917108911633335528994759200e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.50767100225890854218096000852153526257706640350006e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.79354212598752921854694346382153053933709178870365e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22829848834607910587947957072698363475405049514861e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.70691063363569289518344600523741530561019748614806e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.00884949274594535609095332297684714775260624951825e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78341094639115825398956813042728307580960455542744e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15265496830848341113806943808080759239756631409525e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.57315927453204720744811655603371636021315489208197e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.85204679078224624495444948682547526667095102524654e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74161227361870459284450362091832192677055853279409e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.07876462219180661771716253718191722284989080940137e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.44253835507444012610805302754717855328014016707006e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.62113944435292862305033337145279742309373660330666e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70079323596084060715031479698836179832962876226040e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00660607636030744539992938919621601865776189138704e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.31497886237763070924617652541844323609885629317601e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.39564398862596160919395415621974601387332621717152e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66093089449300961525223017779109302708950139673730e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93613874644561300698599726959494859627890174964948e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19040904529065504857204743126112225011195501281143e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.17543358264254064703206600829360293655988827362640e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62200282665332970268320245960144424095679956397013e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86732299457579395219850121616992176031753071031156e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.06875883329165532088522436776488158979648490753308e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.96038435804935610062036418083267399916819002834560e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58398713540364228777663367294171284220596445493878e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80012011189042378144386404030074611545380892760386e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.94995979813638214930198027960375045149298281432705e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54686243691761942165686883762842249372631955082800e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.83394511536756069267771511760113721074800848019252e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51060784855236271646178597425041551955920802058680e-29), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.72064952672613348894308116953255143520457854922274e-31), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47520297710191671529471286547892233784021035466379e-32), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.61000930344348973529597770462163230645079307893137e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44062790732609054227999303269426009576929146861433e-35), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.50196221039403294462497822716956279927920276478346e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40686319074813529519530569599048837477475167906008e-38), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.39644747108792279748533029997027617117109903686087e-40), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37388983471497587421416571874071130349096844921335e-41), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.29340573348429960691926787106472282340927640380120e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34168929171384362716227120970772588231539887618792e-44), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19277903660576133488209753033664338223562148808726e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31024344893930041715065547823020105694863171502727e-47), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.09451077793531380359579836946937830296447410946021e-49), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99854568157745488632402184518493974898874424751974e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90482976716548328742580258318841772362182055421850e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.81331031949754227287676033514493918322443413497900e-58), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72393585888431862585621126478997967111761145994043e-61), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.63665611219171740806270631327146452257579244134808e-64), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55142198456222403131123663405416457282792230600398e-67), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46818553179904690557737952544352009065226787695701e-70), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.38689993339750674372790969281593758852760534859083e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.30751946620850267942178680939056405129648959823324e-76), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22999947871924089787283868104547270634422812327464e-79), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15429636593675868932894402445846943978928527663539e-82), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08036754486011590754779689888522406229422390296425e-85), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00817143052745694096464540906760162333420303023853e-88), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93766741262446966891078653229257971028730764671731e-91), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86881583264108366104568997294197237332744887374738e-94), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80157796156355826273993161420114489582758679076892e-97), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_cdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    // Left tail of MapAiry distribution inherently limits accuracy due to the rapid decay of the function value.
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41267677661910675305382637108866964194971791718950e-4526), tolerance * 10000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.54257458395442655204313046627840914088415076161558e-3561), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.76526114681351440657658256501506814774341295354922e-2743), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.27125192542763584917976723724200097302881304411026e-2062), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63420353908123838151105660636393196705034472693701e-1504), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.73063520387773809387189485017024200015891995562535e-1057), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87621737485296751690587747650586494006422187478425e-871), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.15431208733487028595846723973676765010037279135068e-709), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.43691228284359420616981379531226120901046405612148e-568), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94968725712637201733674598027292284194096042437396e-447), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.29903053626343464859342616262182157628847143496274e-345), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.84047255379287327139957588241933355294847277196332e-260), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.79693358121995588307456046556605766916709047503732e-190), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.18430997009344263598977403572421080974427275299628e-134), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.48855014561480471542019201883561279219078606560987e-111), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21188569601559235190706821985880880180873775432009e-90), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.35130675597097791570481439579882762106711974084282e-73), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37868088180310978639226395953519655144561270921646e-58), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.96213643222050268066173675729245650285594216946076e-45), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54299664164424690506837069440249011982208536500223e-34), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55256887328573175640232009727759270424877561672436e-25), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.76658378173553845515260323095527685644595481193099e-18), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53962634794926085939153812168733146892427038438756e-15), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.86644224834640735242565183060109673582728544145215e-13), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03383983622833649608546095853620837892086215933298e-10), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.91537779419133030075704775849634109699414218730481e-9), tolerance * 10);
+
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.98085764775551392183308859729746156105641469279537e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.74005376900861403666100209810033834996576655180465e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38210242545410097936371084112947842536958832190953e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.20388922732913226923590659641162717163243937441333e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.01190141003747964176020229987886598385662366685178e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.81314867410709227363443913418400543623685087660036e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40335466769957406990026955582239481134043242080576e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65057217408705944017729221733489193253150025104939e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.62249422314997336809404422537950480283670862386341e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.49463093988108215731880519187728405325669137953076e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.13731490830425435301322069056843269169838775278008e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62598955251978523174755901843430986522046460911826e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90499210557846036762061906872202100639194335579553e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20405659651083834253744598353980626247223640040816e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.52019615753011340929652761968369152398962550184606e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85001847038770817549042011993996310385733185736928e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.18987376977895959785022298515900161162070947963445e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.53600587820316569763364664186012515534206385253539e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.88469588484092929432583134493879046529813482615104e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.23238998449671083670041452413316011919930693856385e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.40482473418234444080637631800355214131813723348029e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.57580541347059341976751497432836530189703719631253e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74497724348320019407539810613151808302214091800752e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.91201100390145330029548239186193815674350921221373e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.07660411254690680532566892253363954450731338298810e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.23848132271235424597841060643701240046967758423031e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.39739506217816326324441201522899717272689507530078e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.55312544188864070398568309403385234827691551635647e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.70547996523808722092270387778468756135745550977842e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.85429297088468989836573146625524898390641430572229e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.99942484305170440309173928292359597658678248461166e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14076102348433999265595009037280955266566735857487e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.27821085871238004955876961091597273535850920355153e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.41170631513311055182782737833523982566081113132113e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.54120059278782917662600347641177702821526512639253e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.66666666666666666666666666666666666666666666666667e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.78809578204369927830516637473281842472755486735670e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.90549592781258492544813432997757039278246435622280e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.01889030914802776673544656107973638254340107333208e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.12831583813566709661955692651725308671816974125125e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.23382165835700226601867127791408227947098667962247e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.33546771684027578538449554398877013955180783305967e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43332339433579641844979454704458465657719551526672e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.52746620257793576893322261719616438461321552900402e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.61798055507971738758762860873629690865112979477773e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.70495661608502783177600997939957544744070827966369e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.78848923058628458126731690124829998626066330325893e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86867693680400430433267457602884639416039914905443e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.94562106121611865967124973894234486976489176337189e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.01942489511196041360944230423166502583801465481058e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.09019295071828335416784977458008517243666113680032e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.15803029418984060112492565010063896412665755747313e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.28533238809939722865056318522346970220432633092471e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40216194581500702945839843944471675879234503695234e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.50932751104023843947651194694738668613497033313653e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.60760530927220029947644215642926175488027901722942e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.69773224168421631436187338078646751800825779589535e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.78040142637134263427912246171411479166776409276684e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85625978983111842670865940159150361843054620140300e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.92590726602475875901684499549667744162908005254207e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.04873777288161758991649770533103505875566036067315e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.15278911856248478088063341213669352039898456875983e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.24130503839415290663064766600863877055306793445333e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.31696102735179394495180164200593784488582138327694e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.38195112746199551037885830108115610693678956104594e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.43806900885896605694390358343940460845582243989715e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.48677954836791634391273767979450406335892640585045e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.52927980046477119746205391036666872656611789316554e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.59939373386293535847669182576818465955927373035467e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.65433945362867879413538593557411941750837354200812e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.69816672594606569822299986511094581346810669802925e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73368884642273321841166642302379087929797275815602e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.76289558464640301369422872101450331194067414657857e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.78721979671508698647720200666528542996105699216801e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.80771139145909061814002155447578879059651577452407e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.82515243555548699954994382507757214540918643206410e-1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_ccdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.37401044748021476825244098156569013477953539088174e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.09500789442153963237938093127797899360805664420447e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.79594340348916165746255401646019373752776359959184e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.47980384246988659070347238031630847601037449815394e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.14998152961229182450957988006003689614266814263072e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.81012623022104040214977701484099838837929052036555e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.46399412179683430236635335813987484465793614746461e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.11530411515907070567416865506120953470186517384896e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.76761001550328916329958547586683988080069306143615e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.59517526581765555919362368199644785868186276651971e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.42419458652940658023248502567163469810296280368747e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25502275651679980592460189386848191697785908199248e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.08798899609854669970451760813806184325649078778627e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.92339588745309319467433107746636045549268661701190e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.76151867728764575402158939356298759953032241576969e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.60260493782183673675558798477100282727310492469922e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.44687455811135929601431690596614765172308448364353e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.29452003476191277907729612221531243864254449022158e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.14570702911531010163426853374475101609358569427771e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00057515694829559690826071707640402341321751538834e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.85923897651566000734404990962719044733433264142513e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72178914128761995044123038908402726464149079644847e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.58829368486688944817217262166476017433918886867887e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.45879940721217082337399652358822297178473487360747e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.33333333333333333333333333333333333333333333333333e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.21190421795630072169483362526718157527244513264330e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.09450407218741507455186567002242960721753564377720e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98110969085197223326455343892026361745659892666792e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.87168416186433290338044307348274691328183025874875e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76617834164299773398132872208591772052901332037754e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66453228315972421461550445601122986044819216694033e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56667660566420358155020545295541534342280448473328e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.47253379742206423106677738280383561538678447099598e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.38201944492028261241237139126370309134887020522227e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.29504338391497216822399002060042455255929172033631e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21151076941371541873268309875170001373933669674107e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.13132306319599569566732542397115360583960085094557e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05437893878388134032875026105765513023510823662811e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.98057510488803958639055769576833497416198534518943e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90980704928171664583215022541991482756333886319968e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.84196970581015939887507434989936103587334244252687e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.71466761190060277134943681477653029779567366907529e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.59783805418499297054160156055528324120765496304766e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49067248895976156052348805305261331386502966686347e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39239469072779970052355784357073824511972098277058e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30226775831578368563812661921353248199174220410465e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21959857362865736572087753828588520833223590723316e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.14374021016888157329134059840849638156945379859700e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07409273397524124098315500450332255837091994745793e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51262227118382410083502294668964941244339639326852e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.47210881437515219119366587863306479601015431240172e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.58694961605847093369352333991361229446932065546671e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.83038972648206055048198357994062155114178616723061e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.18048872538004489621141698918843893063210438954059e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.61930991141033943056096416560595391544177560102847e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.13220451632083656087262320205495936641073594149555e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.70720199535228802537946089633331273433882106834460e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00606266137064641523308174231815340440726269645335e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.45660546371321205864614064425880582491626457991880e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.01833274053934301777000134889054186531893301970748e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66311153577266781588333576976209120702027241843979e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37104415353596986305771278985496688059325853421426e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.12780203284913013522797993334714570038943007831995e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92288608540909381859978445524211209403484225475927e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74847564444513000450056174922427854590813567935902e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46888494885704354461170804278826523218710845325600e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.25613324230091750631240813030902908673461241410450e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08995384276796746727925033729177141093311272472945e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.57298412261448730944183018356841954457807894385431e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.49445667426015051170301411155410826055184233951431e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60377136717752997401167765152949642869947243569953e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.85823720627621671017207210698248665551570440429385e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.22684103170563193014558918295924551172698239430713e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.22006950358287273393523413555812293504310335665744e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.45787594574479193246071067008198432980227781543963e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.86454025983790677529906306805195677315975322722262e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.39200041143645646258373331865031120883657317932172e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00844464598329521611240330284790908003180945122524e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69207105975977872414400493979073211647180301757125e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42749222811426799055113000065152671289607878504149e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20357145727036120652264700679701054983338793783565e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.84678186992189202260619598427428218285343162114238e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57685005349633837416913019835892196933717853056275e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36681189477727165566612776659042216546642387956225e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.19958501309529382285703116836639459985687034231775e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06387729083711703707125561075502300925516821745411e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51956726422504037060971384488455660747488001979504e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.58369730588727742464054792329377206933983130862391e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.79171138168694768852946218859426934990849762414603e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.52989549449674176739274234303186543768254475184699e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.57534022322054445175812334907544905864245720421642e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.83262692804541386527340439387556377914021496108680e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.24132027619974492546489695559384126869565934766815e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.76147662885863808608468523190827912794216909524203e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36574864341415676513997111497521230889735520043816e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03484906797876224319052497399923183994442800112441e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75482620393356950171417803995157642981745916059418e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73979922776430555363554632966080889507162029820752e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44353982639936003430898773389958569528340214901924e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21747521599099094720054911524728128905331418743558e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.30442492111514986227593224497576120783344940470632e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184402609265962838062304205455964936542503385355e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.38053115409151479601077504716814204054241984396579e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230503273504174320645323659877052404533613091567e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.72566394266708055503723315148592640827491725732841e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788129092113064009710124961268854372530077851514e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40707992833487973793766069223107728401530584918012e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235161365145877787702193738699569533619914113956e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05088499104186197709404571098840228587836479911802e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951706432436058369237052221627684485231071286e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31360623880232751062247585210413319083311528997997e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64429939633040546807800247387131067206560952703714e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64200779850290938904479244625064763530742033320990e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424541300683543633877614223483555123688801843e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05250974812863673632096512092113144155816177586613e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.25671780676625854430204135462707277286762193086669e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56563718516079592040149887308711394838177046916383e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845782318037768094883949095101477347530653e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.20704648145099490050187930370138656919662848438144e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.13386215730722789754721037105719349775366357126605e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00880810181374362562734924119592255004499293746830e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403487193401296875220001924045479390391e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77165962079254358991751621103655291754760707304047e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067948739689526379757206282312287607911e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76821815748834935924611907974700181516735308796565e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669905764884968375298647166107661462e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.32534087107554587382206106210469124710349176992174e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.40667608884443234227757632763086405915307399803018e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.75834511105554042784697040953858007394668838202264e-22), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44793138881942553480871301192322509243346488933465e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05599142360242819185108912649040313655418331509614e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31998927950303523981386140811300392069272914785317e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64998659937879404976732676014125490086591143489426e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06248324922349256220915845017656862608238929361934e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.57810406152936570276144806272071078260298661702420e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22263007691170712845181007840088847825373327128025e-28), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.02828759613963391056476259800111059781716658910032e-29), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.03535949517454238820595324750138824727145823637540e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86774921121022248157180194922091913636165349433656e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22933581425159726274559405456576861505650835849009e-33), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92083720976812072303999071025901346102579431014076e-35), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00130814026268862974998548477970853285280360959494e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.68954396916045098398435231996829458258250563999209e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.32741245181320466247555049995046028528516506248764e-41), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.14490819559581322851180476561725941957580704101369e-42), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78891905561845816954969494627696784308719850158390e-44), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79518602440384088992139835355776225482374765872484e-46), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.36747816313100139050218492743400352316210571675756e-48), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.82418462989218967265966394911563050494079018243369e-50), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06627884842065463635307249204931726639699846600526e-51), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66606070065727286930167576882705822874531010313323e-53), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.60321984477698885828386838879227848241454703614566e-55), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.06753100746404509106854435748793512877272974397760e-57), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.35551719916257045479460055857489863870739022496500e-59), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 600))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.71969536983273370677446521953393512020163902133418e-272), tolerance);
+
+    // The test is terminated because x is inf after this in fp64.
+    if (N <= 53) {
+        return;
+    }
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 10000))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41571262853590848961675783559267306723234880166889e-4516), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_quantile_nearzero() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.92947985498880164288717582971263069265106409267331e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.59822399410385083283727681965013516508738702183587e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.37051518906738394785544825118798831695789651589080e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.18765177572396470161180571018467021827812222940306e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.02990438632621036358966845969387883330987649629695e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.88799753980914934718534117636680696659950540760708e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.75672646260182080486757173789442594487758358719568e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.63281240925531315038207673147576301428806562043208e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.51400400121400801502802449510679455584862826208973e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.39864166928988824635332108295073034590821798923232e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.28542241490194660184907680173328998444992309715534e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.17326074020471664204142312429732771994689840460362e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.06119903663447640834652691309939508582577539512003e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.48344198262277235851026749871350785648904607023049e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.33817641975610807828267883212039917352738594297812e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.16710685455022053317001962780672309444401429230030e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.96039220307812911673187933977720502663701213461352e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.70691924008504753346480857177819427470334982130948e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.39365150798529936746993802101957358628812489096556e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.00474815142578902619056852805926625285378475306847e-1), tolerance);
+
+    // Relative error decreases near the root.
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.20300033010874226241969971846939668616524880409485e-2), tolerance * 4);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08557609474704600193050942980969400222443967430903e-1), tolerance * 4);
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.84775355628419671941908878470333245751721020657513e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.81512108276093787175849069715334396559730936013748e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.05946829281923976565971908177998486051088750363345e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.69237131791870252926200620656937624841227431099908e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.29003620591891062966640208281844476036608475704263e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70276979914029738186601698003670175695927342267323e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.28080064428173146950050714257245479404308412291534e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22141517097499177560650456638736418866609207598601e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.36798741582712685566660459972731625067678977232527e0), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_quantile_lower() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.18765177572396470161180571018467021827812222940306e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.59822399410385083283727681965013516508738702183587e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.92947985498880164288717582971263069265106409267331e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.20998806047945704828514962310033638603842757237089e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.45496901537018787335070643452598202244805633093375e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.67354365380697578246790709817724830651682057476917e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.05331626220443158014611601879873776289585727270317e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.37844135506419820279451552495734835192576864639213e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.66475100891248273292011043832615771689316788780040e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -16)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.92187819510636694694450607724165688786106650410224e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -20)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.37198340489560108355199818136414022326129982959773e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -24)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.76028477470580699278679082649703786389435657070830e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -28)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.10419378761193307962534180728809528372838135595700e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -32)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.41443550638291131009585191506467027832121974024563e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -40)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.96026448032205844753104387192915744062974794241787e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -48)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.43355682497258196703130282301265363831865507562392e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -56)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.85432398223245647091315413807705550499215849013310e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -64)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.23500806363233607692361021471929015767129541901722e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -80)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.90695141954692987290075695228754376250679911499016e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -96)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.49149767947731938416802231743764792842977181401152e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -112)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.00124089585489463242206889945762289007601620222216e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -128)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.04845570631944023525776899386112795192930377369709e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -160)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.13196240444608571220864964743861585994042496495014e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.20475312075429969521072327133506584708675011147301e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -224)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.26971371983788322297191645356972895828456120573844e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.32865827226175697711590794217590458317537880046696e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.32865827226175697711590794217590458317537880046696e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -320)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.43303723297942256778502134022428247271630018451935e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -384)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.52413050129859916220402440029315858653640179700446e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -448)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.60549473918897820617071548963372947780704796096977e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -512)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.67937186583822375017526293948703697021001956377209e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -640)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.81028650954862232126230250634527453300745376729470e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -768)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.92461760606525027716536281516018610241283237089375e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -896)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.02678879167343824140492421290271637384390204302948e1), tolerance);
+
+    // The test is terminated because p = 0 after this in fp64.
+    if(N <= 53){
+        return;
+    }
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.11959316095291435774375635827672516757012476284109e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1280)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.28411538998117558460421271505353342631141242515516e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1536)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.42785430825019465839030492595482468932343681278349e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1792)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.55634220352411216642587067287258912926964865154135e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.67307564006689676593687414536012112442665935238575e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -2560)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.88006705102088142572333576380332410442882971872985e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3072)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.06095108081567569614908765234696115918183394966145e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3584)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.22266885559263332213569359568928269416384800428618e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.36960987939726803544369406181770745085696438921663e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5120)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.63019918860979732881015320942243118103538614206846e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6144)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.85794964449030059786959849735574335608745736630897e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7168)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.06158611834421484993920289979452825015061756369038e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.24662793339079714510108682543625432044226557042768e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10240)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.57480988422877882295975852850886697641784458384426e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12288)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.86165509604814747106458415059041118242367113233764e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14336)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.11814205550106893579346476384206383922751551334008e1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_quantile_upper() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.16710685455022053317001962780672309444401429230030e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.46875))), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.96039220307812911673187933977720502663701213461352e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.70691924008504753346480857177819427470334982130948e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.40625))), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.39365150798529936746993802101957358628812489096556e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.00474815142578902619056852805926625285378475306847e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.34375))), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.20300033010874226241969971846939668616524880409485e-2), tolerance * 4);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08557609474704600193050942980969400222443967430903e-1), tolerance * 4);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.28125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.84775355628419671941908878470333245751721020657513e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.81512108276093787175849069715334396559730936013748e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.21875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.05946829281923976565971908177998486051088750363345e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.69237131791870252926200620656937624841227431099908e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.15625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.29003620591891062966640208281844476036608475704263e0), tolerance);
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70276979914029738186601698003670175695927342267323e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22141517097499177560650456638736418866609207598601e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.36798741582712685566660459972731625067678977232527e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.63240190107315016002742117235901647573374032928275e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37487073802383509843362175744776155324007021797019e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18429841828919685808654152263914024115105410242857e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.50552947051871870287466561935025391775332522082960e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38732922416208535732704088926085913683321415168727e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.49585416520688234273370911116680490544653394894587e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.80900106401310352569173769396359734191276945763559e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.59336704609415555521333325344685782416363311947039e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55156669326461321628671444544286440554399508021258e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25510428200953290831680861672648808196801287129080e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43190196382396984755739962193081183260874381700500e6), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.77306696194440571351895040208958865072901805506645e7), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32755474809804845725014907927003674268598932505496e9), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.38411271011676880227484089908793278086771148389202e10), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.78343716417988572841183668816998971166780683532365e12), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14997210570212560225883973162628933329443239976683e15), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.99677152273063632531264438890163357898418349270434e18), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62497388866235918645459765949830559011448320623360e22), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.64139290653028845793860203742403295803332310962125e25), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.97920970865877789202766313638336627695568626671453e31), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.84407885843159775798215826490261804734522750775796e38), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87250989448760462117787200600339872607929758715096e44), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28743695332377477386366453958993754420344828061498e51), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28743695332377477386366453958993754420344828061498e51), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -320))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.98819430202303731872899900564216427734599065613620e63), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.27507518735966284635753747136817320622994832637767e76), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -448))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38092093738495853701408205401696240265896114717023e89), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.05852403143769157513875467957386926795647775801563e102), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -640))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49075014586685014041688089060587827415714205982384e128), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.26604066065618724776472365999448082037897284653223e153), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -896))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54152887582709267575372250070675971504362522185818e179), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_mapairy_locscale_param() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    mapairy_distribution<RealType> dist_0_1(static_cast<RealType>(0), static_cast<RealType>(1));
+    mapairy_distribution<RealType> dist_1_3(static_cast<RealType>(1), static_cast<RealType>(3));
+    mapairy_distribution<RealType> dist_0_invcbrt18(static_cast<RealType>(0), 1 / cbrt(static_cast<RealType>(18)));
+
+    BOOST_CHECK_CLOSE(entropy(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.0072768184106563460003025875575283708), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_1_3), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.0072768184106563460003025875575283708) + log(static_cast<RealType>(3)), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_0_invcbrt18), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.0438195657786014485977283891231190450), tolerance);
+
+    BOOST_CHECK_CLOSE(median(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.71671068545502205331700196278067230944440), tolerance);
+    BOOST_CHECK_CLOSE(
+        median(dist_1_3),
+        (1 + 3 * BOOST_MATH_BIG_CONSTANT(RealType, N, -0.71671068545502205331700196278067230944440)),
+        tolerance
+    );
+    BOOST_CHECK_CLOSE(median(dist_0_invcbrt18), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.27347630981017495237228835747364595601553), tolerance);
+
+    BOOST_CHECK_CLOSE(mode(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.1615872711359706852500000803029112987), tolerance);
+    BOOST_CHECK_CLOSE(
+        mode(dist_1_3),
+        (1 + 3 * BOOST_MATH_BIG_CONSTANT(RealType, N, -1.1615872711359706852500000803029112987)),
+        tolerance
+    );
+    BOOST_CHECK_CLOSE(mode(dist_0_invcbrt18), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.4432284977460014720866292801600737435), tolerance);
+
+    BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06251243013238748252181151646220197947016365256337e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97516171847191855609649452292217911972760948598791e-1) / 3, tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_0_invcbrt18, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.29264884227495575949271548513687010027396013858107e-2), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.15803029418984060112492565010063896412665755747313e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.66666666666666666666666666666666666666666666666667e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_invcbrt18, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.19730152884211135907661924151362266458717453254074e-1), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_invcbrt18, quantile(dist_0_invcbrt18, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_invcbrt18, quantile(dist_0_invcbrt18, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_pdf_fp64)
+{
+    do_test_mapairy_pdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_pdf_fp128)
+{
+    do_test_mapairy_pdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
+{
+    do_test_mapairy_cdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_cdf_fp128)
+{
+    do_test_mapairy_cdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
+{
+    do_test_mapairy_ccdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp128)
+{
+    do_test_mapairy_ccdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
+{
+    do_test_mapairy_quantile_nearzero<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp128)
+{
+    do_test_mapairy_quantile_nearzero<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
+{
+    do_test_mapairy_quantile_lower<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp128)
+{
+    do_test_mapairy_quantile_lower<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
+{
+    do_test_mapairy_quantile_upper<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp128)
+{
+    do_test_mapairy_quantile_upper<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
+{
+    do_test_mapairy_locscale_param<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(mapairy_locscale_fp128)
+{
+    do_test_mapairy_locscale_param<cpp_bin_float_quad, 113>();
+}

From 7103a2694d23291c2499823eccc6817f251311fc Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 14:40:31 +0900
Subject: [PATCH 002/399] Add holtsmark distribution

---
 .../boost/math/distributions/holtsmark.hpp    | 2465 +++++++++++++++++
 test/test_holtsmark.cpp                       |  795 ++++++
 2 files changed, 3260 insertions(+)
 create mode 100644 include/boost/math/distributions/holtsmark.hpp
 create mode 100644 test/test_holtsmark.cpp

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
new file mode 100644
index 0000000000..5e759cb3e3
--- /dev/null
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -0,0 +1,2465 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_STATS_HOLTSMARK_HPP
+#define BOOST_STATS_HOLTSMARK_HPP
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable : 4127) // conditional expression is constant
+#endif
+
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/distributions/complement.hpp>
+#include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <utility>
+#include <cmath>
+
+namespace boost { namespace math {
+template <class RealType, class Policy>
+class holtsmark_distribution;
+
+namespace detail {
+
+template <class RealType>
+inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 4.7894e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(2.87352751452164445024e-1),
+            static_cast<RealType>(1.18577398160636011811e-3),
+            static_cast<RealType>(-2.16526599226820153260e-2),
+            static_cast<RealType>(2.06462093371223113592e-3),
+            static_cast<RealType>(2.43382128013710116747e-3),
+            static_cast<RealType>(-2.15930711444603559520e-4),
+            static_cast<RealType>(-1.04197836740809694657e-4),
+            static_cast<RealType>(1.74679078247026597959e-5),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.12654472808214997252e-3),
+            static_cast<RealType>(2.93891863033354755743e-1),
+            static_cast<RealType>(8.70867222155141724171e-3),
+            static_cast<RealType>(3.15027515421842640745e-2),
+            static_cast<RealType>(2.11141832312672190669e-3),
+            static_cast<RealType>(1.23545521355569424975e-3),
+            static_cast<RealType>(1.58181113865348637475e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.0925e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(2.02038159607840130389e-1),
+            static_cast<RealType>(-1.20368541260123112191e-2),
+            static_cast<RealType>(-3.19235497414059987151e-3),
+            static_cast<RealType>(8.88546222140257289852e-3),
+            static_cast<RealType>(-5.37287599824602316660e-4),
+            static_cast<RealType>(-2.39059149972922243276e-4),
+            static_cast<RealType>(9.19551014849109417931e-5),
+            static_cast<RealType>(-8.45210544648986348854e-6),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.11634701234079515138e-1),
+            static_cast<RealType>(4.39922162828115412952e-1),
+            static_cast<RealType>(1.73609068791154078128e-1),
+            static_cast<RealType>(6.15831808473403962054e-2),
+            static_cast<RealType>(1.64364949550314788638e-2),
+            static_cast<RealType>(2.94399615562137394932e-3),
+            static_cast<RealType>(4.99662797033514776061e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.4499e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(8.45396231261375200568e-2),
+            static_cast<RealType>(-9.15509628797205847643e-3),
+            static_cast<RealType>(1.82052933284907579374e-2),
+            static_cast<RealType>(-2.44157914076021125182e-4),
+            static_cast<RealType>(8.40871885414177705035e-4),
+            static_cast<RealType>(7.26592615882060553326e-5),
+            static_cast<RealType>(-1.87768359214600016641e-6),
+            static_cast<RealType>(1.65716961206268668529e-6),
+            static_cast<RealType>(-1.73979640146948858436e-7),
+            static_cast<RealType>(7.24351142163396584236e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.88099527896838765666e-1),
+            static_cast<RealType>(6.53896948546877341992e-1),
+            static_cast<RealType>(2.96296982585381844864e-1),
+            static_cast<RealType>(1.14107585229341489833e-1),
+            static_cast<RealType>(3.08914671331207488189e-2),
+            static_cast<RealType>(7.03139384769200902107e-3),
+            static_cast<RealType>(1.01201814277918577790e-3),
+            static_cast<RealType>(1.12200113270398674535e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5259e-17
+        static const RealType P[11] = {
+            static_cast<RealType>(1.36729417918039395222e-2),
+            static_cast<RealType>(1.19749117683408419115e-2),
+            static_cast<RealType>(6.26780921592414207398e-3),
+            static_cast<RealType>(1.84846137440857608948e-3),
+            static_cast<RealType>(3.39307829797262466829e-4),
+            static_cast<RealType>(2.73606960463362090866e-5),
+            static_cast<RealType>(-1.14419838471713498717e-7),
+            static_cast<RealType>(1.64552336875610576993e-8),
+            static_cast<RealType>(-7.95501797873739398143e-10),
+            static_cast<RealType>(2.55422885338760255125e-11),
+            static_cast<RealType>(-4.12196487201928768038e-13),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.61334003864149486454e0),
+            static_cast<RealType>(1.28348868912975898501e0),
+            static_cast<RealType>(6.36594545291321210154e-1),
+            static_cast<RealType>(2.11478937436277242988e-1),
+            static_cast<RealType>(4.71550897200311391579e-2),
+            static_cast<RealType>(6.64679677197059316835e-3),
+            static_cast<RealType>(4.93706832858615742810e-4),
+            static_cast<RealType>(9.26919465059204396228e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.5084e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.90649774685568282390e-3),
+            static_cast<RealType>(7.43708409389806210196e-4),
+            static_cast<RealType>(9.53777347766128955847e-5),
+            static_cast<RealType>(3.79800193823252979170e-6),
+            static_cast<RealType>(2.84836656088572745575e-8),
+            static_cast<RealType>(-1.22715411241721187620e-10),
+            static_cast<RealType>(8.56789906419220801109e-13),
+            static_cast<RealType>(-4.17784858891714869163e-15),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.29383849235788831455e-1),
+            static_cast<RealType>(2.16287201867831015266e-1),
+            static_cast<RealType>(3.28789040872705709070e-2),
+            static_cast<RealType>(2.64660789801664804789e-3),
+            static_cast<RealType>(1.03662724048874906931e-4),
+            static_cast<RealType>(1.47658125632566407978e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.4660e-19
+        static const RealType P[9] = {
+            static_cast<RealType>(3.07231582988207590928e-4),
+            static_cast<RealType>(5.16108848485823513911e-5),
+            static_cast<RealType>(3.05776014220862257678e-6),
+            static_cast<RealType>(7.64787444325088143218e-8),
+            static_cast<RealType>(7.40426355029090813961e-10),
+            static_cast<RealType>(1.57451122102115077046e-12),
+            static_cast<RealType>(-2.14505675750572782093e-15),
+            static_cast<RealType>(5.11204601013038698192e-18),
+            static_cast<RealType>(-9.00826023095223871551e-21),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.28966789835486457746e-1),
+            static_cast<RealType>(4.46981634258601621625e-2),
+            static_cast<RealType>(3.22521297380474263906e-3),
+            static_cast<RealType>(1.31985203433890010111e-4),
+            static_cast<RealType>(3.01507121087942156530e-6),
+            static_cast<RealType>(3.47777238523841835495e-8),
+            static_cast<RealType>(1.50780503777979189972e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.2292e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(5.25741312407933720817e-5),
+            static_cast<RealType>(2.34425802342454046697e-6),
+            static_cast<RealType>(3.30042747965497652847e-8),
+            static_cast<RealType>(1.58564820095683252738e-10),
+            static_cast<RealType>(1.54070758384735212486e-13),
+            static_cast<RealType>(-8.89232435250437247197e-17),
+            static_cast<RealType>(8.14099948000080417199e-20),
+            static_cast<RealType>(-4.61828164399178360925e-23),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.23544974283127158019e-1),
+            static_cast<RealType>(6.01210465184576626802e-3),
+            static_cast<RealType>(1.45390926665383063500e-4),
+            static_cast<RealType>(1.80594709695117864840e-6),
+            static_cast<RealType>(1.06088985542982155880e-8),
+            static_cast<RealType>(2.20287881724613104903e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x * x * x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.3004e-17
+        static const RealType P[4] = {
+            static_cast<RealType>(2.99206710301074508455e-1),
+            static_cast<RealType>(-8.62469397757826072306e-1),
+            static_cast<RealType>(1.74661995423629075890e-1),
+            static_cast<RealType>(8.75909164947413479137e-1),
+        };
+        static const RealType Q[3] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(-6.07405848111002255020e0),
+            static_cast<RealType>(1.34068401972703571636e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 4.5215e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87352751452164445024482162286994868262e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07622509000285763173795736744991173600e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75004930885780661923539070646503039258e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.72358602484766333657370198137154157310e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80082654994455046054228833198744292689e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53887200727615005180492399966262970151e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07684195532179300820096260852073763880e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.39151986881253768780523679256708455051e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31700721746247708002568205696938014069e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.52538425285394123789751606057231671946e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.13997198703138372752313576244312091598e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74788965317036115104204201740144738267e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.18994723428163008965406453309272880204e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.49208308902369087634036371223527932419e-11),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07053963271862256947338846403373278592e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30146528469038357598785392812229655811e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.22168809220570888957518451361426420755e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.30911708477464424748895247790513118077e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.32037605861909345291211474811347056388e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.37380742268959889784160508321242249326e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.17777859396994816599172003124202701362e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.69357597449425742856874347560067711953e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.22061268498705703002731594804187464212e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.03685918248668999775572498175163352453e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42037705933347925911510259098903765388e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.13651251802353350402740200231061151003e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.15390928968620849348804301589542546367e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.96186359077726620124148756657971390386e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.3996e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02038159607840130388931544845552929992e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85240836242909590376775233472494840074e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92928437142375928121954427888812334305e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56075992368354834619445578502239925632e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85410663490566091471288623735720924369e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09160661432404033681463938555133581443e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60290555290385646856693819798655258098e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24420942563054709904053017769325945705e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06370233020823161157791461691510091864e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.51562554221298564845071290898761434388e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.77361020844998296791409508640756247324e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10768937536097342883548728871352580308e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.97810512763454658214572490850146305033e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77430867682132459087084564268263825239e-11),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30030169049261634787262795838348954434e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45935676273909940847479638179887855033e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14724239378269259016679286177700667008e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21580123796578745240828564510740594111e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70287348745451818082884807214512422940e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46859813604124308580987785473592196488e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49627445316021031361394030382456867983e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05157712406194406440213776605199788051e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91541875103990251411297099611180353187e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47960462287955806798879139599079388744e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.80126815763067695392857052825785263211e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04569118116204820761181992270024358122e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63024381269503801668229632579505279520e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00967434338725770754103109040982001783e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.6834e-35
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45396231261375200568114750897618690566e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.83107635287140466760500899510899613385e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71690205829238281191309321676655995475e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95995611963950467634398178757261552497e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52444689050426648467863527289016233648e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.40423239472181137610649503303203209123e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72181273738390251101985797318639680476e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.11423032981781501087311583401963332916e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37255768388351332508195641748235373885e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25140171472943043666747084376053803301e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98925617316135247540832898350427842870e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27532592227329144332335468302536835334e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25846339430429852334026937219420930290e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17852693845678292024334670662803641322e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60008761860786244203651832067697976835e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85474213475378978699789357283744252832e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05561259222780127064607109581719435800e-15),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08902510590064634965634560548380735284e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.60127698266075086782895988567899172787e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.73299227011247478433171171063045855612e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94019328695445269130845646745771017029e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21478511930928822349285105322914093227e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42888485420705779382804725954524839381e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36839484685440714657854206969200824442e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77082068469251728028552451884848161629e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.92625563541021144576900067220082880950e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88302521658522279293312672887766072876e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37703703342287521257351386589629343948e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32454189932655869016489443530062686013e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.81822848072558151338694737514507945151e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40176559099032106726456059226930240477e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.55722115663529425797132143276461872035e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18236697046568703899375072798708359035e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6207e-35
+        static const RealType P[20] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36729417918039395222067998266923903488e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05780369334958736210688756060527042344e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88449456199223796440901487003885388570e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20213624124017393492512893302682417041e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95009975955570002297453163471062373746e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35668345583965001606910217518443864382e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.69006847702829685253055277085000792826e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08366922884479491780654020783735539561e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.71834368599657597252633517017213868956e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88269472722301903965736220481240654265e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37797139843759131750966129487745639531e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72390971590654495025982276782257590019e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68354503497961090303189233611418754374e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20749461042713568368181066233478264894e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.71167265100639100355339812752823628805e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37497033071709741762372104386727560387e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08992504249040731356693038222581843266e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.03311745412603363076896897060158476094e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89266184062176002518506060373755160893e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.22157263424086267338486564980223658130e-22),
+        };
+        static const RealType Q[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24254809760594824834854946949546737102e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66740386908805016172202899592418717176e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17175023341071972435947261868288366592e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33939409711833786730168591434519989589e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.58859674176126567295417811572162232222e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66346764121676348703738437519493817401e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.00687534341032230207422557716131339293e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57352381181825892637055619366793541271e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23955067096868711061473058513398543786e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28279376429637301814743591831507047825e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22380760186302431267562571014519501842e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21421839279245792393425090284615681867e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.80151544531415207189620615654737831345e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.57177992740786529976179511261318869505e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54223623314672019530719165336863142227e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26447311109866547647645308621478963788e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76514314007336173875469200193103772775e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.63785420481380041892410849615596985103e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.8882e-35
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90649774685568282389553481307707005425e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70151946710788532273869130544473159961e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76188245008605985768921328976193346788e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.94997481586873355765607596415761713534e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83556339450065349619118429405554762845e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.39766178753196196595432796889473826698e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48835240264191055418415753552383932859e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23205178959384483669515397903609703992e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80665018951397281836428650435128239368e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27113208299726105096854812628329439191e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75272882929773945317046764560516449105e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.73174017370926101455204470047842394787e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.55548825213165929101134655786361059720e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.79786015549170518239230891794588988732e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73060731998834750292816218696923192789e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62842837946576938669447109511449827857e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33878078951302606409419167741041897986e-26),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75629880937514507004822969528240262723e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43883005193126748135739157335919076027e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26826935326347315479579835343751624245e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52263130214924169696993839078084050641e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34708681216662922818631865761136370252e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19079618273418070513605131981401070622e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68812668867590621701228940772852924670e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81323523265546812020317698573638573275e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46655191174052062382710487986225631851e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.79864553144116347379916608661549264281e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81866770335021233700248077520029108331e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15408288688082935176022095799735538723e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29421875915133979067465908221270435168e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74564282803894180881025348633912184161e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69782249847887916810010605635064672269e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85875986197737611300062229945990879767e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.7988e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07231582988207590928480356376941073734e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35574911514921623999866392865480652576e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60219401814297026945664630716309317015e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84927222345566515103807882976184811760e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96327408363203008584583124982694689234e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86684048703029160378252571846517319101e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65469175974819997602752600929172261626e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.21842057555380199566706533446991680612e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.53555106309423641769303386628162522042e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.92686543698369260585325449306538016446e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01838615452860702770059987567879856504e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65492535746962514730615062374864701860e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53395563720606494853374354984531107080e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.99957357701259203151690416786669242677e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46357124817620384236108395837490629563e-31),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02259092175256156108200465685980768901e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63438230616954606028022008517920766366e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63880061357592661176130881772975919418e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81911305852397235014131637306820512975e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09690724408294608306577482852270088377e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11275552068434583356476295833517496456e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.24681861037105338446379750828324925566e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16034379416965004687140768474445096709e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23234481703249409689976894391287818596e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93297387560911081670605071704642179017e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50338428974314371000017727660753886621e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27897854868353937080739431205940604582e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37798740524930029176790562876868493344e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29920082153439260734550295626576101192e-22),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.9688e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25741312407933720816582583160953651639e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04434146174674791036848306058526901384e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.68959516304795838166182070164492846877e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78859935261158263390023581309925613858e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.21854067989018450973827853792407054510e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20573856697340412957421887367218135538e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30843538021351383101589538141878424462e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.05991458689384045976214216819611949900e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82253708752556965233757129893944884411e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.97645331663303764054986066027964294209e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69353366461654917577775981574517182648e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59050144462227302681332505386238071973e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.85165507189649330971049854127575847359e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70711310565669331853925519429988855964e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.72047006026700174884151916064158941262e-38),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50985661940624198574968436548711898948e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81705882167596649186405364717835589894e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86537779048672498307196786015602357729e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09555188550938733096253930959407749063e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41930442687159455334801545898059105733e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.09084284266255183930305946875294557622e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.58122754063904909636061457739518406730e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91800215912676651584368499126132687326e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66413330532845384974993669138524203429e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65919563020196445006309683624384862816e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.61596083414169579692212575079167989319e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16321386033703806802403099255708972015e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.90892719803158002834365234646982537288e-25),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x * x * x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.0545e-39
+        static const RealType P[8] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99206710301074508454959544950786401357e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.75243304700875633383991614142545185173e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.69652690455351600373808930804785330828e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.36233941060408773406522171349397343951e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.28958973553713980463808202034854958375e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.55704950313835982743029388151551925282e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.28767698270323629107775935552991333781e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.80591252844738626580182351673066365090e1),
+        };
+        static const RealType Q[7] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.57593243741246726197476469913307836496e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99458751269722094414105565700775283458e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.91043982880665229427553316951582511317e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.99054490423334526438490907473548839751e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.36948968143124830402744607365089118030e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13781639547150826385071482161074041168e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
+}
+
+template <class RealType>
+inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
+}
+
+template <class RealType, class Policy>
+inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x) {
+    //
+    // This calculates the pdf of the Holtsmark distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::pdf(holtsmark<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = holtsmark_pdf_imp_prec(u, tag_type()) / scale;
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.5) {
+        // Rational Approximation
+        // Maximum Relative Error: 1.3147e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(5.0e-1),
+            static_cast<RealType>(-1.34752580674786639030e-1),
+            static_cast<RealType>(1.86318418252163378528e-2),
+            static_cast<RealType>(1.04499798132512381447e-2),
+            static_cast<RealType>(-1.60831910014592923855e-3),
+            static_cast<RealType>(1.38823662364438342844e-4),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.05200341554753776087e-1),
+            static_cast<RealType>(2.12663999430421346175e-1),
+            static_cast<RealType>(7.23836000984872591553e-2),
+            static_cast<RealType>(1.67941072412796299986e-2),
+            static_cast<RealType>(4.71213644318790580839e-3),
+            static_cast<RealType>(5.86825130959777535991e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.6265e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(3.60595773518728397351e-1),
+            static_cast<RealType>(5.75238626843218819756e-1),
+            static_cast<RealType>(-3.31245319943021227117e-1),
+            static_cast<RealType>(1.48132966310216368831e-1),
+            static_cast<RealType>(-2.32875122617713403365e-2),
+            static_cast<RealType>(2.08038303148835575624e-3),
+            static_cast<RealType>(6.01511310581302829460e-6),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.32264360456739861886e0),
+            static_cast<RealType>(6.39715443864749851087e-1),
+            static_cast<RealType>(5.03940458163958921325e-1),
+            static_cast<RealType>(8.84780893031413729292e-2),
+            static_cast<RealType>(3.01497774031208621961e-2),
+            static_cast<RealType>(3.45886005612108195390e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.4398e-20
+        static const RealType P[8] = {
+            static_cast<RealType>(2.43657975600729535515e-1),
+            static_cast<RealType>(-6.02286263626532324632e-2),
+            static_cast<RealType>(4.68361231392743283350e-2),
+            static_cast<RealType>(-1.13497179885838883972e-3),
+            static_cast<RealType>(1.20141595689136205012e-3),
+            static_cast<RealType>(3.02402304689333413256e-4),
+            static_cast<RealType>(-1.22652173865646814676e-6),
+            static_cast<RealType>(2.29521832683440044997e-6),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.82002427359748247121e-1),
+            static_cast<RealType>(3.96529686558825119743e-1),
+            static_cast<RealType>(1.49690294526117385174e-1),
+            static_cast<RealType>(5.15049953937764895435e-2),
+            static_cast<RealType>(1.30218216530450637564e-2),
+            static_cast<RealType>(2.53640337919037463659e-3),
+            static_cast<RealType>(3.79575042317720710311e-4),
+            static_cast<RealType>(2.94034997185982139717e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6148e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(1.05039829654829164883e-1),
+            static_cast<RealType>(1.66621813028423002562e-2),
+            static_cast<RealType>(2.93820049104275137099e-2),
+            static_cast<RealType>(3.36850260303189378587e-3),
+            static_cast<RealType>(2.27925819398326978014e-3),
+            static_cast<RealType>(1.66394162680543987783e-4),
+            static_cast<RealType>(4.51400415642703075050e-5),
+            static_cast<RealType>(2.12164734714059446913e-7),
+            static_cast<RealType>(1.69306881760242775488e-8),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.63461239051296108254e-1),
+            static_cast<RealType>(6.54183344973801096611e-1),
+            static_cast<RealType>(2.92007762594247903696e-1),
+            static_cast<RealType>(1.00918751132022401499e-1),
+            static_cast<RealType>(2.55899135910670703945e-2),
+            static_cast<RealType>(4.85740416919283630358e-3),
+            static_cast<RealType>(6.11435190489589619906e-4),
+            static_cast<RealType>(4.10953248859973756440e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5866e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(3.05754562114095142887e-2),
+            static_cast<RealType>(3.25462617990002726083e-2),
+            static_cast<RealType>(1.78205524297204753048e-2),
+            static_cast<RealType>(5.61565369088816402420e-3),
+            static_cast<RealType>(1.05695297340067353106e-3),
+            static_cast<RealType>(9.93588579804511250576e-5),
+            static_cast<RealType>(2.94302107205379334662e-6),
+            static_cast<RealType>(1.09016076876928010898e-8),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.51164395622515150122e0),
+            static_cast<RealType>(1.09391911233213526071e0),
+            static_cast<RealType>(4.77950346062744800732e-1),
+            static_cast<RealType>(1.34082684956852773925e-1),
+            static_cast<RealType>(2.37572579895639589816e-2),
+            static_cast<RealType>(2.41806218388337284640e-3),
+            static_cast<RealType>(1.10378140456646280084e-4),
+            static_cast<RealType>(1.31559373832822136249e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6575e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(9.47408470248235718880e-3),
+            static_cast<RealType>(4.70888722333356024081e-3),
+            static_cast<RealType>(8.66397831692913140221e-4),
+            static_cast<RealType>(7.11721056656424862090e-5),
+            static_cast<RealType>(2.56320582355149253994e-6),
+            static_cast<RealType>(3.37749186035552101702e-8),
+            static_cast<RealType>(8.32182844837952178153e-11),
+            static_cast<RealType>(-8.80541360484428526226e-14),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.98261117346347123707e-1),
+            static_cast<RealType>(1.97823959738695249267e-1),
+            static_cast<RealType>(2.89311735096848395080e-2),
+            static_cast<RealType>(2.30087055379997473849e-3),
+            static_cast<RealType>(9.60592522700377510007e-5),
+            static_cast<RealType>(1.84474415187428058231e-6),
+            static_cast<RealType>(1.14339998084523151203e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.4164e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(3.19610991747326729867e-3),
+            static_cast<RealType>(5.11880074251341162590e-4),
+            static_cast<RealType>(2.80704092977662888563e-5),
+            static_cast<RealType>(6.31310155466346114729e-7),
+            static_cast<RealType>(5.29618446795457166842e-9),
+            static_cast<RealType>(9.20292337847562746519e-12),
+            static_cast<RealType>(-9.16761719448360345363e-15),
+            static_cast<RealType>(1.20433396121606479712e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.56283944667056551858e-1),
+            static_cast<RealType>(2.56811818304462676948e-2),
+            static_cast<RealType>(1.26678062261253559927e-3),
+            static_cast<RealType>(3.17001344827541091252e-5),
+            static_cast<RealType>(3.68737201224811007437e-7),
+            static_cast<RealType>(1.47625352605312785910e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.2537e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(1.11172037056341397612e-3),
+            static_cast<RealType>(7.84545643188695076893e-5),
+            static_cast<RealType>(1.94862940242223222641e-6),
+            static_cast<RealType>(2.02704958737259525509e-8),
+            static_cast<RealType>(7.99772378955335076832e-11),
+            static_cast<RealType>(6.62544230949971310060e-14),
+            static_cast<RealType>(-3.18234118727325492149e-17),
+            static_cast<RealType>(2.03424457039308806437e-20),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.17861198759233241198e-1),
+            static_cast<RealType>(5.45962263583663240699e-3),
+            static_cast<RealType>(1.25274651876378267111e-4),
+            static_cast<RealType>(1.46857544539612002745e-6),
+            static_cast<RealType>(8.06441204620771968579e-9),
+            static_cast<RealType>(1.53682779460286464073e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType x_cube = x * x * x;
+        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.2897e-18
+        static const RealType P[4] = {
+            static_cast<RealType>(1.99471140200716338970e-1),
+            static_cast<RealType>(-6.90933799347184400422e-1),
+            static_cast<RealType>(4.30385245884336871950e-1),
+            static_cast<RealType>(3.52790131116013716885e-1),
+        };
+        static const RealType Q[3] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(-5.05959751628952574534e0),
+            static_cast<RealType>(8.04408113719341786819e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.5) {
+        // Rational Approximation
+        // Maximum Relative Error: 8.6635e-36
+        static const RealType P[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.48548242430636907136192799540229598637e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31541453581608245475805834922621529866e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.16579064508490250336159593502955219069e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61598809551362112011328341554044706550e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.15119245273512554325709429759983470969e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02145196753734867721148927112307708045e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90817224464950088663183617156145065001e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69596202760983052482358128481956242532e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.50461337222845025623869078372182437091e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62777995800923647521692709390412901586e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.63937253747323898965514197114021890186e-8),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76090180430550757765787254935343576341e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07685236907561593034104428156351640194e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27770556484351179553611274487979706736e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.99201460869149634331004096815257398515e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70139000408086498153685620963430185837e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74682544708653069148470666809094453722e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57607114117485446922700160080966856243e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01069214414741946409122492979083487977e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19996282759031441186748256811206136921e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60933466092746543579699079418115420013e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92780739162611243933581782562159603862e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.1235e-35
+        static const RealType P[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60595773518728397925852903878144761766e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46999595154527091473427440379143006753e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36962313432466566724352608642383560211e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08387290167105915393692028475888846796e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34156151832478939276011262838869269011e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15970594471853166393830585755485842021e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47022841547527682761332752928069503835e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.01955019188793323293925482112543902560e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.03069493388735516695142799880566783261e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61367662035593735709965982000611000987e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62800430658278408539398798888955969345e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.22300086876618079439960709120163780513e-8),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19740977756009966244249035150363085180e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39394884078938560974435920719979860046e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.97107758486905601309707335353809421910e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.36594079604957733960211938310153276332e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85712904264673773213248691029253356702e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.87605080555629969548037543637523346061e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.26356599628579249350545909071984757938e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.79582114368994462181480978781382155103e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.00970375323007336435151032145023199020e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.06528824060244313614177859412028348352e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.13914667697998291289987140319652513139e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.7659e-38
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43657975600729535499895880792984203140e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.37090874182351552816526775008685285108e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70793783828569126853147999925198280654e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.27295555253412802819195403503721983066e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.95916890788873842705597506423512639342e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93625795791721417553345795882983866640e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73237387099610415336810752053706403935e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08118655139419640900853055479087235138e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74920069862339840183963818219485580710e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59015304773612605296533206093582658838e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57256820413579442950151375512313072105e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.36240848333000575199740403759568680951e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53890585580518120552628221662318725825e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59245311730292556271235324976832000740e-10),
+        };
+        static const RealType Q[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.49800491033591771256676595185869442663e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35827615015880595229881139361463765537e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41657125931991211322147702760511651998e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11782602975553967179829921562737846592e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79410805176258968660086532862367842847e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22872839892405613311532856773434270554e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23742349724658114137235071924317934569e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.80350762663884259375711329227548815674e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59501693037547119094683008622867020131e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86068186167498269806443077840917848151e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.36940342373887783231154918541990667741e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48911186460768204167014270878839691938e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.55051094964993052272146587430780404904e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.96312716130620326771080033656930839768e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45496951385730104726429368791951742738e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.9091e-35
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05039829654829170780787685299556996311e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28948022754388615368533934448107849329e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.34139151583225691775740839359914493385e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13366377215523066657592295006960955345e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08045462837998791188853367062130086996e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37648565386728404881404199616182064711e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14881702523183566448187346081007871684e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73169022445183613027772635992366708052e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.86434609673325793686202636939208406356e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20865083025640755296377488921536984172e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24550087063009488023243811976147518386e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78763689691843975658550702147832072016e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.53901449493513509116902285044951137217e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64133451376958243174967226929215155126e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78021916681275593923355425070000331160e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40116391931116431686557163556034777896e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.43891156389092896219387988411277617045e-15),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30840297297890638941129884491157396207e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16059271948787750556465175239345182035e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.32333703228724830516425197803770832978e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74722711058640395885914966387546141874e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57544653090705553268164186689966671940e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.65943099435809995745673109708218670077e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74158626875895095042054345316232575354e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65978318533667031874695821156329945501e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07907034178758316909655424935083792468e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.16769901831316460137104511711073411646e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72764558714782436683712413015421717627e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42494185105694341746192094740530489313e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.47668761140694808076322373887857100882e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06395948884595166425357861427667353718e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.04398743651684916010743222115099630062e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47852251142917253705233519146081069006e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.2255e-36
+        static const RealType P[20] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05754562114095147060025732340404111260e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29082907781747007723015304584383528212e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.15736486393536930535038719804968063752e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47619683293773846642359668429058772885e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78777185267549567154655052281449528836e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.32280474402180284471490985942690221861e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45430564625797085273267452885960070105e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.81643129239005795245093568930666448817e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57851748656417804512189330871167578685e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.04264676511381380381909064283066657450e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.84536783037391183433322642273799250079e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27169201994160924743393109705813711010e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42623512076200527099335832138825884729e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.98298083389459839517970895839114237996e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71357920034737751299594537655948527288e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.98563999354325930973228648080876368296e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36248172644168880316722905969876969074e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61071663749398045880261823483568866904e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.95933262363502031836408613043245164787e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23007623135952181561484264810647517912e-21),
+        };
+        static const RealType Q[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17760389606658547971193065026711073898e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49565543987559264712057768584303008339e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94822569926563661124528478579051628722e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14676844425183314970062115422221981422e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35960757354198367535169328826167556715e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04865288305482048252211468989095938024e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51599632816346741950206107526304703067e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74065824586512487126287762563576185455e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91819078437689679732215988465616022328e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.41675362609023565846569121735444698127e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17176431752708802291177040031150143262e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52367587943529121285938327286926798550e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59405168077254169099025950029539316125e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29448420654438993509041228047289503943e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.70091773726833073512661846603385666642e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.03909417984236210307694235586859612592e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.59098698207309055890188845050700901852e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28146456709550379493162440280752828165e-14),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0174e-36
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47408470248235665279366712356669210597e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32149712567170349164953101675315481096e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39806230477579028722350422669222849223e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19665271447867857827798702851111114658e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.06773237553503696884546088197977608676e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41294370314265386485116359052296796357e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74848600628353761723457890991084017928e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52963427970210468265870547940464851481e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.33389244528769791436454176079341120973e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.86702000100897346192018772319301428852e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04192907586200235211623448416582655030e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70804269459077260463819507381406529187e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52665761996923502719902050367236108720e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.01866635015788942430563628065687465455e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46658865059509532456423012727042498365e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.05806999626031246519161395419216393127e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.37645700309533972676063947195650607935e-26),
+        };
+        static const RealType Q[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59608758824065179587008165265773042260e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17347162462484266250945490058846704988e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.24511137251392519285309985668265122633e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58497164094526279145784765183039854604e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40787701096334660711443654292041286786e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.34615029717812271556414485397095293077e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.17712219229282308306346195001801048971e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.24578142893420308057222282020407949529e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23429691331344898578916434987129070432e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41486460551571344910835151948209788541e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23569151219279213399210115101532416912e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.21438860148387356361258237451828377118e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.46770060692933726695086996017149976796e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58079984178724940266882149462170567147e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19997796316046571607659704855966005180e-17),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.5109e-36
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19610991747326725339429696634365932643e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74646611039453235739153286141429338461e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13331430865337412098234177873337036811e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58947311195482646360642638791970923726e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79226752074485124923797575635082779509e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73081326043094090549807549513512116319e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05408849431691450650464797109033182773e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75716486666270246158606737499459843698e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81075133718930099703621109350447306080e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41318403854345256855350755520072932140e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70220987388883118699419526374266655536e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38711669183547686107032286389030018396e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31300491679098874872172866011372530771e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.99223939265527640018203019269955457925e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18316957049006338447926554380706108087e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47298013808154174645356607027685011183e-32),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42561659771176310412113991024326129105e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83353398513931409985504410958429204317e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07254121026393428163401481487563215753e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36667170168890854756291846167398225330e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54019749685699795075624204463938596069e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35321766966107368759516431698755077175e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13350720091296144188972188966204719103e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38107118390482863395863404555696613407e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59267757423034664579822257229473088511e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29549090773392058626428205171445962834e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69922128600755513676564327500993739088e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31337037977667816904491472174578334375e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28088047429043940293455906253037445768e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.01213369826105495256520034997664473667e-22),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2707e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11172037056341396583040940446061501972e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09383362521204903801686281772843962372e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71440982391172647693486692131238237524e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.01685075759372692173396811575536866699e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36574894913423830789864836789988898151e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.59644999935503505576091023207315968623e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95573282292603122067959656607163690356e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10361486103428098366627536344769789255e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80946231978997457068033851007899208222e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.39341134002270945594553624959145830111e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72307967968246649714945553177468010263e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41093409238620968003297675770440189200e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70464969040825495565297719377221881609e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25341184125872354328990441812668510029e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54663422572657744572284839697818435372e-36),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35632539169215377884393376342532721825e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.46975491055790597767445011183622230556e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51806800870130779095309105834725930741e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07403939022350326847926101278370197017e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66046114012817696416892197044749060854e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.16723371111678357128668916130767948114e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22972796529973974439855811125888770710e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91073180314665062004869985842402705599e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43753004383633382914827301174981384446e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.77313206526206002175298314351042907499e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32850553089285690900825039331456226080e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.85369976595753971532524294793778805089e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28948021485210224442871255909409155592e-25),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType x_cube = x * x * x;
+        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.4677e-35
+        static const RealType P[7] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.48481268366645066801385595379873318648e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64087860141734943856373451877569284231e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.45555576045996041260191574503331698473e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43290677381328916734673040799990923091e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63011127597770211743774689830589568544e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.61127812511057623691896118746981066174e0),
+        };
+        static const RealType Q[6] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90660291309478542795359451748753358123e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60631500002415936739518466837931659008e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.88655117367497147850617559832966816275e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48350179543067311398059386524702440002e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.18873206560757944356169500452181141647e3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+    if (x >= 0) {
+        return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - holtsmark_cdf_plus_imp_prec(-x, tag) : holtsmark_cdf_plus_imp_prec(-x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - holtsmark_cdf_plus_imp_prec(-x, tag) : holtsmark_cdf_plus_imp_prec(-x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+    //
+    // This calculates the cdf of the Holtsmark distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::cdf(holtsmark<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = holtsmark_cdf_imp_prec(u, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (ilogb(p) >= -2) {
+        RealType t = -log2(ldexp(p, 1));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.8068e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(7.59789769759814986929e-1),
+            static_cast<RealType>(1.27515008642985381862e0),
+            static_cast<RealType>(4.38619247097275579086e-1),
+            static_cast<RealType>(-1.25521537863031799276e-1),
+            static_cast<RealType>(-2.58555599127223857177e-2),
+            static_cast<RealType>(1.20249932437303932411e-2),
+            static_cast<RealType>(-1.36753104188136881229e-3),
+            static_cast<RealType>(6.57491277860092595148e-5),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.48696501912062288766e0),
+            static_cast<RealType>(2.06239370128871696850e0),
+            static_cast<RealType>(5.67577904795053902651e-1),
+            static_cast<RealType>(-2.89022828087034733385e-2),
+            static_cast<RealType>(-2.17207943286085236479e-2),
+            static_cast<RealType>(3.14098307020814954876e-4),
+            static_cast<RealType>(3.51448381406676891012e-4),
+            static_cast<RealType>(5.71995514606568751522e-5),
+        };
+
+        result = t * tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -3) {
+        RealType t = -log2(ldexp(p, 2));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0339e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(3.84521387984759064238e-1),
+            static_cast<RealType>(4.15763727809667641126e-1),
+            static_cast<RealType>(-1.73610240124046440578e-2),
+            static_cast<RealType>(-3.89915764128788049837e-2),
+            static_cast<RealType>(1.07252911248451890192e-2),
+            static_cast<RealType>(7.62613727089795367882e-4),
+            static_cast<RealType>(-3.11382403581073580481e-4),
+            static_cast<RealType>(3.93093062843177374871e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.76193897442484823754e-1),
+            static_cast<RealType>(3.70953499602257825764e-2),
+            static_cast<RealType>(-2.84211795745477605398e-2),
+            static_cast<RealType>(2.66146101014551209760e-3),
+            static_cast<RealType>(1.85436727973937413751e-3),
+            static_cast<RealType>(2.00318687649825430725e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.4431e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(4.46943301497773314460e-1),
+            static_cast<RealType>(-1.07267614417424412546e-2),
+            static_cast<RealType>(-7.21097021064631831756e-2),
+            static_cast<RealType>(2.93948745441334193469e-2),
+            static_cast<RealType>(-7.33259305010485915480e-4),
+            static_cast<RealType>(-1.38660725579083612045e-3),
+            static_cast<RealType>(2.95410432808739478857e-4),
+            static_cast<RealType>(-2.88688017391292485867e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(-2.72809429017073648893e-2),
+            static_cast<RealType>(-7.85526213469762960803e-2),
+            static_cast<RealType>(2.41360900478283465241e-2),
+            static_cast<RealType>(3.44597797125179611095e-3),
+            static_cast<RealType>(-8.65046428689780375806e-4),
+            static_cast<RealType>(-1.04147382037315517658e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -6) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8871e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(4.25344469980677332786e-1),
+            static_cast<RealType>(3.42055470008289997369e-2),
+            static_cast<RealType>(9.33607217644370441642e-2),
+            static_cast<RealType>(4.57057092587794346086e-2),
+            static_cast<RealType>(1.16149976708336017542e-2),
+            static_cast<RealType>(6.40479797962035786337e-3),
+            static_cast<RealType>(1.58526153828271386329e-3),
+            static_cast<RealType>(3.84032908993313260466e-4),
+            static_cast<RealType>(6.98960839033991110525e-5),
+            static_cast<RealType>(9.66690587477825432174e-6),
+        };
+        static const RealType Q[10] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.60044610004497775009e-1),
+            static_cast<RealType>(2.41675490962065446592e-1),
+            static_cast<RealType>(1.13752642382290596388e-1),
+            static_cast<RealType>(4.05058759031434785584e-2),
+            static_cast<RealType>(1.59432816225295660111e-2),
+            static_cast<RealType>(4.79286678946992027479e-3),
+            static_cast<RealType>(1.16048151070154814260e-3),
+            static_cast<RealType>(2.01755520912887201472e-4),
+            static_cast<RealType>(2.82884561026909054732e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8173e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(3.68520435599726877886e-1),
+            static_cast<RealType>(8.26682725061327242371e-1),
+            static_cast<RealType>(6.85235826889543887309e-1),
+            static_cast<RealType>(3.28640408399661746210e-1),
+            static_cast<RealType>(9.04801242897407528807e-2),
+            static_cast<RealType>(1.57470088502958130451e-2),
+            static_cast<RealType>(1.61541023176880542598e-3),
+            static_cast<RealType>(9.78919203915954346945e-5),
+            static_cast<RealType>(9.71371309261213597491e-8),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.29132755303753682133e0),
+            static_cast<RealType>(1.95530118226232968288e0),
+            static_cast<RealType>(9.55029685883545321419e-1),
+            static_cast<RealType>(2.68254036588585643328e-1),
+            static_cast<RealType>(4.61398419640231283164e-2),
+            static_cast<RealType>(4.66131710581568432246e-3),
+            static_cast<RealType>(2.94491397241310968725e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.0376e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(3.48432718168951419458e-1),
+            static_cast<RealType>(2.99680703419193973028e-1),
+            static_cast<RealType>(1.09531896991852433149e-1),
+            static_cast<RealType>(2.28766133215975559897e-2),
+            static_cast<RealType>(3.09836969941710802698e-3),
+            static_cast<RealType>(2.89346186674853481383e-4),
+            static_cast<RealType>(1.96344583080243707169e-5),
+            static_cast<RealType>(9.48415601271652569275e-7),
+            static_cast<RealType>(3.08821091232356755783e-8),
+            static_cast<RealType>(5.58003465656339818416e-10),
+        };
+        static const RealType Q[10] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.73938978582311007855e-1),
+            static_cast<RealType>(3.21771888210250878162e-1),
+            static_cast<RealType>(6.70432401844821772827e-2),
+            static_cast<RealType>(9.05369648218831664411e-3),
+            static_cast<RealType>(8.50098390828726795296e-4),
+            static_cast<RealType>(5.73568804840571459050e-5),
+            static_cast<RealType>(2.78374120155590875053e-6),
+            static_cast<RealType>(9.03427646135263412003e-8),
+            static_cast<RealType>(1.63556457120944847882e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.2804e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(3.41419813138786920868e-1),
+            static_cast<RealType>(1.30219412019722274099e-1),
+            static_cast<RealType>(2.36047671342109636195e-2),
+            static_cast<RealType>(2.67913051721210953893e-3),
+            static_cast<RealType>(2.10896260337301129968e-4),
+            static_cast<RealType>(1.19804595761611765179e-5),
+            static_cast<RealType>(4.91470756460287578143e-7),
+            static_cast<RealType>(1.38299844947707591018e-8),
+            static_cast<RealType>(2.25766283556816829070e-10),
+            static_cast<RealType>(-8.46510608386806647654e-18),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.81461950831351846380e-1),
+            static_cast<RealType>(6.91390438866520696447e-2),
+            static_cast<RealType>(7.84798596829449138229e-3),
+            static_cast<RealType>(6.17735117400536913546e-4),
+            static_cast<RealType>(3.50937328177439258136e-5),
+            static_cast<RealType>(1.43958654321452532854e-6),
+            static_cast<RealType>(4.05109749922716264456e-8),
+            static_cast<RealType>(6.61306247924109415113e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8545e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(3.41392032051575965049e-1),
+            static_cast<RealType>(1.53372256183388434238e-1),
+            static_cast<RealType>(3.33822240038718319714e-2),
+            static_cast<RealType>(4.66328786929735228532e-3),
+            static_cast<RealType>(4.67981207864367711082e-4),
+            static_cast<RealType>(3.48119463063280710691e-5),
+            static_cast<RealType>(2.17755850282052679342e-6),
+            static_cast<RealType>(7.40424342670289242177e-8),
+            static_cast<RealType>(4.61294046336533026640e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.49255524669251621744e-1),
+            static_cast<RealType>(9.77826688966262423974e-2),
+            static_cast<RealType>(1.36596271675764346980e-2),
+            static_cast<RealType>(1.37080296105355418281e-3),
+            static_cast<RealType>(1.01970588303201339768e-4),
+            static_cast<RealType>(6.37846903580539445994e-6),
+            static_cast<RealType>(2.16883897125962281968e-7),
+            static_cast<RealType>(1.35121503608967367232e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else {
+        const static RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
+
+        RealType p_square = p * p;
+
+        if (isnormal(p_square)) {
+            result = 1 / (cbrt(p_square) * c);
+        }
+        else if (p > 0) {
+            result = 1 / (cbrt(p) * cbrt(p) * c);
+        }
+        else {
+            result = std::numeric_limits<RealType>::infinity();
+        }
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (ilogb(p) >= -2) {
+        RealType u = -log2(ldexp(p, 1));
+
+        if (u < 0.5) {
+            // Rational Approximation
+            // Maximum Relative Error: 1.7987e-35
+            static const RealType P[14] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.59789769759815031687162026655576575384e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23247138049619855169890925442523844619e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35351935489348780511227763760731136136e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.17321534695821967609074567968260505604e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30930523792327030433989902919481147250e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.47676800034255152477549544991291837378e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.09952071024064609787697026812259269093e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.65479872964217159571026674930672527880e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30204907832301876030269224513949605725e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.61038349134944320766567917361933431224e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.17242905696479357297850061918336600969e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43640101589433162893041733511239841220e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.39406616773257816628641556843884616119e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54871597065387376666252643921309051097e-7),
+            };
+            static const RealType Q[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06310038178166385607814371094968073940e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06144046990424238286303107360481469219e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17860081295611631017119482265353540470e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26319639748358310901277622665331115333e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25962127567362715217159291513550804588e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65543974081934423010588955830131357921e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.80331848633772107482330422252085368575e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.97426948050874772305317056836660558275e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10722999873793200671617106731723252507e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.68871255379198546500699434161302033826e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70190278641952708999014435335172772138e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11562497711461468804693130702653542297e-7),
+            };
+
+            result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
+        }
+        else {
+            RealType t = u - 0.5;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.5554e-35
+            static const RealType P[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63490994331899195346399558699533994243e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68682839419340144322747963938810505658e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63089084712442063245295709191126453412e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24910510426787025593146475670961782647e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.14005632199839351091767181535761567981e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.88144015238275997284082820907124267240e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.12015895125039876623372795832970536355e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.96386756665254981286292821446749025989e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.82855208595003635135641502084317667629e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.18007513930934295792217002090233670917e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.82563310387467580262182864644541746616e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52830681121195099547078704713089681353e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91383571211375811878311159248551586411e-8),
+            };
+            static const RealType Q[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96820655322136936855997114940653763917e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30209571878469737819039455443404070107e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61235660141139249931521613001554108034e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.31683133997030095798635713869616211197e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20681979279848555447978496580849290723e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08958899028812330281115719259773001136e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02478613175545210977059079339657545008e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.68653479132148912896487809682760117627e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35166554499214836086438565154832646441e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95409975934011596023165394669416595582e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84312112139729518216217161835365265801e-7),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+        }
+    }
+    else if (ilogb(p) >= -3) {
+        RealType u = -log2(ldexp(p, 2));
+
+        if (u < 0.5) {
+            // Rational Approximation
+            // Maximum Relative Error: 1.0297e-35
+            static const RealType P[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84521387984759060262188972210005114936e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70837834325236202821328032137877091515e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53856963029219911450181095566096563059e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.97659091653089105048621336944687224192e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77726241585387617566937892474685179582e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21657224955483589784473724186837316423e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76357400631206366078287330192525531850e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.45967265853745968166172649261385754061e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08367654892620484522749804048317330020e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41224530727710207304898458924763411052e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.02908228738160003274584644834000176496e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05702214080592377840761032481067834813e-7),
+            };
+            static const RealType Q[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33954869248363301881659953529609341564e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73738626674455393272550888585363920917e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.90708494363306682523722238824373341707e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.49559648492983033200126224112060119905e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.07561158260652000950392950266037061167e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30349651195547682860585068738648645100e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.21766408404123861757376277367204136764e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.22181499366766592894880124261171657846e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.74488053046587079829684775540618210211e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90504597668186854963746384968119788469e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45195198322028676384075318222338781298e-7),
+            };
+
+            result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
+        }
+        else {
+            RealType t = u - 0.5;
+
+            // Rational Approximation
+            // Maximum Relative Error: 1.3688e-35
+            static const RealType P[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34418795581931891732555950599385666106e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.13006013029934051875748102515422669897e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.27990072710518465265454549585803147529e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.82530244963278920355650323928131927272e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05335741422175616606162502617378682462e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71242678756797136217651369710748524650e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.65147398836785709305701073315614307906e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23912765853731378067295654886575185240e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77861910171412622761254991979036167882e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.11971510714149983297022108523700437739e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23649928279010039670034778778065846828e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.99636080473697209793683863161785312159e-8),
+            };
+            static const RealType Q[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95056572065373808001002483348789719155e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.55702988004729812458415992666809422570e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.07586989542594910084052301521098115194e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96831670560124470215505714403486118412e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.86445076378084412691927796983792892534e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.75566285003039738258189045863064261980e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.18557444175572723760508226182075127685e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66667716357950609103712975111660496416e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70999480357934082364999779023268059131e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.14604868719110256415222454908306045416e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.32724040071094913191419223901752642417e-8),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+        }
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.6020e-36
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46943301497773318715008398224877079279e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.85403413700924949902626248891615772650e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02791895890363892816315784780533893399e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.89147412486638444082129846251261616763e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.93382251168424191872267997181870008850e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.68332196426082871660060467570049113632e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.88720436260994811649162949644253306037e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34099304204778307050211441936900839075e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.42970601149275611131932131801993030928e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19329425598839605828710629592687495198e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.48826007216547106568423189194739111033e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47132934846160946190230821709692067279e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34123780321108493820637601375183345528e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.64549285026064221742294542922996905241e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72723306533295983872420985773212608299e-9),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.23756826160440280076231428938184359865e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46557011055563840763437682311082689407e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18907861669025579159409035585375166964e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.09998981512549500250715800529896557509e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.09496663758959409482213456915225652712e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37086325651334206453116588474211557676e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65325780110454655811120026458133145750e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.93435549562125602056160657604473721758e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34967558308250784125219085040752451132e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73883529653464036447550624641291181317e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.88600727347267778330635397957540267359e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.26681383000234695948685993798733295748e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19871610873353691152255428262732390602e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42468017918888155246438948321084323623e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -5) {
+        RealType u = -log2(ldexp(p, 4));
+
+        if (u < 0.5) {
+            // Rational Approximation
+            // Maximum Relative Error: 5.0596e-35
+            static const RealType P[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25344469980677353573160570139298422046e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41915371584999983192100443156935649063e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02829239548689190780023994008688591230e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29283473326959885625548350158197923999e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.01078477165670046284950196047161898687e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02714892887893367912743194877742997622e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.43133417775367444366548711083157149060e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34782994090554432391320506638030058071e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06742736859237185836735105245477248882e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.55982601406660341132288721616681417444e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.57770758189194396236862269776507019313e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29311341249565125992213260043135188072e-8),
+            };
+            static const RealType Q[12] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54021943144355190773797361537886598583e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30965787836836308380896385568728211303e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19314242976592846926644622802257778872e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.84123785238634690769817401191138848504e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.75779029464908805680899310810660326192e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15078294915445673781718097749944059134e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84667183003626452412083824490324913477e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.59521438712225874821007396323337016693e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.90446539427779905568600432145715126083e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.21425779911599424040614866482614099753e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.00972806247654369646317764344373036462e-8),
+            };
+
+            result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
+        }
+        else {
+            RealType t = u - 0.5;
+
+            // Rational Approximation
+            // Maximum Relative Error: 8.3743e-35
+            static const RealType P[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08071367192424306005939751362206079160e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94625900993512461462097316785202943274e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55970241156822104458842450713854737857e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07663066299810473476390199553510422731e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89859986209620592557993828310690990189e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04002735956724252558290154433164340078e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.28754717941144647796091692241880059406e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19307116062867039608045413276099792797e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.02377178609994923303160815309590928289e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.71739619655097982325716241977619135216e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70229045058419872036870274360537396648e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90495731447121207951661931979310025968e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23210708203609461650368387780135568863e-8),
+            };
+            static const RealType Q[11] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.93402256203255215539822867473993726421e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42452702043886045884356307934634512995e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.16981055684612802160174937997247813645e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39560623514414816165791968511612762553e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26014275897567952035148355055139912545e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42163967753843746501638925686714935099e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.63605648300801696460942201096159808446e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.55933967787268788177266789383155699064e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41526208021076709058374666903111908743e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.08505866202670144225100385141263360218e-6),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+        }
+    }
+    else if (ilogb(p) >= -6) {
+        RealType t = -log2(ldexp(p, 5));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.4734e-35
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92042979500197776619414802317216082414e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94742044285563829335663810275331541585e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14525306632578654372860377652983462776e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88893010132758460781753381176593178775e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08491462791290535107958214106528611951e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61374431854187722720094162894017991926e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11641062509116613779440753514902522337e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12474548036763970495563846370119556004e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.48140831258790372410036499310440980121e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26913338169355215445128368312197650848e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63109797282729701768942543985418804075e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55296802973076575732233624155433324402e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72108609713971908723724065216410393928e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.93328436272999507339897246655916666269e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72119240610740992234979508242967886200e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17836139198065889244530078295061548097e-10),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78065342260594920160228973261455037923e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08575070304822733863613657779515344137e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81185785915044621118680763035984134530e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87597191269586886460326897968559867853e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07903258768761230286548634868645339678e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88395769450457864233486684232536503140e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05678227243099671420442217017131559055e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.24803207742284923122212652186826674987e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06094715338829793088081672723947647238e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.96454433858093590192363331553516923090e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94509901530299070041475386866323617753e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49001710126540196485963921184736711193e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58899179756014192338509671769986887613e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06916561094749601736592488829778059190e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1570e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.68520435599726860132888599110871216319e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.01076105507184082206031922185510102322e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39912455237662038937400667644545834191e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51088991221663244634723139723207272560e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26465949648856746869050310379379898086e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37079746226805258449355819952819997723e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49372033421420312720741838903118544951e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95729572745049276972587492142384353131e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92794840197452838799536047152725573779e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96897979363475104635129765703613472468e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44138843334474914059035559588791041371e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.78076328055619970057667292651627051391e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04182093251998194244585085400876144351e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04392999917657413659748817212746660436e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76006125565969084470924344826977844710e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21045181507045010640119572995692565368e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61400097324698003962179537436043636306e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.88084230973635340409728710734906398080e-11),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49319798750825059930589954921919984293e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90218243410186000622818205955425584848e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25384789213915993855434876209137054104e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.58563858782064482133038568901836564329e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39112608961600614189971858070197609546e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29192895265168981204927382938872469754e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66418375973954918346810939649929797237e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01606040038159207768769492693779323748e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.75837675697421536953171865636865644576e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30258315910281295093103384193132807400e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28333635097670841003561009290200071343e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.04871369296490431325621140782944603554e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05077352164673794093561693258318905067e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28508157403208548483052311164947568580e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22527248376737724147359908626095469985e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75479484339716254784610505187249810386e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39990051830081888581639577552526319577e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1362e-35
+        static const RealType P[22] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48432718168951398420402661878962745094e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55946442453078865766668586202885528338e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.54912640113904816247923987542554486059e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60852745978561293262851287627328856197e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93256608166097432329211369307994852513e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.94707001299612588571704157159595918562e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40368387009950846525432054396214443833e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62326983889228773089492130483459202197e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97166112600628615762158757484340724056e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95053681446806610424931810174198926457e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13613767164027076487881255767029235747e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46627172639536503825606138995804926378e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.26813757095977946534946955553296696736e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01393212063713249666862633388902006492e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04428602119155661411061942866480445477e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52977051350929618206095556763031195967e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63092013964238065197415324341392517794e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77457116423818347179318334884304764609e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10372468210274291890669895933038762772e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85517152798650696598776156882211719502e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01916800572423194619358228507804954863e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72241483171311778625855302356391965266e-26),
+        };
+        static const RealType Q[21] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18341916009800042837726003154518652168e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19215655980509256344434487727207541208e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34380326549827252189214516628038733750e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.65069135930665131327262366757787760402e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74132905027750048531814627726862962404e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.11184893124573373947875834716323223477e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.68456853089572312034718359282699132364e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16340806625223749486884390838046244494e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45007766006724826837429360471785418874e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50443251593190111677537955057976277305e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30829464745241179175728900376502542995e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.57256894336319418553622695416919409120e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89973763917908403951538315949652981312e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05834675579622824896206540981508286215e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32721343511724613011656816221169980981e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77569292346900432492044041866264215291e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39903737668944675386972393000746368518e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23200083621376582032771041306045737695e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43557805626692790539354751731913075096e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91326410956582998375100191562832969140e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.1729e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41419813138786928653984591611599949126e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94225020281693988785012368481961427155e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28967134188573605597955859185818311256e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.16617725083935565014535265818666424029e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13379610773944032381149443514208866162e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06508483032198116332154635763926628153e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.89315471210589177037346413966039863126e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72993906450633221200844495419180873066e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32883391567312244751716481903540505335e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.50998889887280885500990101116973130081e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23247766687180294767338042555173653249e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.12326475887709255500757383109178584638e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11688319088825228685832870139320733695e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95381542569360703428852622701723193645e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.70730387484749668293167350494151199659e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84243405919322052861165273432136993833e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40860917180131228318146854666419586211e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.85122374200561402546731933480737679849e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.79744248200459077556218062241428072826e-32),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68930884381361438749954611436694811868e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54944129151720429074748655153760118465e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68493670923968273171437877298940102712e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.32109946297461941811102221103314572340e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.11983030120265263999033828442555862122e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31204888358097171713697195034681853057e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38548604936907265274059071726622071821e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.82158855359673890472124017801768455208e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78564556026252472894386810079914912632e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.46854501887011863360558947087254908412e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67236380279070121978196383998000020645e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20076045812548485396837897240357026254e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15814123143437217877762088763846289858e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67177999717442465582949551415385496304e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71135001552136641449927514544850663366e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98449056954034104266783180068258117013e-22),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.8330e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392032051575981622151194498090952488e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32651097995974052731414709779952524875e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51927763729719814565225981452897995722e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.11148082477882981299945196621348531180e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80457559655975695558885644380771202301e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96223001525552834934139567532649816367e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10625449265784963560596299595289620029e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.14785887121654524328854820350425279893e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00832358736396150660417651391240544392e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63128732906298604011217701767305935851e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86148432181465165445355560568442172406e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44088921565424320298916604159745842835e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.95220124898384051195673049864765987092e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50531060529388128674128631193212903032e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06119051130826148039530805693452156757e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19849873960405145967462029876325494393e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66833600176986734600260382043861669021e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07829060832934383885234817363480653925e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21485411177823993142696645934560017341e-40),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.88559444380290379529260819350179144435e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.37942717465159991856146428659881557553e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.11409915376157429952160202733757574026e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.21511733003564236929107862750700281202e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74773232555012468159223116269289241483e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.24042271031862389840796415749527818562e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50790246845873571117791557191071320982e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88274886666078071130557536971927872847e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94242592538917360235050248151146832636e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45262967284548223426004177385213311949e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30081806380053435857465845326686775489e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62226426496757450797456131921060042081e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40933140159573381494354127717542598424e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03760580312376891985077265621432029857e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43980683769941233230954109646012150124e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88686274782816858372719510890126716148e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07336140055510452905474533727353308321e-25),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.9085e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392031627647840832213878541731833340e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48256908849985263191468999842405689327e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.16515822909144946601084169745484248278e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42246334265547596187501472291026180697e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.54145961608971551335283437288203286104e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64840354062369555376354747633807898689e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.38246669464526050793398379055335943951e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29684566081664150074215568847731661446e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98456331768093420851844051941851740455e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36738267296531031235518935656891979319e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08128287278026286279504717089979753319e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.38334581618709868951669630969696873534e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.08478537820365448038773095902465198679e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30768169494950935152733510713679558562e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49254243621461466892836128222648688091e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17026357413798368802986708112771803774e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05630817682870951728748696694117980745e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.13881361534205323565985756195674181203e-50),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239599863811873205236246e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849060586077266046297964e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29542078693828543540010668640353491847e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33027698228265344545932885863767276804e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06868444562964057780556916100143215394e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.97868278672593071061800234869603536243e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79869926850283188735312536038469293739e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75298857713475428365153491580710497759e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.93449891515741631851202042430818496480e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36715626731277089013724968542144140938e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.98125789528264426869121548546848968670e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78234546049400950521459021508632294206e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83044000387150792643468853129175805308e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30111486296552039388613073915170671881e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28628462422858134962149154420358876352e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48108558735886480279744474396456699335e-21),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
+    }
+    else {
+        const static RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
+
+        RealType p_square = p * p;
+
+        if (isnormal(p_square)) {
+            result = 1 / (cbrt(p_square) * c);
+        }
+        else if (p > 0) {
+            result = 1 / (cbrt(p) * cbrt(p) * c);
+        }
+        else {
+            result = std::numeric_limits<RealType>::infinity();
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+{
+    if (p > 0.5) {
+        return holtsmark_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? holtsmark_quantile_upper_imp_prec(p, tag) : -holtsmark_quantile_upper_imp_prec(p, tag);
+}
+
+template <class RealType>
+inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+{
+    if (p > 0.5) {
+        return holtsmark_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? holtsmark_quantile_upper_imp_prec(p, tag) : -holtsmark_quantile_upper_imp_prec(p, tag);
+}
+
+template <class RealType, class Policy>
+inline RealType holtsmark_quantile_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+{
+    // This routine implements the quantile for the Holtsmark distribution,
+    // the value p may be the probability, or its complement if complement=true.
+
+    static const char* function = "boost::math::quantile(holtsmark<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_probability(function, p, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = location + scale * holtsmark_quantile_imp_prec(p, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+{
+    return static_cast<RealType>(2.06944850513462440032);
+}
+
+template <class RealType>
+inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0694485051346244003155800384542166381);
+}
+
+template <class RealType, class Policy>
+inline RealType holtsmark_entropy_imp(const holtsmark_distribution<RealType, Policy>& dist)
+{
+    // This implements the entropy for the Holtsmark distribution,
+
+    static const char* function = "boost::math::entropy(holtsmark<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = holtsmark_entropy_imp_prec<RealType>(tag_type()) + log(scale);
+
+    return result;
+}
+
+} // detail
+
+template <class RealType = double, class Policy = policies::policy<> >
+class holtsmark_distribution
+{
+    public:
+    typedef RealType value_type;
+    typedef Policy policy_type;
+
+    holtsmark_distribution(RealType l_location = 0, RealType l_scale = 1)
+        : mu(l_location), c(l_scale)
+    {
+        static const char* function = "boost::math::holtsmark_distribution<%1%>::holtsmark_distribution";
+        RealType result = 0;
+        detail::check_location(function, l_location, &result, Policy());
+        detail::check_scale(function, l_scale, &result, Policy());
+    } // holtsmark_distribution
+
+    RealType location()const
+    {
+        return mu;
+    }
+    RealType scale()const
+    {
+        return c;
+    }
+
+    private:
+    RealType mu;    // The location parameter.
+    RealType c;     // The scale parameter.
+};
+
+typedef holtsmark_distribution<double> holtsmark;
+
+#ifdef __cpp_deduction_guides
+template <class RealType>
+holtsmark_distribution(RealType) -> holtsmark_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+template <class RealType>
+holtsmark_distribution(RealType, RealType) -> holtsmark_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+#endif
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> range(const holtsmark_distribution<RealType, Policy>&)
+{ // Range of permissible values for random variable x.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> support(const holtsmark_distribution<RealType, Policy>&)
+{ // Range of supported values for random variable x.
+   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType pdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::holtsmark_pdf_imp(dist, x);
+} // pdf
+
+template <class RealType, class Policy>
+inline RealType cdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::holtsmark_cdf_imp(dist, x, false);
+} // cdf
+
+template <class RealType, class Policy>
+inline RealType quantile(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p)
+{
+    return detail::holtsmark_quantile_imp(dist, p, false);
+} // quantile
+
+template <class RealType, class Policy>
+inline RealType cdf(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::holtsmark_cdf_imp(c.dist, c.param, true);
+} //  cdf complement
+
+template <class RealType, class Policy>
+inline RealType quantile(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::holtsmark_quantile_imp(c.dist, c.param, true);
+} // quantile complement
+
+template <class RealType, class Policy>
+inline RealType mean(const holtsmark_distribution<RealType, Policy> &dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType variance(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+{
+    return std::numeric_limits<RealType>::infinity();
+}
+
+template <class RealType, class Policy>
+inline RealType mode(const holtsmark_distribution<RealType, Policy>& dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType median(const holtsmark_distribution<RealType, Policy>& dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType skewness(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no skewness:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::skewness(holtsmark<%1%>&)",
+        "The Holtsmark distribution does not have a skewness: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis(holtsmark<%1%>&)",
+        "The Holtsmark distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis_excess(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis excess:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis_excess(holtsmark<%1%>&)",
+        "The Holtsmark distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType entropy(const holtsmark_distribution<RealType, Policy>& dist)
+{
+    return detail::holtsmark_entropy_imp(dist);
+}
+
+}} // namespaces
+
+
+#endif // BOOST_STATS_HOLTSMARK_HPP
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
new file mode 100644
index 0000000000..8f34124d14
--- /dev/null
+++ b/test/test_holtsmark.cpp
@@ -0,0 +1,795 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_TEST_MODULE StatsHoltsmarkTest
+#include <boost/test/included/unit_test.hpp>
+#include <boost/multiprecision/cpp_bin_float.hpp>
+
+#include <boost/math/distributions/holtsmark.hpp>
+using boost::math::holtsmark_distribution;
+using boost::multiprecision::cpp_bin_float_quad;
+
+template<class RealType, int N>
+void do_test_holtsmark_pdf(){
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36729417918039395222067998266923903487897550760740e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65389736963758327689008908803579458127136270822821e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02515191704410688567167143509210415364664018836038e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51083986231955529936787758130352472694082331202869e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15094236163249353135030241188004077293096105502542e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99750209903363198419241505065146206315152726747464e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.11488945306717663129360225856869217115733169200098e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.57635410598104651856363821355027691095093972951943e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.45396231261375200568114750897618690566092315194568e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.56644599840900478087175884712634478003230341866094e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07991505579130717014680432847812811882295188855215e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21504440259916207727077397273468920426729181666284e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36133628073378183373326886775069575640127303211029e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51745548085348400860371488668500734429223868343929e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68134487107062900924723590620591092812119992658420e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85018067925573560771430043931430243630326746823000e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02038159607840130388931544845552929991729709746772e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.10468477092312109723487937526691724501188944561469e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18768434960425041116444711570747254236793293668156e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26876533945661456653252880545328465490361724757011e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34729279420630671501163324236373491976559833675371e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42262031889641529582832839126322520342094549884605e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.49409942058625893002692983261905908575520500298169e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56108951988457608160176526934999395388199046235972e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.62296840354090035789597147663858548813023471783846e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.67914286936215258107106284322230987052088197806732e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72905929336501384188469491706325278582273134014420e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77221383677408177290219591627664575751370295766362e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80816200831657887972174538033323818453141437738815e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83652730587590691770044766018047580182775092180058e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85700868106012048340895194764008089858950037497619e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86938660017923959009561433879636172948429661600328e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.87352751452164445024482162286994868261727837966217e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86938660017923959009561433879636172948429661600328e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85700868106012048340895194764008089858950037497619e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83652730587590691770044766018047580182775092180058e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80816200831657887972174538033323818453141437738815e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77221383677408177290219591627664575751370295766362e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72905929336501384188469491706325278582273134014420e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.67914286936215258107106284322230987052088197806732e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.62296840354090035789597147663858548813023471783846e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56108951988457608160176526934999395388199046235972e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.49409942058625893002692983261905908575520500298169e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42262031889641529582832839126322520342094549884605e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34729279420630671501163324236373491976559833675371e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26876533945661456653252880545328465490361724757011e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18768434960425041116444711570747254236793293668156e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.10468477092312109723487937526691724501188944561469e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02038159607840130388931544845552929991729709746772e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85018067925573560771430043931430243630326746823000e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68134487107062900924723590620591092812119992658420e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51745548085348400860371488668500734429223868343929e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36133628073378183373326886775069575640127303211029e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21504440259916207727077397273468920426729181666284e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07991505579130717014680432847812811882295188855215e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.56644599840900478087175884712634478003230341866094e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.45396231261375200568114750897618690566092315194568e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.57635410598104651856363821355027691095093972951943e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.11488945306717663129360225856869217115733169200098e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99750209903363198419241505065146206315152726747464e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15094236163249353135030241188004077293096105502542e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51083986231955529936787758130352472694082331202869e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02515191704410688567167143509210415364664018836038e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65389736963758327689008908803579458127136270822821e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36729417918039395222067998266923903487897550760740e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.66754576694881156512310862711445437434536539665220e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.11173604765480684115169149814306652067264621028219e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.40661030133408839114013026681116038222350468593972e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22346322254737897976061662951210609505224644527458e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37441612177611972649583292419049409747033180591176e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.74744460065068339118467750880557414156817094839507e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.27304026309950351561235691054710976330201642992015e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90649774685568282389553481307707005424869182652166e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38767874243521145729361398147898730301527980427894e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04777602492944046116536405570429208835346612226751e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.14427312838534546510639939284636768866987456541955e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.48125490715334110982111302156190976484065179596964e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25926848543648125740563360613612653857829343973075e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.33819608589296696976594994753563070519825392999328e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62882342819480981578669644070664737082208227167328e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.07231582988207590928480356376941073734041404814646e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.27006701837892764913571864450685488819589225207004e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73366906892470965030093227280098921046549874789447e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.35957320021440204694920969306620767773792096574145e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08962051920666002556891360954800856160496745325982e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.89257005093845424113694708405490444536741708307432e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.36985573727704971748849427466806366268717813920884e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.18908057108330090847508167263164576897080536147998e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25741312407933720816582583160953651639222885045617e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90521803068812235229266578780465914597024834788499e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.99440098605222381975051163529379005706849379136631e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.35556983515831713649398537010595127693244595946631e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89252591391344813399503397931059007207167187335384e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54761819718387004182264813450582914982582239574760e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28473144505453904388319480756963924103363111590946e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08038477619830474574170723303117982155643976342020e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.18821097500148811906668422616947735567544539343910e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.83770756909753597744679176403606964363170824955403e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25030682765210472090258978149127752580598842866547e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.13470581474698689445958562292807701026370826971490e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.32481553840568432886657947564022812389544240910245e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72079249234488105623103527050493983216840056389979e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25993583492605042781181768463472827114252734385354e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90139785097711606987697985776461422964227374409867e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61772178749879746562419160426660201168856327635754e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85568203412051586615998003517909621954036193765824e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.04563780918059698346140819518179336362098891429611e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.91792339891869109849236922708731694322153177924824e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57638176923363231335450711092364627257129748508825e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78661356398095539721893167504764083609118624639856e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.92604459926540711296353370623384343787650705186643e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70807462044367666228538283653300633948804226008283e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53938313936621297172285881159282265471330118114236e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72126969520581558576219170420297785383800313247716e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.81057004571925961169117504945825287978291651680376e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.50396638201843310535816082381660912483279969324341e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50330305081854272655464104542050109297998338121296e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65748943908780839905864199570025333227786061957216e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.69782199924985143903444545973473854205301886566784e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.30465447555059221873312238790689561215989143051468e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46806937341565301230797169380667244412810953871153e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.59520452276585659227559942516968833301265805493281e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58771679139660099100514647692148711295768774585921e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.11001413331373018059574227843565648889473010676660e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43366149729083958029796238740037446793377590904146e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.53437941664766678806680232945039585344994407777604e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48019217902582750507529988918628139079404963189635e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.91993567701892984811136675864172386794777828712695e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40006005594525679129869441468227938628239752074460e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.47497989906821913751146663525981445654490373951224e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.73431218458810807033921781897016124929992555367139e-27), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.41697255768378077454412606000376285104775580444420e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55303924276181374957661287953452523234530316565188e-30), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36032476336306675100543445227730858361169873925804e-31), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37601488550958357902586661939110889053699438042016e-33), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30500465172174486774768816059192932509423715417166e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20313953663045271143891020576861031160487434865093e-36), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25098110519701647231401040429952006498171313622520e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03431595374067647597712273413788666502302011992057e-39), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19822373554396139874268836303925702273981755123190e-40), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.86944917357487937107083766130282172728072819621788e-42), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14670286674214980345963428973545770896346187182759e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.70844645856921813581135618689921390269372237700480e-45), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09638951830288066744104877057303202280205793138993e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55121724469650208575327739326222025805731763269349e-48), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04725538896765690179789918481715848637732139291593e-49), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.99927284078872744316201092259372825667966088624440e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95241488358274164371290129159422806319923560612665e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90665515974877113643838016757246988460215123083510e-58), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86196792944215931292810563239498984002947733280447e-61), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.81832805609585870403135315663573226135611325562940e-64), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77571099228111201565561831702708228641500206234884e-67), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73409276589952345278868976272176004532614982149466e-70), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69344996669875337186395484640796879426380291665101e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65375973310425133971089340469528202564824480281467e-76), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61499973935962044893641934052273635317211406169375e-79), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57714818296837934466447201222923471989464263831856e-82), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54018377243005795377389844944261203114711195148214e-85), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50408571526372847048232270453380081166710151511926e-88), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46883370631223483445539326614628985514365382335866e-91), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43440791632054183052284498647098618666372443687369e-94), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40078898078177913136996580710057244791379339538446e-97), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_cdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.05754562114095147060025732340404110273918791128410e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.43368449353064312968788810247763526151579823896375e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.89152652981222928500336992235218785823347685619486e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.45576815036790322986175114501424442292398775002753e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.15978035591850473786135203626730317231876547935253e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.04840867577215219812315602202859291564396444891271e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.18107352643844092577238041212187564083206726822056e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.63452659158632535349648745626466375370661702427253e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05039829654829170780787685299557006719608839147146e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16290125976286647650587923507379034571826555851855e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.29006094814340314434551699445775276932192677014796e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43337488600334723245402521343673257218591019586678e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.59428804524998597404889957316726146572475641692056e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77411943695232738645173996334900914289694617802622e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97397674713122675501528813572074060920189377220435e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19466281873758062089629668872911218009781881016957e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43657975600729535499895880792984203156689462603233e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56549331000915958092357114949075709547374035120716e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69963821328456787766164921360924665804748003656962e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83891389704828738280543932012082190429368746897774e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98318069008956501931929973721256792184639224594009e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13225883262651243874304479279543149837428487068880e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.28592804901375835801811223649103787689862120396348e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44392772657854742558827130471487286937515502098876e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.60595773518728397925852903878144782668636743128847e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.77167990746831553875195022302050315427406387091454e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.94072018335986771952143399033763464047462959349960e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.11267140533666880513239944176560287064005137544504e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.28709673289702231328042170648699212093305785288837e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.46353362731996489993314637378816744341919505345430e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64149834100915287958166424201293669944118353975980e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.82049083059559169016945833205795772857456974521089e-1), tolerance);
+    BOOST_CHECK_EQUAL(cdf(dist, static_cast<RealType>(0)), static_cast<RealType>(0.5));
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.17950916940440830983054166794204227142543025478911e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.35850165899084712041833575798706330055881646024020e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53646637268003510006685362621183255658080494654570e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.71290326710297768671957829351300787906694214711163e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.88732859466333119486760055823439712935994862455496e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.05927981664013228047856600966236535952537040650040e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.22832009253168446124804977697949684572593612908546e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.39404226481271602074147096121855217331363256871153e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55607227342145257441172869528512713062484497901124e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.71407195098624164198188776350896212310137879603652e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.86774116737348756125695520720456850162571512931120e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.01681930991043498068070026278743207815360775405991e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.16108610295171261719456067987917809570631253102226e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.30036178671543212233835078639075334195251996343038e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43450668999084041907642885050924290452625964879284e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.56342024399270464500104119207015796843310537396767e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.80533718126241937910370331127088781990218118983044e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.02602325286877324498471186427925939079810622779565e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.22588056304767261354826003665099085710305382197378e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40571195475001402595110042683273853427524358307944e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.56662511399665276754597478656326742781408980413322e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70993905185659685565448300554224723067807322985204e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.83709874023713352349412076492620965428173444148145e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94960170345170829219212314700442993280391160852854e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.13654734084136746465035125437353362462933829757275e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.28189264735615590742276195878781243591679327317794e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.39515913242278478018768439779714070843560355510873e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.48402196440814952621386479637326968276812345206475e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.55442318496320967701382488549857555770760122499725e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.61084734701877707149966300776478121417665231438051e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.65663155064693568703121118975223647384842017610363e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.69424543788590485293997426765959588972608120887159e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.75181239051510561995724918481437181225561682663730e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.79330912859883809209439632732487322514831404016950e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.82433333964997258238374422700352745232108521574338e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.84823776850456273960749947374965581355459282720918e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.86712078422837181984231917376692653955733800370589e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.88234978933381804514525314568892574021644736001062e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.89484817977790488434819448808352507951600536883956e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.90525915297517643347206332876433307912297417265919e-1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_ccdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94960170345170829219212314700442993280391160852854e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.83709874023713352349412076492620965428173444148145e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70993905185659685565448300554224723067807322985204e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.56662511399665276754597478656326742781408980413322e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40571195475001402595110042683273853427524358307944e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.22588056304767261354826003665099085710305382197378e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.02602325286877324498471186427925939079810622779565e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.80533718126241937910370331127088781990218118983044e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.56342024399270464500104119207015796843310537396767e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43450668999084041907642885050924290452625964879284e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.30036178671543212233835078639075334195251996343038e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.16108610295171261719456067987917809570631253102226e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.01681930991043498068070026278743207815360775405991e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.86774116737348756125695520720456850162571512931120e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.71407195098624164198188776350896212310137879603652e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55607227342145257441172869528512713062484497901124e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.39404226481271602074147096121855217331363256871153e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.22832009253168446124804977697949684572593612908546e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.05927981664013228047856600966236535952537040650040e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.88732859466333119486760055823439712935994862455496e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.71290326710297768671957829351300787906694214711163e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53646637268003510006685362621183255658080494654570e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.35850165899084712041833575798706330055881646024020e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.17950916940440830983054166794204227142543025478911e-1), tolerance);
+    BOOST_CHECK_EQUAL(cdf(complement(dist, static_cast<RealType>(0))), static_cast<RealType>(0.5));
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.82049083059559169016945833205795772857456974521089e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64149834100915287958166424201293669944118353975980e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.46353362731996489993314637378816744341919505345430e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.28709673289702231328042170648699212093305785288837e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.11267140533666880513239944176560287064005137544504e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.94072018335986771952143399033763464047462959349960e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.77167990746831553875195022302050315427406387091454e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.60595773518728397925852903878144782668636743128847e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44392772657854742558827130471487286937515502098876e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.28592804901375835801811223649103787689862120396348e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13225883262651243874304479279543149837428487068880e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98318069008956501931929973721256792184639224594009e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83891389704828738280543932012082190429368746897774e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69963821328456787766164921360924665804748003656962e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56549331000915958092357114949075709547374035120716e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43657975600729535499895880792984203156689462603233e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19466281873758062089629668872911218009781881016957e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97397674713122675501528813572074060920189377220435e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77411943695232738645173996334900914289694617802622e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.59428804524998597404889957316726146572475641692056e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43337488600334723245402521343673257218591019586678e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.29006094814340314434551699445775276932192677014796e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16290125976286647650587923507379034571826555851855e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05039829654829170780787685299557006719608839147146e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.63452659158632535349648745626466375370661702427253e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.18107352643844092577238041212187564083206726822056e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.04840867577215219812315602202859291564396444891271e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.15978035591850473786135203626730317231876547935253e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.45576815036790322986175114501424442292398775002753e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.89152652981222928500336992235218785823347685619486e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.43368449353064312968788810247763526151579823896375e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.05754562114095147060025732340404110273918791128410e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.48187609484894380042750815185628187744383173362701e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06690871401161907905603672675126774851685959830498e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.75666660350027417616255772996472547678914784256620e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51762231495437260392500526250344186445407172790817e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.32879215771628180157680826233073460442661996294112e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.17650210666181954854746854311074259783552639989383e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05151820222095115651805511916474920483994631160437e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.47408470248235665279366712356669208770258273408139e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.84633233633455623701916449563937321750458546930453e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63980919776847052871529866313101745651230650390958e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.71560271091813267790502831701953317735310509411390e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.98877952779840995427042841099634486251917561421235e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.40474538743684446341559852404247422921805516802754e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.92694975034713587589009244180464471384939103569360e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.53008216069181937774819568728358865566934398876406e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.19610991747326725339429696634365931201323237447865e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66754697245984312281273324441306444625571550964874e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.27055303995134836245432119316955904009319977641407e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96335385591609284864855802297989450933958012331026e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.71983068404058084817697571696065106175519154567134e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52289416073896095009461377823763903270627907120760e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36093802515022944719982175339249822123873546752029e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22583027731897389283291308558313649709444449306352e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.11172037056341396583040940446061500559620114648017e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.30343276748924876383449972567328892540120922780153e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.93479451609843506274951848311637162210971363421001e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.87195324030611990483144403072151789810819131065125e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.02706331251660616582062908165140543120249377843861e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.34227281260431186934023112980425214646324423530835e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.77808682390572890160969127059116197868923042197157e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.30671561098656496307105837586195479010992455366704e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90809577465797739887717333706777298095814323854594e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.27353325758395877256315285908308787899438871193344e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79392283157821028307612118603031347679870090601645e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42100764912263851750335808792156725434230560510519e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.12427366298380215713674931256380175628765437052256e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.88357904993849478063900853297202135211787374336745e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68514784935653217641685603828708555083243580835252e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51927236784831507287987712585213807190192778503378e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37893523202524132194116984313653211252949573780743e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87179879353850251536193247663317269917137569329013e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72200715673082274403568012456413425331659480927047e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08767256634253255597053159005214917567906016620942e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15224951834965340756402503731619739933629215689572e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60926645137475638433041259135060814007792759468100e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69027136710097153757239920401079588116557633592788e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51153240121827639330112195094153363441740650435701e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36283287602527689849064009106938913094716520594050e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894075854698171408179022464997418218329601220535e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.20354010552543796231728241342645692784842686349965e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617582449547816069323420820736862370145659607645e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25442497729649541267939242007563203416972765165476e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771976129306035185873711236944017216967773980517e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56803119746276025902637885330726865801883592203156e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969859659307190062902673645385449168267230206e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.21003899305378486738410997502574389330326609057126e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90268712277390815798081242324390081166198190434103e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02625487407274396069298698869802596448489279633645e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890339366126281650716118851052269284048205938e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28281859258171445903392888079435183340041265714998e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53544862923055721373031196622890601888700626111182e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60352324072570315319362346398633880353985161880622e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653639661641440656550426788294070266782671e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00440405090690395389846895694672344247801107283103e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08663848317021453602605776312368607691806298813143e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396272422714320494875293186097734524880995e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728726299533984178525425523566315206520781873938e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417469494912307476988489629927133322828e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013634843021835192352185216943643167993641440545e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293728520200407227686276581114275508e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333804442221617119725245647479628568092558840977e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917255552777021393262025049731570198920941773050e-22), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396569440971276740578385685661655637545268535833e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995711801214095925566865602936005935821644314758e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994639751517619906934188799897966230541134026964e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993299689397024883663924561783076352358304956329e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162461174628110457931016502737959110130110786e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905203076468285138072404465359649544991622324619e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503845585356422590504127751316165005771606733e-28), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379806981695528238129932509731805283190086691e-29), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974758727119410297662380140381412701796292469e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460560511124078590097461169759773383672872924e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907125798631372797027282887330061342582520339e-34), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604884060361519995355129506804305208883665969e-36), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013134431487499274238985426822797191535889e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198458022549199217615998414729133523646527342e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590660233123777524997523014264365635070860e-41), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797906614255902382808629709787906142136400e-43), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809229084774847473138483921543599314796577e-45), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220192044496069917677888112741187383092503e-46), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550069525109246371700176158105285841693e-48), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609483632983197455781525247039509121778e-50), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327318176536246024658633198499233002634e-52), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636434650837884413529114372655051566613e-54), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442914193419439613924120727351807283e-55), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254553427217874396756438636487198880e-57), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522739730027928744931935369511248250e-59), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 600))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.35984768491636685338723260976696756010081951066709e-272), tolerance);
+
+    // The test is terminated because x is inf after this in fp64.
+    if (N <= 53) {
+        return;
+    }
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 10000))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.07856314267954244808378917796336533616174400834444e-4517), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_quantile_nearzero() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 4;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.95154561868642736172727541497862573947423988108440e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.70076903638473389271107254016757513871156973570753e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.14334937403136202998120100318789158621074793095204e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.78777320599109327486003359289950832456660816353247e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.52359744792606448551215814625237535910408488746319e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.31030403921397562363480619469818801698833367088973e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.12887694529692805365864437467349833307816315605127e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.68933181713583005208786313049614919507807226788256e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.24180933056718074475811972779037648260058221511975e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.90498457639035315478919560434827057700411821656397e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.65011034985136468564856594364133703131867596374603e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.45602574935161564367593993713685007358536186330925e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.30636223130194458226267853223267146033119688836326e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.18783126811804488668597304309230757418655445388316e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.08910089454817618171205461377219663239656206354005e-1), tolerance);
+    BOOST_CHECK_EQUAL(quantile(dist, static_cast<RealType>(0.5)), static_cast<RealType>(0));
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.50390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.35942281074760935023421465350943213907657016740203e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.71903117534558589826852519194663375075753566669865e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.51171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.07901080568320221484687881885423066805647774437405e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.43954773006081419776089446583406196027634755818438e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.51953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.80082845222988104915780076816665811376325257794804e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.16304011143799846843111212111260495740955724460844e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.52734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.52637064382003902226333974540096053392566128735022e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08910089454817618171205461377219663239656206354005e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22571450376289000001278843371459783620761964026442e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36249702341028008589045826702986410397012912904709e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.54296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49946773116932301309732751744953722231029126346486e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.63664606836100199300226165836560082654887238338208e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.55078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77405165765079089783419383641965337744707947259452e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.91170432114732759551367174850419509782585472590891e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.55859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04962409893975946705863512977926741730110899605668e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18783126811804488668597304309230757418655445388316e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.56640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32634636232249536218129854873203382200612639970098e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46519019187105731139818680492599864661432850376167e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.57421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.60438386451527503677057942069112096470660708202704e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.74394880687856404334281468719091417527159191461011e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.58203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.88390678663337502806483517706706303095739191330472e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.02427993547706435128366410334899635275725704584021e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.58984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.16509077296982960387421259319514641259915543447926e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.30636223130194458226267853223267146033119688836326e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44811768106176498805637646337817923388445968601566e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.59038095808060603000739360761949422570819209911788e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.60546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.73317639143565086527888233910690716885943557654200e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.87652883269757340156275635385373789172745768932299e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.61328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.02046368651559365036792703758158149784555601527522e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.16500694263927667044145946879116606537710528519644e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.62109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.31018520948359067342384024222999190532594772267877e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.45602574935161564367593993713685007358536186330925e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.62890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.60255651543790720669175415204007861250418903243190e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74980619074494545171846930824082767773201407564280e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.63671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.89780422905541754178666731200120149076546958331875e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.04658089811438846102378009478135229217539543328542e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.64453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19616732518780928821098759267869073306168616762584e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.34659554517741239172052324381351337830662490680744e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.49789855148697728320168560667825948269915149112198e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.65011034985136468564856594364133703131867596374603e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.66015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80326601535777269419392897717286438879602729753825e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.95740175290855108336930680485963056005472680796594e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.66796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.11255496139682430686772264889247897534154814090188e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.26876430189035334589546274389116075758343949758676e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.67578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.42606977014577414303134971466049624688623181490963e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.58451277380488310882288163359470075488686595989134e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.68359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.74413621465733462219129425896964561569492923310844e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.90498457639035315478919560434827057700411821656397e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.69140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.06710401828627699619029762829527775785025847826609e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.23054247537343446268743874344186034038860806575417e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.69921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.39534976558556849766533672421653104101284193327489e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.56157770454041251979362066603791706893576777672076e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.70703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.72928022860981170501224651695596294779402544635284e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.89851352702281826568041708053406482267060399077072e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.06933618382042868991732981731903327683778049211437e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24180933056718074475811972779037648260058221511975e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.72265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.41599681082196095188647911444502703373377770261645e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.59196535747955714353182241432999465132648793939716e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.73046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.76978478421742214185140384463517803619244579498785e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94952819242075830879661206434669971092120406861116e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.73828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.13127219511566873406119301005062170096048576202346e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.31509715961740080067603245114697688184732500932588e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.74609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.50108747080172235764142816696014524944397797022118e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.68933181713583005208786313049614919507807226788256e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.87992350186512083533727177758662092012850600324604e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.00729607820486228792863859054788768644744365249151e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.76171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02685472384747190194216544893563951741322238866541e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04667921798768908218602656800798525125137666299761e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.76953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06678110853147091220341113291781102477507787382916e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08717260890978562986849760571609969494354300822263e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.77734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10786665132220733188524032283620543957825067010411e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12887694529692805365864437467349833307816315605127e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.15021804221161134460394215947401773984635551400974e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.17190540651154074066537741066806130017312231661434e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.79296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.19395549446874295273954813640902172894636549828066e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21638584145104788446634880619086527181141939030279e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.80078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23921515881685008719278461299232510042094064507963e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.26246344172387198181843263481470665031951188807903e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.80859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28615208934364044613153187689263023500565577152964e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31030403921397562363480619469818801698833367088973e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.81640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.33494391774730388327762461486718746182135887404098e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.36009820925261741664314298719135880075160309673291e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.82421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38579544623528308147561770378298998291069435447743e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41206642422644329402039008236727065491131379281346e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.83203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43894444498096320102061428365633543440558564852878e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46646559259303986239248263261753112540493595538180e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.83984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49466904794112146248736006028509653369456653722975e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52359744792606448551215814625237535910408488746319e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55329729725622722446696215102952397443200898053734e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58381944212178952767489242020964875845531372433107e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.85546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61521961706725528436767664289542667668084392814972e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64755907881888895242774154629775987069182281943649e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.86328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68090534388763421593277486421165006597881155937148e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.71533305062559095290467926282068904086311880655794e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.87109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.75092497130127405520149304919663885139873951807268e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78777320599109327486003359289950832456660816353247e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.87890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.82598059808698758538443295349421685195378444570311e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86566242157090907181680189290396765394233286379846e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.88671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90694840369852884963353039612138690706293500611801e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94998516446439884497123835171451955479771823102329e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.89453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.99493917772297054805704471816059443529057908424094e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04200039028200656353168185848438653746136511354273e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09138667776446768039690693058064390661207192288310e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14334937403136202998120100318789158621074793095204e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.91015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19818019103302928413100774795456740418726081571239e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25621995785515543565780905111478616154698242356459e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.91796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31786976613802108820384089261971867032207069978249e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.38360533647314959687029290315016585988822268727435e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.92578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.45399575188877505107943151191453137828469465461499e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.52972819582716132188558325053476431645151134471514e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.93359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.61164107343000684767083444817632028828927968917161e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70076903638473389271107254016757513871156973570753e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.94140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79840522818853957979403024307775647164832128717134e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90618896524175502682103322803168945370341377670787e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.94921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.02623187745561328365781914812219941666139382669240e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.16130376436882129187002225210296787778679380216571e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.95703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.31511403805596290718635028471440503099806209998330e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.49275168669289561003117954123304779848451307206373e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.70139933971958385705119882168933347231988022896107e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.95154561868642736172727541497862573947423988108440e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.97265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.25916037511354144395537844168672288266598351274466e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64987772024289138285743520182808805983174934278635e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.98046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.16779337095862086311250586064141028622224308218889e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.89632696959562976212621758577393939287586784169403e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.98828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.01689760146742972661016754806402368873114241071209e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.02446937207505244639190533898754565373763855739835e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.99609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40479269149807902190125365288201718857308359786880e1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_quantile_lower() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.78777320599109327486003359289950832456660816353247e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.70076903638473389271107254016757513871156973570753e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.95154561868642736172727541497862573947423988108440e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.89632696959562976212621758577393939287586784169403e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.02446937207505244639190533898754565373763855739835e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.40479269149807902190125365288201718857308359786880e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.48634712845212854436829850825868101882854019691874e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.75100888665534247471443047755794084714498529274899e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.20296704598194178128278789813687898595549252840676e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -16)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.54977454632239578277064855837334284482347724412824e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -20)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.52361836255645260708087122768062244544827526253646e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -24)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.23734752970824778029419146983721335265273533376700e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -28)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.42062670553125367339285994800008811139726501576815e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -32)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.02041713923935805934169232925253585383521252378005e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -40)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.63680429392084153704899843149763443252941653727485e7), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -48)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.46626761095577290791010108814328116732395911944180e9), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -56)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.91162056903107188819131273099660458893079363542047e10), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -64)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.38341606205240162091324729036756554251581053237655e12), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -80)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.87423965612020298589373786039770640757408383939246e15), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -96)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.29757143623897661671305188560924841842505858740001e18), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -112)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.02366940392761715971201478542352832996294475084257e22), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -128)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.66397326199025580692950800332626492430331068544172e25), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -160)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.39662661178492965217151228166250717006976010266469e31), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.16169688570203891305395889425358741905195655516409e38), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -224)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.06948889094299024072567114732250581789838857797378e44), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.11034458952573565292573972403491751744218292992004e50), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.11034458952573565292573972403491751744218292992004e50), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -320)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.66220760083199094068657639449976729910923748932480e63), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -384)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.95304965911372717286692649124348058110571556299024e76), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -448)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.75980725346824443030445016705237404631255977139835e89), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -512)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.92674940440883821350824836233864795634501852860731e102), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -640)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.39113744455748572074441450789762236967081046313794e127), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -768)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.57731878887639063343639480262468437174058078877170e153), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -896)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.23102338973254024994084948896750440849135610207358e179), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_quantile_upper() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78777320599109327486003359289950832456660816353247e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70076903638473389271107254016757513871156973570753e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.95154561868642736172727541497862573947423988108440e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.89632696959562976212621758577393939287586784169403e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.02446937207505244639190533898754565373763855739835e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40479269149807902190125365288201718857308359786880e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.48634712845212854436829850825868101882854019691874e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.75100888665534247471443047755794084714498529274899e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20296704598194178128278789813687898595549252840676e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.54977454632239578277064855837334284482347724412824e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.52361836255645260708087122768062244544827526253646e3), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_holtsmark_locscale_param() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    holtsmark_distribution<RealType> dist_0_1(static_cast<RealType>(0), static_cast<RealType>(1));
+    holtsmark_distribution<RealType> dist_1_3(static_cast<RealType>(1), static_cast<RealType>(3));
+
+    BOOST_CHECK_CLOSE(entropy(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.0694485051346244003155800384542166381), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_1_3), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.0694485051346244003155800384542166381) + log(static_cast<RealType>(3)), tolerance);
+
+    BOOST_CHECK_EQUAL(median(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(median(dist_1_3), static_cast<RealType>(1));
+
+    BOOST_CHECK_EQUAL(mode(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(mode(dist_1_3), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02038159607840130388931544845552929991729709746772e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.87352751452164445024482162286994868261727837966217e-1) / 3, tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94960170345170829219212314700442993280391160852854e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94960170345170829219212314700442993280391160852854e-1), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp64)
+{
+    do_test_holtsmark_pdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp128)
+{
+    do_test_holtsmark_pdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
+{
+    do_test_holtsmark_cdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp128)
+{
+    do_test_holtsmark_cdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
+{
+    do_test_holtsmark_ccdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp128)
+{
+    do_test_holtsmark_ccdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
+{
+    do_test_holtsmark_quantile_nearzero<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp128)
+{
+    do_test_holtsmark_quantile_nearzero<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
+{
+    do_test_holtsmark_quantile_lower<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp128)
+{
+    do_test_holtsmark_quantile_lower<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
+{
+    do_test_holtsmark_quantile_upper<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp128)
+{
+    do_test_holtsmark_quantile_upper<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
+{
+    do_test_holtsmark_locscale_param<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp128)
+{
+    do_test_holtsmark_locscale_param<cpp_bin_float_quad, 113>();
+}

From 0d0ff9493ce17309328a427ab6125889c7d4a1ea Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 16:44:22 +0900
Subject: [PATCH 003/399] Add saspoint5 distribution

---
 .../boost/math/distributions/saspoint5.hpp    | 2742 +++++++++++++++++
 test/test_saspoint5.cpp                       |  878 ++++++
 2 files changed, 3620 insertions(+)
 create mode 100644 include/boost/math/distributions/saspoint5.hpp
 create mode 100644 test/test_saspoint5.cpp

diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
new file mode 100644
index 0000000000..231b8f4939
--- /dev/null
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -0,0 +1,2742 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_STATS_SASPOINT5_HPP
+#define BOOST_STATS_SASPOINT5_HPP
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable : 4127) // conditional expression is constant
+#endif
+
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/distributions/complement.hpp>
+#include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <utility>
+#include <cmath>
+
+namespace boost { namespace math {
+template <class RealType, class Policy>
+class saspoint5_distribution;
+
+namespace detail {
+
+template <class RealType>
+inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.125) {
+        // Rational Approximation
+        // Maximum Relative Error: 7.8747e-17
+        static const RealType P[13] = {
+            static_cast<RealType>(6.36619772367581343076e-1),
+            static_cast<RealType>(2.17275699713513462507e2),
+            static_cast<RealType>(3.49063163361344578910e4),
+            static_cast<RealType>(3.40332906932698464252e6),
+            static_cast<RealType>(2.19485577044357440949e8),
+            static_cast<RealType>(9.66086435948730562464e9),
+            static_cast<RealType>(2.90571833690383003932e11),
+            static_cast<RealType>(5.83089315593106044683e12),
+            static_cast<RealType>(7.37911022713775715766e13),
+            static_cast<RealType>(5.26757196603002476852e14),
+            static_cast<RealType>(1.75780353683063527570e15),
+            static_cast<RealType>(1.85883041942144306222e15),
+            static_cast<RealType>(4.19828222275972713819e14),
+        };
+        static const RealType Q[15] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.41295871011779138155e2),
+            static_cast<RealType>(5.48907134827349102297e4),
+            static_cast<RealType>(5.36641455324410261980e6),
+            static_cast<RealType>(3.48045461004960397915e8),
+            static_cast<RealType>(1.54920747349701741537e10),
+            static_cast<RealType>(4.76490595358644532404e11),
+            static_cast<RealType>(1.00104823128402735005e13),
+            static_cast<RealType>(1.39703522470411802507e14),
+            static_cast<RealType>(1.23724881334160220266e15),
+            static_cast<RealType>(6.47437580921138359461e15),
+            static_cast<RealType>(1.77627318260037604066e16),
+            static_cast<RealType>(2.04792815832538146160e16),
+            static_cast<RealType>(7.45102534638640681964e15),
+            static_cast<RealType>(3.68496090049571174527e14),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 0.25) {
+        RealType t = x - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.1471e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(4.35668401768623200524e-1),
+            static_cast<RealType>(7.12477357389655327116e0),
+            static_cast<RealType>(4.02466317948738993787e1),
+            static_cast<RealType>(9.04888497628205955839e1),
+            static_cast<RealType>(7.56175387288619211460e1),
+            static_cast<RealType>(1.26950253999694502457e1),
+            static_cast<RealType>(-6.59304802132933325219e-1),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.98623818041545101115e1),
+            static_cast<RealType>(1.52856383017632616759e2),
+            static_cast<RealType>(5.70706902111659740041e2),
+            static_cast<RealType>(1.06454927680197927878e3),
+            static_cast<RealType>(9.13160352749764887791e2),
+            static_cast<RealType>(2.58872466837209126618e2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 0.5) {
+        RealType t = x - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.3265e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(2.95645445681747568732e-1),
+            static_cast<RealType>(2.23779537590791610124e0),
+            static_cast<RealType>(5.01302198171248036052e0),
+            static_cast<RealType>(2.76363131116340641935e0),
+            static_cast<RealType>(1.18134858311074670327e-1),
+            static_cast<RealType>(2.00287083462139382715e-2),
+            static_cast<RealType>(-7.53979800555375661516e-3),
+            static_cast<RealType>(1.37294648777729527395e-3),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.02879626214781666701e1),
+            static_cast<RealType>(3.85125274509784615691e1),
+            static_cast<RealType>(6.18474367367800231625e1),
+            static_cast<RealType>(3.77100050087302476029e1),
+            static_cast<RealType>(5.41866360740066443656e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.7947e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.70762401725206223811e-1),
+            static_cast<RealType>(8.43343631021918972436e-1),
+            static_cast<RealType>(1.39703819152564365627e0),
+            static_cast<RealType>(8.75843324574692085009e-1),
+            static_cast<RealType>(1.86199552443747562584e-1),
+            static_cast<RealType>(7.35858280181579907616e-3),
+            static_cast<RealType>(-1.03693607694266081126e-4),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.73363440952557318819e0),
+            static_cast<RealType>(1.74288966619209299976e1),
+            static_cast<RealType>(2.15943268035083671893e1),
+            static_cast<RealType>(1.29818726981381859879e1),
+            static_cast<RealType>(3.40707211426946022041e0),
+            static_cast<RealType>(2.80229012541729457678e-1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.7051e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(8.61071469126041183247e-2),
+            static_cast<RealType>(1.69689585946245345838e-1),
+            static_cast<RealType>(1.09494833291892212033e-1),
+            static_cast<RealType>(2.76619622453130604637e-2),
+            static_cast<RealType>(2.44972748006913061509e-3),
+            static_cast<RealType>(4.09853605772288438003e-5),
+            static_cast<RealType>(-2.63561415158954865283e-7),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.04082856018856244947e0),
+            static_cast<RealType>(3.52558663323956252986e0),
+            static_cast<RealType>(1.94795523079701426332e0),
+            static_cast<RealType>(5.23956733400745421623e-1),
+            static_cast<RealType>(6.19453597593998871667e-2),
+            static_cast<RealType>(2.31061984192347753499e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.9247e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(3.91428580496513429479e-2),
+            static_cast<RealType>(4.07162484034780126757e-2),
+            static_cast<RealType>(1.43342733342753081931e-2),
+            static_cast<RealType>(2.01622178115394696215e-3),
+            static_cast<RealType>(1.00648013467757737201e-4),
+            static_cast<RealType>(9.51545046750892356441e-7),
+            static_cast<RealType>(-3.56598940936439037087e-9),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.63904431617187026619e0),
+            static_cast<RealType>(1.03812003196677309121e0),
+            static_cast<RealType>(3.18144310790210668797e-1),
+            static_cast<RealType>(4.81930155615666517263e-2),
+            static_cast<RealType>(3.25435391589941361778e-3),
+            static_cast<RealType>(7.01626957128181647457e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.6547e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.65057384221262866484e-2),
+            static_cast<RealType>(8.05429762031495873704e-3),
+            static_cast<RealType>(1.35249234647852784985e-3),
+            static_cast<RealType>(9.18685252682786794440e-5),
+            static_cast<RealType>(2.23447790937806602674e-6),
+            static_cast<RealType>(1.03176916111395079569e-8),
+            static_cast<RealType>(-1.94913182592441292094e-11),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.10113554189626079232e-1),
+            static_cast<RealType>(2.54175325409968367580e-1),
+            static_cast<RealType>(3.87119072807894983910e-2),
+            static_cast<RealType>(2.92520770162792443587e-3),
+            static_cast<RealType>(9.89094130526684467420e-5),
+            static_cast<RealType>(1.07148513311070719488e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.5484e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(6.60044810497290557553e-3),
+            static_cast<RealType>(1.59342644994950292031e-3),
+            static_cast<RealType>(1.32429706922966110874e-4),
+            static_cast<RealType>(4.45378136978435909660e-6),
+            static_cast<RealType>(5.36409958111394628239e-8),
+            static_cast<RealType>(1.22293787679910067873e-10),
+            static_cast<RealType>(-1.16300443044165216564e-13),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.10446485803039594111e-1),
+            static_cast<RealType>(6.51887342399859289520e-2),
+            static_cast<RealType>(5.02151225308643905366e-3),
+            static_cast<RealType>(1.91741179639551137839e-4),
+            static_cast<RealType>(3.27316600311598190022e-6),
+            static_cast<RealType>(1.78840301213102212857e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.9866e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(2.54339461777955741686e-3),
+            static_cast<RealType>(3.10069525357852579756e-4),
+            static_cast<RealType>(1.30082682796085732756e-5),
+            static_cast<RealType>(2.20715868479255585050e-7),
+            static_cast<RealType>(1.33996659756026452288e-9),
+            static_cast<RealType>(1.53505360463827994365e-12),
+            static_cast<RealType>(-7.42649416356965421308e-16),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.09203384450859785642e-1),
+            static_cast<RealType>(1.69422626897631306130e-2),
+            static_cast<RealType>(6.65649059670689720386e-4),
+            static_cast<RealType>(1.29654785666009849481e-5),
+            static_cast<RealType>(1.12886139474560969619e-7),
+            static_cast<RealType>(3.14420104899170413840e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.3581e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(9.55085695067883584460e-4),
+            static_cast<RealType>(5.86125496733202756668e-5),
+            static_cast<RealType>(1.23753971325810931282e-6),
+            static_cast<RealType>(1.05643819745933041408e-8),
+            static_cast<RealType>(3.22502949410095015524e-11),
+            static_cast<RealType>(1.85366144680157942079e-14),
+            static_cast<RealType>(-4.53975807317403152058e-18),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.05980850386474826374e-1),
+            static_cast<RealType>(4.34966042652000070674e-3),
+            static_cast<RealType>(8.66341538387446465700e-5),
+            static_cast<RealType>(8.55608082202236124363e-7),
+            static_cast<RealType>(3.77719968378509293354e-9),
+            static_cast<RealType>(5.33287361559571716670e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.7450e-19
+        static const RealType P[5] = {
+            static_cast<RealType>(1.99471140200716338970e-1),
+            static_cast<RealType>(-1.93310094131437487158e-2),
+            static_cast<RealType>(-8.44282614309073196195e-3),
+            static_cast<RealType>(3.47296024282356038069e-3),
+            static_cast<RealType>(-4.05398011689821941383e-4),
+        };
+        static const RealType Q[5] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.00973251258577238892e-1),
+            static_cast<RealType>(2.66969681258835723157e-1),
+            static_cast<RealType>(5.51785147503612200456e-2),
+            static_cast<RealType>(6.50130030979966274341e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.0625) {
+        // Rational Approximation
+        // Maximum Relative Error: 8.8841e-35
+        static const RealType P[27] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581343075535053490057448138e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.57459506929453385798277946154823008327e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46717322844023441698710451505816706570e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71501459971530549476153273173061194095e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76700973495278431084530045707075552432e10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01328150775099946510145440412520620021e13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70028222513668830210058353057559790101e15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29641781943744384078006991488193839955e17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52611994112742436432957758588495082163e19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27833177267552931459542318826727288124e21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68946162731840551853993619351896931533e23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02965010233956763504899745874128908220e25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.14128569264874914146628076133997950655e26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09103580386900060922163883603492216942e28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.86778299087452621293332172137014749128e29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80029712249744334924217328667885673985e31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70890080432228368476255091774238573277e32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88600513999992354909078399482884993261e33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01189178534848836605739139176681647755e34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06531475170803043941021113424602440078e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64956999370443524098457423629252855270e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44276098283517934229787916584447559248e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45856704224433991524661028965741649584e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47263237190968408624388275549716907309e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66186300951901408251743228798832386260e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48064966533519934186356663849904556319e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64877082086372991309408001661535573441e35),
+        };
+        static const RealType Q[28] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18981461118065892086304195732751798634e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01761929839041982958990681130944341399e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69465252239913021973760046507387620537e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.49221044103838155300076098325950584061e10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59327386289821190042576978177896481082e13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67528179803224728786405503232064643870e15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61672367849271591791062829736720884633e17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98395893917909208201801908435620016552e19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60025693881358827551113845076726845495e21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67730578745705562356709169493821118109e23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63843883526710042156562706339553092312e25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.23075214698024188140971761421762265880e26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37775321923937393366376907114580842429e28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12444724625354796650300159037364355605e30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00860835602766063447009568106012449767e31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.39614080159468893509273006948526469708e32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06547095715472468415058181351212520255e34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36755997709303811764051969789337337957e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32519530489892818585066019217287415587e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.45230390606834183602522256278256501404e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80344475131699029428900627020022801971e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66469314795307459840482483320814279444e38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70209065673736156218117594311801487932e38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.84490531246108754748100009460860427732e38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30215083398643966091721732133851539475e38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.58032845332990262754766784625271262271e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.50461648438613634025964361513066059697e36),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 0.125) {
+        RealType t = x - 0.0625;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.4585e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46416716200748206779925127900698754119e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41771273526123373239570033672829787791e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56142610225585235535211648703534340871e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15655694129872563686497490176725921724e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.00791883661952751945853742455643714995e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30252591667828615354689186280704562254e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76168115448224677276551213052798322583e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88534624532179841393387625270218172719e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14740447137831585842166880265350244623e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14904082614021239315925958812100948136e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76866867279164114004579652405104553404e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53475339598769347326916978463911377965e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.88896160275915786487519266368539625326e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05543800791717482823610940401201712196e4),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.44407579416524903840331499438398472639e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15911780811299460009161345260146251462e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88457596285725454686358792906273558406e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.66501639812506059997744549411633476528e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.12674134216028769532305433586266118000e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.87676063477990584593444083577765264392e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.56084282739608760299329382263598821653e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.34250986378665047914811630036201995871e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31288233106689286803200674021353188597e9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33621494302241474082474689597125896975e9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63379428046258653791600947328520263412e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14558538557562267533922961110917101850e8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 0.25) {
+        RealType t = x - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.9278e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35668401768623200524372663239480799018e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30066509937988171489091367354416214000e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05924026744937322690717755156090122074e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.12998524955326375684693500551926325112e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52237930808361186011042950178715609183e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10734809597587633852077152938985998879e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20796157836149826988172603622242119074e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12398478061053302537736799402801934778e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17841330491647012385157454335820786724e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.46281413765362795389526259057436151953e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52220357379402116641048490644093497829e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.51130316105543847380510577656570543736e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.32201781975497810173532067354797097401e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96874547436310030183519174847668703774e0),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.63164311578114868477819520857286165076e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34964379844144961683927306966955217328e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82966031793809959278519002412667883288e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56215285850856046267451500310816276675e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.81046679663412610005501878092824281161e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33868038251479411246071640628518434659e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.46262495881941625571640264458627940579e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40052628730443097561652737049917920495e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44394803828297754346261138417756941544e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.56647617803506258343236509255155360957e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53513095899009948733175317927025056561e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69130675750530663088963759279778748696e5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 0.5) {
+        RealType t = x - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.9378e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95645445681747568731488283573032414811e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.83246437763964151893665752064650172391e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85333417559435252576820440080930004674e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90974714199542064991001365628659054084e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39707205668285805800884524044738261436e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.24814598419826565698241508792385416075e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95012897118808793886195172068123345314e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87265743900139300849404272909665705025e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98795164648056126707212245325405968413e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07012128790318535418330629467906917213e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99797198893523173981812955075412130913e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55029227544167913873724286459253168886e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54064889901609722583601330171719819660e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72254289950537680833853394958874977464e-3),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58291085070053442257438623486099473087e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95618461039379226195473938654286975682e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97427161745150579714266897556974326502e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.52730436681412535198281529590508861106e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49521185356761585062135933350225236726e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03881178612341724262911142022761966061e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.02360046338629039644581819847209730553e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65580339066083507998465454599272345735e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15462499626138125314518636645472893045e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61951767959774678843021179589300545717e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60745557054877240279811529503888551492e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91061555870569579915258835459255406575e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43045229010040855016672246098687100063e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.4363e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70762401725206223811383500786268939645e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19353011456197635663058525904929358535e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22974648900600015961253465796487372402e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91951696059042324975935209295355569292e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.79039444119906169910281912009369164227e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00089963120992100860902142265631127046e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37108883429306700857182028809960789020e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49586566873564432788366931251358248417e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49790521605774884174840168128255220471e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90660338063979435668763608259382712726e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93409982383888149064797608605579930804e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22802459215932860445033185874876812040e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07739227340181463034286653569468171767e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.02669738424010290973023004028523684766e-7),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46404480283267324138113869370306506431e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.54550184643308468933661600211579108422e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63602410602063476726031476852965502123e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.94463479638213888403144706176973026333e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48607087483870766806529883069123352339e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69715692924508994524755312953665710218e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33237849965272853370191827043868842100e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.08460086451666825383009487734769646087e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.47365552394788536087148438788608689300e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38010282703940184371247559455167674975e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.67219842525655806370702248122668214685e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.01852843874982199859775136086676841910e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.14767043526088185802569803397824432028e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.1244e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.61071469126041183247373313827161939454e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35837460186564880289965856498718321896e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47783071967681246738651796742079530382e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16019502727107539284403003943433359877e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.80510046274709592896987229782879937271e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30456542768955299533391113704078540955e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36539167913428133313942008990965988621e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76450743657913389896743235938695682829e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42847090205575096649865021874905747106e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41380341540026027117735179862124402398e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.40549721587212773424211923602910622515e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09089653391032945883918434200567278139e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21403900721572475664926557233205232491e-10),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13172035933794917563324458011617112124e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65687100738157412154132860910003018338e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59672433683883998168388916533196510994e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61469557815097583209668778301921207455e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77070955301136405523492329700943077340e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.20825570431301943907348077675777546304e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60136197167727810483751794121979805142e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.53723076053642006159503073104152703814e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63397465217490984394478518334313362490e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.40577918603319523990542237990107206371e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94376458316662573143947719026985667328e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.09333568224541559157192543410988474886e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.59947287428695057506683902409023760438e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.1110e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91428580496513429479068747515164587814e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69015019070193436467106672180804948494e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03147451266231819912643754579290008651e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18825170881552297150779588545792258740e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30548850262278582401286533053286406505e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54315108501815531776138839512564427279e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.66434584176931077662201101557716482514e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.66158632576958238392567355014249971287e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31365802206301246598393821671437863818e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85378389166807263837732376845556856416e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20375363151456683883984823721339648679e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06637401794693307359898089790558771957e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08663671047376684678494625068451888284e-14),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07443397096591141329212291707948432414e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16665031056584124503224711639009530348e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27666060511630720485121299731204403783e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65646979169107732387032821262953301311e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.63594064986880863092994744424349361396e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31360114173642293100378020953197965181e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09489929949457075237756409511944811481e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24574519309785870806550506199124944514e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56048486483867679310086683710523566607e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60417286783794818094722636906776809193e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53154117367296710469692755461431646999e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60041713691072903334637560080298818163e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77381528950794767694352468734042252745e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.5228e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65057384221262866484014802392420311075e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92801687242885330588201777283015178448e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65508815862861196424333614846876229064e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71545573465295958468808641544341412235e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72077718130407940498710469661947719216e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.26299620525538984108147098966692839348e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77971404992990847565880351976461271350e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71176235845517643695464740679643640241e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64603919225244695533557520384631958897e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85274347406803894317891882905083368489e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48564096627181435612831469651920186491e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.90886715044580341917806394089282500340e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.39396206221935864416563232680283312796e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37760675743046300528308203869876086823e-22),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49023284463742780238035958819642738891e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76284367953836866133894756472541395734e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69932155343422362573146811195224195135e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.97593541520549770519034085640975455763e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45862809001322359249894968573830094537e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61348135835522976885804369721316193713e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21069949470458047530981551232427019037e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03132437580490629136144285669590192597e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91030348024641585284338958059030520141e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56320479309161046934628280237629402373e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.39524198476052364627683067034422502163e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18666081063885228839052386515073873844e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.6732e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60044810497290557552736366450372523266e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27034183360438185616541260923634443241e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19813403884333707962156711479716066536e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91346554854771687970018076643044998737e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91975837766081548424458764226669789039e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26031304514411902758114277797443618334e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.47127194811140370123712253347211626753e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55248861254135821097921903190564312000e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78340847719683652633864722047250151066e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95888612422041337572422846394029849086e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66363005792960308636467394552324255493e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93244800648299424751906591077496534948e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95046217952146113063614290717113024410e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.46784746963816915795587433372284530785e-25),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.16012189991825507132967712656930682478e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95202772611563835130347051925062280272e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23801477561401113332870463345197159418e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.54022665579711946784722766000062263305e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94266182294627770206082679848878391116e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11782839184878848480753630961211685630e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28827067686094594197542725283923947812e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.00220719177374237332018587370837457299e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42250513143925626748132661121749401409e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82007216963767723991309138907689681422e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34214834652884406013489167210936679359e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85519293212465087373898447546710143008e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.96728437809303144188312623363453475831e-19),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0113e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54339461777955741686401041938275102207e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17747085249877439037826121862689145081e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14104576580586095462211756659036062930e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06903778663262313120049231822412184382e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53115958954246158081703822428768781010e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48225007017630665357941682179157662142e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20810829523286181556951002345409843125e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.54070972719909957155251432996372246019e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06258623970363729581390609798632080752e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15603641527498625694677136504611545743e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05376970060354261667000502105893106009e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.14727542705613448694396750352455931731e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76883960167449461476228984331517762578e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.03558202009465610972808653993060437679e-29),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08809672969012756295937194823378109391e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.41148083436617376855422685448827300528e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.85101541143091590863368934606849033688e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38984899982960112626157576750593711628e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51437845497783812562009857096371643785e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.12891276596072815764119699444334380521e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82412500887161687329929693518498698716e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80215715026891688444965605768621763721e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.85838684678780184082810752634454259831e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83675729736846176693608812315852523556e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80347165008408134158968403924819637224e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23639219622240634094606955067799349447e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63446235885036169537726818244420509024e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.7056e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55085695067883584460317653567009454037e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52919532248638251721278667010429548877e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06266842295477991789450356745903177571e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.20671609948319334255323512011575892813e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04692714549374449244320605137676408001e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70605481454469287545965803970738264158e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83960996572005209177458712170004097587e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29732261733491885750067029092181853751e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.78385693918239619309147428897790440735e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52969197316398995616879018998891661712e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14063120299947677255281707434419044806e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25957675329657493245893497219459256248e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55238112862817593053765898004447484717e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.93970406521541790658675747195982964585e-34),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04722757068068234153968603374387493579e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85854131835804458353300285777969427206e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.85809281481040288085436275150792074968e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.38860750164285700051427698379841626305e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91463283601681120487987016215594255423e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28104952818420195583669572450494959042e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43912720109615655035554724090181888734e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10668954229813492117417896681856998595e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.65093571330749369067212003571435698558e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81758227619561958470583781325371429458e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36970757752002915423191164330598255294e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06487673393164724939989217811068656932e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47121057452822097779067717258050172115e-27),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.1032e-36
+        static const RealType P[8] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82846732476244747063962056024672844211e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.69724475658159099827638225237895868258e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21259630917863228526439367416146293173e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.13469812721679130825429547254346177005e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.73237434182338329541631611908947123606e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72986150007117100707304201395140411630e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53567129749337040254350979652515879881e-7),
+        };
+        static const RealType Q[9] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.89815449697874475254942178935516387239e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.21223228867921988134838870379132038419e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79514417558927397512722128659468888701e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43331254539687594239741585764730095049e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.99078779616201786316256750758748178864e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04590833634768023225748107112347131311e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.17497990182339853998751740288392648984e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53420609011698705803549938558385779137e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
+}
+
+template <class RealType>
+inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
+}
+
+template <class RealType, class Policy>
+inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x) {
+    //
+    // This calculates the pdf of the Saspoint5 distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::pdf(saspoint5<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = saspoint5_pdf_imp_prec(u, tag_type()) / scale;
+
+    return result;
+}
+
+template <class RealType>
+inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.5) {
+        // Rational Approximation
+        // Maximum Relative Error: 2.6225e-17
+        static const RealType P[16] = {
+            static_cast<RealType>(5.0e-1),
+            static_cast<RealType>(1.11530082549581486148e2),
+            static_cast<RealType>(1.18564167533523512811e4),
+            static_cast<RealType>(7.51503793077701705413e5),
+            static_cast<RealType>(3.05648233678438482191e7),
+            static_cast<RealType>(8.12176734530090957088e8),
+            static_cast<RealType>(1.39533182836234507573e10),
+            static_cast<RealType>(1.50394359286077974212e11),
+            static_cast<RealType>(9.79057903542935575811e11),
+            static_cast<RealType>(3.73800992855150140014e12),
+            static_cast<RealType>(8.12697090329432868343e12),
+            static_cast<RealType>(9.63154058643818290870e12),
+            static_cast<RealType>(5.77714904017642642181e12),
+            static_cast<RealType>(1.53321958252091815685e12),
+            static_cast<RealType>(1.36220966258718212359e11),
+            static_cast<RealType>(1.70766655065405022702e9),
+        };
+        static const RealType Q[16] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.24333404643898143947e2),
+            static_cast<RealType>(2.39984636687021023600e4),
+            static_cast<RealType>(1.53353791432086858132e6),
+            static_cast<RealType>(6.30764952479861776476e7),
+            static_cast<RealType>(1.70405769169309597488e9),
+            static_cast<RealType>(3.00381227010195289341e10),
+            static_cast<RealType>(3.37519046677507392667e11),
+            static_cast<RealType>(2.35001610518109063314e12),
+            static_cast<RealType>(9.90961948200767679416e12),
+            static_cast<RealType>(2.47066673978544828258e13),
+            static_cast<RealType>(3.51442593932882610556e13),
+            static_cast<RealType>(2.68891431106117733130e13),
+            static_cast<RealType>(9.99723484253582494535e12),
+            static_cast<RealType>(1.49190229409236772612e12),
+            static_cast<RealType>(5.68752980146893975323e10),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.2135e-19
+        static const RealType P[8] = {
+            static_cast<RealType>(3.31309550000758082456e-1),
+            static_cast<RealType>(1.63012162307622129396e0),
+            static_cast<RealType>(2.97763161467248770571e0),
+            static_cast<RealType>(2.49277948739575294031e0),
+            static_cast<RealType>(9.49619262302649586821e-1),
+            static_cast<RealType>(1.38360148984087584165e-1),
+            static_cast<RealType>(4.00812864075652334798e-3),
+            static_cast<RealType>(-4.82051978765960490940e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.43565383128046471592e0),
+            static_cast<RealType>(1.13265160672130133152e1),
+            static_cast<RealType>(1.13352316246726435292e1),
+            static_cast<RealType>(5.56671465170409694873e0),
+            static_cast<RealType>(1.21011708389501479550e0),
+            static_cast<RealType>(8.34618282872428849500e-2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.4688e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(2.71280312689343248819e-1),
+            static_cast<RealType>(7.44610837974139249205e-1),
+            static_cast<RealType>(7.17844128359406982825e-1),
+            static_cast<RealType>(2.98789060945288850507e-1),
+            static_cast<RealType>(5.22747411439102272576e-2),
+            static_cast<RealType>(3.06447984437786430265e-3),
+            static_cast<RealType>(2.60407071021044908690e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.06221257507188300824e0),
+            static_cast<RealType>(3.44827372231472308047e0),
+            static_cast<RealType>(1.78166113338930668519e0),
+            static_cast<RealType>(4.25580478492907232687e-1),
+            static_cast<RealType>(4.09983847731128510426e-2),
+            static_cast<RealType>(1.04343172183467651240e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.2289e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(2.13928162275383716645e-1),
+            static_cast<RealType>(2.35139109235828185307e-1),
+            static_cast<RealType>(9.35967515134932733243e-2),
+            static_cast<RealType>(1.64310489592753858417e-2),
+            static_cast<RealType>(1.23186728989215889119e-3),
+            static_cast<RealType>(3.13500969261032539402e-5),
+            static_cast<RealType>(1.17021346758965979212e-7),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.28212183177829510267e0),
+            static_cast<RealType>(6.17321009406850420793e-1),
+            static_cast<RealType>(1.38400318019319970893e-1),
+            static_cast<RealType>(1.44994794535896837497e-2),
+            static_cast<RealType>(6.17774446282546623636e-4),
+            static_cast<RealType>(7.00521050169239269819e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.7284e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.63772802979087193656e-1),
+            static_cast<RealType>(9.69009603942214234119e-2),
+            static_cast<RealType>(2.08261725719828138744e-2),
+            static_cast<RealType>(1.97965182693146960970e-3),
+            static_cast<RealType>(8.05499273532204276894e-5),
+            static_cast<RealType>(1.11401971145777879684e-6),
+            static_cast<RealType>(2.25932082770588727842e-9),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.92463563872865541733e-1),
+            static_cast<RealType>(1.80720987166755982366e-1),
+            static_cast<RealType>(2.20416647324531054557e-2),
+            static_cast<RealType>(1.26052070140663063778e-3),
+            static_cast<RealType>(2.93967534265875431639e-5),
+            static_cast<RealType>(1.82706995042259549615e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.9609e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(1.22610122564874280532e-1),
+            static_cast<RealType>(3.70273222121572231593e-2),
+            static_cast<RealType>(4.06083618461789591121e-3),
+            static_cast<RealType>(1.96898134215932126299e-4),
+            static_cast<RealType>(4.08421066512186972853e-6),
+            static_cast<RealType>(2.87707419853226244584e-8),
+            static_cast<RealType>(2.96850126180387702894e-11),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.55825191301363023576e-1),
+            static_cast<RealType>(4.77251766176046719729e-2),
+            static_cast<RealType>(2.99136605131226103925e-3),
+            static_cast<RealType>(8.78895785432321899939e-5),
+            static_cast<RealType>(1.05235770624006494709e-6),
+            static_cast<RealType>(3.35423877769913468556e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6559e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(9.03056141356415077080e-2),
+            static_cast<RealType>(1.37568904417652631821e-2),
+            static_cast<RealType>(7.60947271383247418831e-4),
+            static_cast<RealType>(1.86048302967560067128e-5),
+            static_cast<RealType>(1.94537860496575427218e-7),
+            static_cast<RealType>(6.90524093915996283104e-10),
+            static_cast<RealType>(3.58808434477817122371e-13),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.80501347735272292079e-1),
+            static_cast<RealType>(1.22807958286146936376e-2),
+            static_cast<RealType>(3.90421541115275676253e-4),
+            static_cast<RealType>(5.81669449234915057779e-6),
+            static_cast<RealType>(3.53005415676201803667e-8),
+            static_cast<RealType>(5.69883025435873921433e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.0653e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(6.57333571766941474226e-2),
+            static_cast<RealType>(5.02795551798163084224e-3),
+            static_cast<RealType>(1.39633616037997111325e-4),
+            static_cast<RealType>(1.71386564634533872559e-6),
+            static_cast<RealType>(8.99508156357247137439e-9),
+            static_cast<RealType>(1.60229460572297160486e-11),
+            static_cast<RealType>(4.17711709622960498456e-15),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.10198637347368265508e-2),
+            static_cast<RealType>(3.12263472357578263712e-3),
+            static_cast<RealType>(5.00524795130325614005e-5),
+            static_cast<RealType>(3.75913188747149725195e-7),
+            static_cast<RealType>(1.14970132098893394023e-9),
+            static_cast<RealType>(9.34957119271300093120e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0104e-20
+        static const RealType P[5] = {
+            static_cast<RealType>(3.98942280401432677940e-1),
+            static_cast<RealType>(8.12222388783621449146e-2),
+            static_cast<RealType>(1.68515703707271703934e-2),
+            static_cast<RealType>(2.19801627205374824460e-3),
+            static_cast<RealType>(-5.63321705854968264807e-5),
+        };
+        static const RealType Q[5] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.02536240902768558315e-1),
+            static_cast<RealType>(1.99284471400121092380e-1),
+            static_cast<RealType>(3.48012577961755452113e-2),
+            static_cast<RealType>(3.38545004473058881799e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 0.125) {
+        // Rational Approximation
+        // Maximum Relative Error: 6.9340e-35
+        static const RealType P[30] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25520067710293108163697513129883130648e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70866020657515874782126804139443323023e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.00865235319309486225795793030882782077e7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15226363537737769449645357346965170790e10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90371247243851280277289046301838071764e12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.55124590509169425751300134399513503679e14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31282020412787511681760982839078664474e16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81134278666896523873256421982740565131e18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.36154530125229747305141034242362609073e20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67793867640429875837167908549938345465e22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34584264816825205490037614178084070903e24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.52622279567059369718208827282730379468e25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84678324511679577282571711018484545185e27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99412564257799793932936828924325638617e28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08467105431111959283045453636520222779e30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87466808926544728702827204697734995611e31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55020252231174414164534905191762212055e32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69582736077420504345389671165954321163e33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18203860972249826626461130638196586188e34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32955733788770318392204091471121129386e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.97972270315674052071792562126668438695e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93941537398987201071027348577636994465e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40818708062034138095495206258366082481e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.76833406751769751643745383413977973530e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.67873467711368838525239991688791162617e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.94179310584115437584091984619858795365e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24348215908456320362232906012152922949e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71625432346533320597285660433110657670e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54662474187354179772157464533408058525e33),
+        };
+        static const RealType Q[31] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05231337496532137901354609636674085703e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43071888317491317900094470796567113997e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80864482202910830302921131771345102044e8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.32755297215862998181755216820621285536e10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.86251123527611073428156549377791985741e12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12025543961949466786297141758805461421e15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27681657695574252637426145112570596483e17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17850553865715973904162289375819555884e19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.87285897504702686250962844939736867339e20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46852796231948446334549476317560711795e22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76101689878844725930808096548998198853e24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14017776727845251567032313915953239178e26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83738954971390158348334918235614003163e27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04701345216121451992682705965658316871e29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29994190638467725374533751141434904865e30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.03334024242845994501493644478442360593e31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.59094378123268840693978620156028975277e32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05630254163426327113368743426054256780e33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06008195534030444387061989883493342898e34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21262490304347036689874956206774563906e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52353024633841796119920505314785365242e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28839143293381125956284415313626962263e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31074057704096457802547386358094338369e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24762412200364040971704861346921094354e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55663903116458425420509083471048286114e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81839283802391753865642022579846918253e37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40026559327708207943879092058654410696e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48767474646810049293505781106444169229e36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10591353097667671736865938428051885499e35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26980708896893794012677171239610721832e33),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 0.25) {
+        RealType t = x - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.6106e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31887921568009055676985827521151969069e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62791448964529380666250180886203090183e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18238045199893937316918299064825702894e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77274519306540522227493503092956314136e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89424638466340765479970877448972418958e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84027004420207996285174223581748706097e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.84633134142285937075423713704784530853e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76780579189423063605715733542379494552e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19812409802969581112716039533798357401e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60039008588877024309600768114757310858e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.10268260529501421009222937882726290612e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.72169594688819848498039471657587836720e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27181379647139697258984772894869505788e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.73617450590346508706222885401965820190e1),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18558935411552146390814444666395959919e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49210559503096368944407109881023223654e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93959323596111340518285858313038058302e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53590607436758691037825792660167970938e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.82700985983018132572589829602100319330e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62137033935442506086127262036686905276e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.76014299715348555304267927238963139228e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.12336796972134088340556958396544477713e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01952132024838508233050167059872220508e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41846547214877387780832317250797043384e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.02083431572388097955901208994308271581e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30401057171447074343957754855656724141e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 0.5) {
+        RealType t = x - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.1519e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87119665000174806422420129219814467874e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.60769554551148293079169764245570645155e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.49181979810834706538329284478129952168e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15722765491675871778645250624425739489e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65973147084701923411221710174830072860e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93709338011482232037110656459951914303e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57393131299425403017769538642434714791e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24110491141294379107651487490031694257e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23670394514211681515965192338544032862e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06141024932329394052395469123628405389e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.08599362073145455095790192415468286304e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.22746783794652085925801188098270888502e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.19652234873414609727168969049557770989e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.73529976407853894192156335785920329181e-4),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04157569499592889296640733909653747983e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82248883130787159161541119440215325308e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.35191216924911901198168794737654512677e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05099314677808235578577204150229855903e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.61081069236463123032873733048661305746e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65340645555368229718826047069323437201e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.44526681322128674428653420882660351679e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03963804195353853550682049993122898950e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40399236835577953127465726826981753422e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46764755170079991793106428011388637748e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06384106042490712972156545051459068443e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27614406724572981099586665536543423891e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 1) {
+        RealType t = x - 0.5;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.1196e-37
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31309550000758082761278726632760756847e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07242222531117199094690544171275415854e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18286763141875580859241637334381199648e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72102024869298528501604761974348686708e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31748399999514540052066169132819656757e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72168003284748405703923567644025252608e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52648991506052496046447777354251378257e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.16777263528764704804758173026143295383e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66044453196259367950849328889468385159e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.35095952392355288307377427145581700484e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43011308494452327007589069222668324337e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16582092138863383294685790744721021189e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02261914949200575965813000131964695720e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93943913630044161720796150617166047233e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.76395009419307902351328300308365369814e-8),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28073115520716780203055949058270715651e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.20245752585870752942356137496087189194e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34548337034735803039553186623067144497e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.90925817267776213429724248532378895039e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92883822651628140083115301005227577059e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72868136219107985834601503784789993218e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50498744791568911029110559017896701095e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05178276667813671578581259848923964311e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.16880263792490095344135867620645018480e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16199396397514668672304602774610890666e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25543193822942088303609988399416145281e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62522294286034117189844614005500278984e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18342889744790118595835138444372660676e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.5605e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71280312689343266367958859259591541365e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49628636612698702680819948707479820292e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61090930375686902075245639803646265081e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.01191924051756106307211298794294657688e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42496510376427957390465373165464672088e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59577769624139820954046058289100998534e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02664809521258420718170586857797408674e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72258711278476951299824066502536249701e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72578941800687566921553416498339481887e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.12553368488232553360765667155702324159e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20749770911901442251726681861858323649e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00621121212654384864006297569770703900e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18976033102817074104109472578202752346e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22093548539863254922531707899658394458e-10),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.83305694892673455436552817409325835774e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49922543669955056754932640312490112609e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23488972536322019584648241457582608908e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14051527527038669918848981363974859889e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37891280136777182304388426277537358346e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.08058775103864815769223385606687612117e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83305488980337433132332401784292281716e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71072208215804671719811563659227630554e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.86332040813989094594982937011005305263e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87698178237970337664105782546771501188e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69113555019737313680732855691540088318e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31888539972217875242352157306613891243e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85633766164682554126992822326956560433e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1494e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13928162275383718405630406427822960090e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90742307267701162395764574873947997211e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.13821826367941514387521090205756466068e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.96186879146063565484800486550739025293e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19438785955706463753454881511977831603e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44969124820016994689518539612465708536e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27841835070651018079759230944461773079e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69952429132675045239242077293594666305e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47919853099168659881487026035933933068e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.04644774117864306055402364094681541437e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52604718870921084048756263996119841957e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97610950633031564892821158058978809537e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35934159016861180185992558083703785765e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21044098237798939057079316997065892072e-14),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94437702178976797218081686254875998984e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82068837586514484653828718675654460991e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87606058269189306593797764456467061128e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39130528408903116343256483948950693356e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52792074489091396425713962375223436022e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00892233011840867583848470677898363716e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53717105060592851173320646706141911461e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57293857675930200001382624769341451561e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04219251796696135508847408131139677925e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.20053006131133304932740325113068767057e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.26384707028090985155079342718673255493e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.19146442700994823924806249608315505708e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59879298772002950043508762057850408213e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.9710e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63772802979087199762340235165979751298e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31941534705372320785274994658709390116e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43643960022585762678456016437621064500e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11415302325466272779041471612529728187e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15767742459744253874067896740220951622e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74049309186016489825053763513176160256e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76349898574685150849080543168157785281e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19757202370729036627932327405149840205e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32067727965321839898287320520750897894e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47636340015260789807543414080472136575e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36236727340568181129875213546468908164e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89379573960280486883733996547662506245e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.71832232038263988173042637335112603365e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72380245500539326441037770757072641975e-18),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51702400281458104713682413542736419584e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01375164846907815766683647295932603968e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92796007869834847612192314006582598557e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.77580441164023725582659445614058463183e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63592331843149724480258804892989851727e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87334158717610115008450674967492650941e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46596056941432875244263245821845070102e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.69980051560936361597177347949112822752e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61690034211585843423761830218320365457e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.40619773800285766355596852314940341504e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.10624533319804091814643828283820958419e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10009654621246392691126133176423833259e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48070591106986983088640496621926852293e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.2049e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22610122564874286614786819620499101143e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.30352481858382230273216195795534959290e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45933050053542949214164590814846222512e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.18776888646200567321599584635465632591e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53421996228923143480455729204878676265e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.26075686557831306993734433164305349875e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58045762501721375879877727645933749122e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13469629033419341069106781092024950086e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09157226556088521407323375433512662525e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44961350323527660188267669752380722085e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11052101325523147964890915835024505324e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.26421404354976214191891992583151033361e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.17133505681224996657291059553060754343e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41010917905686427164414364663355769988e-22),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31062773739451672808456319166347015167e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35386721434011881226168110614121649232e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.39357338312443465616015226804775178232e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.26630144036271792027494677957363535353e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.24340476859846183414651435036807677467e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33917136421389571662908749253850939876e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.80972141456523767244381195690041498939e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22653625120465488656616983786525028119e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64072452032620505897896978124863889812e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61842001579321492488462230987972104386e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96631619425501661980194304605724632777e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80392324086028812772385536034034039168e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34254502871215949266781048808984963366e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.7434e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03056141356415128156562790092782153630e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15331583242023443256381237551843296356e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81847913073640285776566199343276995613e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23578443960486030170636772457627141406e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36906354316016270165240908809929957836e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.80584421020238085239890207672296651219e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20726437845755296397071540583729544203e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71042563703818585243207722641746283288e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08307373360265947158569900625482137206e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80776566500233755365518221977875432763e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11405351639704510305055492207286172753e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21575609293568296049921888011966327905e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66081982641748223969990279975752576675e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96483118060215455299182487430511998831e-26),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77347004038951368607085827825968614455e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27559305780716801070924630708599448466e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05452382624230160738008550961679711827e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75369667590360521677018734348769796476e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56551290985905942229892419848093494661e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46972102361871185271727958608184616388e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.72423917010499649257775199140781647069e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14337306905269302583746182007852069459e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69949885309711859563395555285232232606e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00318719634300754237920041312234711548e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41139664927184402637020651515172315287e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79013190225240505774959477465594797961e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.46536966503325413797061462062918707370e-24),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0402e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57333571766941514095434647381791040479e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15416685251021339933358981066948923001e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86806753164417557035166075399588122481e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91972616817770660098405128729991574724e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10225768760715861978198010761036882002e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05986998674039047865566990469266534338e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59572646670205456333051888086612875871e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19347294198055585461131949159508730257e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21328285448498841418774425071549974153e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19331596847283822557042655221763459728e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.36128017817576942059191451016251062072e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35600223942735523925477855247725326228e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14658948592500290756690769268766876322e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86984591055448991335081550609451649866e-30),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90112824856612652807095815199496602262e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59291524937386142936420775839969648652e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.74245361925275011235694006013677228467e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41828589449615478387532599798645159282e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08088176420557205743676774127863572768e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30760429417424419297000535744450830697e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.18464910867914234357511605329900284981e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.74255540513281299503596269087176674333e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02616028440371294233330747672966435921e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.26276597941744408946918920573146445795e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47463109867603732992337779860914933775e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77217411888267832243050973915295217582e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.67397425207383164084527830512920206074e-28),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        RealType t = 1 / sqrt(x);
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.2612e-35
+        static const RealType P[9] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33908701314796522684603310107061150444e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92120397142832495974006972404741124398e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.15463147603421962834297353867930971657e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44488751006069172847577645328482300099e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44057582804743599116332797864164802887e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02968018188491417839349438941039867033e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.75092244933846337077999183310087492887e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35099582728548602389917143511323566818e-8),
+        };
+        static const RealType Q[7] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.34601617336219074065534356705298927390e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82954035780824611941899463895040327299e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70929001162671283123255408612494541378e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05508596604210030533747793197422815105e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02913299057943756875992272236063124608e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37824426836648736125759177846682556245e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+    if (x >= 0) {
+        return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - saspoint5_cdf_plus_imp_prec(-x, tag) : saspoint5_cdf_plus_imp_prec(-x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - saspoint5_cdf_plus_imp_prec(-x, tag) : saspoint5_cdf_plus_imp_prec(-x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+    //
+    // This calculates the cdf of the Saspoint5 distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::cdf(saspoint5<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    RealType u = (x - location) / scale;
+
+    result = saspoint5_cdf_imp_prec(u, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (ilogb(p) >= -2) {
+        RealType u = -log2(ldexp(p, 1));
+
+        if (u < 0.125) {
+            // Rational Approximation
+            // Maximum Relative Error: 4.2616e-17
+            static const RealType P[13] = {
+                static_cast<RealType>(1.36099130643975127045e-1),
+                static_cast<RealType>(2.19634434498311523885e1),
+                static_cast<RealType>(1.70276954848343179287e3),
+                static_cast<RealType>(8.02187341786354339306e4),
+                static_cast<RealType>(2.48750112198456813443e6),
+                static_cast<RealType>(5.20617858300443231437e7),
+                static_cast<RealType>(7.31202030685167303439e8),
+                static_cast<RealType>(6.66061403138355591915e9),
+                static_cast<RealType>(3.65687892725590813998e10),
+                static_cast<RealType>(1.06061776220305595494e11),
+                static_cast<RealType>(1.23930642673461465346e11),
+                static_cast<RealType>(1.49986408149520127078e10),
+                static_cast<RealType>(-6.17325587219357123900e8),
+            };
+            static const RealType Q[13] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.63111146753825227716e2),
+                static_cast<RealType>(1.27864461509685444043e4),
+                static_cast<RealType>(6.10371533241799228037e5),
+                static_cast<RealType>(1.92422115963507708309e7),
+                static_cast<RealType>(4.11544185502250709497e8),
+                static_cast<RealType>(5.95343302992055062258e9),
+                static_cast<RealType>(5.65615858889758369947e10),
+                static_cast<RealType>(3.30833154992293143503e11),
+                static_cast<RealType>(1.06032392136054207216e12),
+                static_cast<RealType>(1.50071282012095447931e12),
+                static_cast<RealType>(5.43552396263989180433e11),
+                static_cast<RealType>(9.57434915768660935004e10),
+            };
+
+            result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * (p * p));
+        }
+        else if (u < 0.25) {
+            RealType t = u - 0.125;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.3770e-19
+            static const RealType P[8] = {
+                static_cast<RealType>(1.46698650748920243698e-2),
+                static_cast<RealType>(3.58380131788385557227e-1),
+                static_cast<RealType>(3.39153750029553194566e0),
+                static_cast<RealType>(1.55457424873957272207e1),
+                static_cast<RealType>(3.44403897039657057261e1),
+                static_cast<RealType>(3.01881531964962975320e1),
+                static_cast<RealType>(2.77679052294606319767e0),
+                static_cast<RealType>(-7.76665288232972435969e-2),
+            };
+            static const RealType Q[7] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.72584280323876188464e1),
+                static_cast<RealType>(1.11983518800147654866e2),
+                static_cast<RealType>(3.25969893054048132145e2),
+                static_cast<RealType>(3.91978809680672051666e2),
+                static_cast<RealType>(1.29874252720714897530e2),
+                static_cast<RealType>(2.08740114519610102248e1),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+        else if (u < 0.5) {
+            RealType t = u - 0.25;
+
+            // Rational Approximation
+            // Maximum Relative Error: 9.2445e-18
+            static const RealType P[8] = {
+                static_cast<RealType>(2.69627866689346445458e-2),
+                static_cast<RealType>(3.23091180507445216811e-1),
+                static_cast<RealType>(1.42164019533549860681e0),
+                static_cast<RealType>(2.74613170828120023406e0),
+                static_cast<RealType>(2.07865023346180997996e0),
+                static_cast<RealType>(2.53267176863740856907e-1),
+                static_cast<RealType>(-2.55816250186301841152e-2),
+                static_cast<RealType>(3.02683750470398342224e-3),
+            };
+            static const RealType Q[6] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(8.55049920135376003042e0),
+                static_cast<RealType>(2.48726119139047911316e1),
+                static_cast<RealType>(2.79519589592198994574e1),
+                static_cast<RealType>(9.88212916161823866098e0),
+                static_cast<RealType>(1.39749417956251951564e0),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+        else {
+            RealType t = u - 0.5;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.2918e-20
+            static const RealType P[9] = {
+                static_cast<RealType>(4.79518653373241051274e-2),
+                static_cast<RealType>(3.81837125793765918564e-1),
+                static_cast<RealType>(1.13370353708146321188e0),
+                static_cast<RealType>(1.55218145762186846509e0),
+                static_cast<RealType>(9.60938271141036509605e-1),
+                static_cast<RealType>(2.11811755464425606950e-1),
+                static_cast<RealType>(8.84533960603915742831e-3),
+                static_cast<RealType>(1.73314614571009160225e-3),
+                static_cast<RealType>(-3.63491208733876986098e-5),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(6.36954463000253710936e0),
+                static_cast<RealType>(1.40601897306833147611e1),
+                static_cast<RealType>(1.33838075106916667084e1),
+                static_cast<RealType>(5.60958095533108032859e0),
+                static_cast<RealType>(1.11796035623375210182e0),
+                static_cast<RealType>(1.12508482637488861060e-1),
+                static_cast<RealType>(5.18503975949799718538e-3),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 2));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.2057e-18
+        static const RealType P[10] = {
+            static_cast<RealType>(8.02395484493329835881e-2),
+            static_cast<RealType>(2.46132933068351274622e-1),
+            static_cast<RealType>(2.81820176867119231101e-1),
+            static_cast<RealType>(1.47754061028371025893e-1),
+            static_cast<RealType>(3.54638964490281023406e-2),
+            static_cast<RealType>(3.99998730093393774294e-3),
+            static_cast<RealType>(3.81581928434827040262e-4),
+            static_cast<RealType>(1.82520920154354221101e-5),
+            static_cast<RealType>(-2.06151396745690348445e-7),
+            static_cast<RealType>(6.77986548138011345849e-9),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.39244329037830026691e0),
+            static_cast<RealType>(2.12683465416376620896e0),
+            static_cast<RealType>(9.02612272334554457823e-1),
+            static_cast<RealType>(2.06667959191488815314e-1),
+            static_cast<RealType>(2.79328968525257867541e-2),
+            static_cast<RealType>(2.28216286216537879937e-3),
+            static_cast<RealType>(1.04195690531437767679e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.3944e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(1.39293493266195561875e-1),
+            static_cast<RealType>(1.26741380938661691592e-1),
+            static_cast<RealType>(4.31117040307200265931e-2),
+            static_cast<RealType>(7.50528269269498076949e-3),
+            static_cast<RealType>(8.63100497178570310436e-4),
+            static_cast<RealType>(6.75686286034521991703e-5),
+            static_cast<RealType>(3.11102625473120771882e-6),
+            static_cast<RealType>(9.63513655399980075083e-8),
+            static_cast<RealType>(-6.40223609013005302318e-11),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.11234548272888947555e-1),
+            static_cast<RealType>(2.63525516991753831892e-1),
+            static_cast<RealType>(4.77118226533147280522e-2),
+            static_cast<RealType>(5.46090741266888954909e-3),
+            static_cast<RealType>(4.15325425646862026425e-4),
+            static_cast<RealType>(2.02377681998442384863e-5),
+            static_cast<RealType>(5.79823311154876056655e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.1544e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(1.57911660613037760235e-1),
+            static_cast<RealType>(5.59740955695099219682e-2),
+            static_cast<RealType>(8.92895854008560399142e-3),
+            static_cast<RealType>(8.88795299273855801726e-4),
+            static_cast<RealType>(5.66358335596607738071e-5),
+            static_cast<RealType>(2.46733195253941569922e-6),
+            static_cast<RealType>(6.44829870181825872501e-8),
+            static_cast<RealType>(7.62193242864380357931e-10),
+            static_cast<RealType>(-7.82035413331699873450e-14),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.49007782566002620811e-1),
+            static_cast<RealType>(5.65303702876260444572e-2),
+            static_cast<RealType>(5.54316442661801299351e-3),
+            static_cast<RealType>(3.58498995501703237922e-4),
+            static_cast<RealType>(1.53872913968336341278e-5),
+            static_cast<RealType>(4.08512152326482573624e-7),
+            static_cast<RealType>(4.72959615756470826429e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.5877e-18
+        static const RealType P[10] = {
+            static_cast<RealType>(1.59150086070234563099e-1),
+            static_cast<RealType>(6.07144002506911115092e-2),
+            static_cast<RealType>(1.10026443723891740392e-2),
+            static_cast<RealType>(1.24892739209332398698e-3),
+            static_cast<RealType>(9.82922518655171276487e-5),
+            static_cast<RealType>(5.58366837526347222893e-6),
+            static_cast<RealType>(2.29005408647580194007e-7),
+            static_cast<RealType>(6.44325718317518336404e-9),
+            static_cast<RealType>(1.05110361316230054467e-10),
+            static_cast<RealType>(1.48083450629432857655e-18),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.81470315977341203351e-1),
+            static_cast<RealType>(6.91330250512167919573e-2),
+            static_cast<RealType>(7.84712209182587717077e-3),
+            static_cast<RealType>(6.17595479676821181012e-4),
+            static_cast<RealType>(3.50829361179041199953e-5),
+            static_cast<RealType>(1.43889153071571504712e-6),
+            static_cast<RealType>(4.04840254888235877998e-8),
+            static_cast<RealType>(6.60429636407045050112e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.7254e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(1.59154943017783026201e-1),
+            static_cast<RealType>(6.91506515614472069475e-2),
+            static_cast<RealType>(1.44590186111155933843e-2),
+            static_cast<RealType>(1.92616138327724025421e-3),
+            static_cast<RealType>(1.79640147906775699469e-4),
+            static_cast<RealType>(1.30852535070639833809e-5),
+            static_cast<RealType>(5.55259657884038297268e-7),
+            static_cast<RealType>(3.50107118687544980820e-8),
+            static_cast<RealType>(-1.47102592933729597720e-22),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.34486357752330500669e-1),
+            static_cast<RealType>(9.08486933075320995164e-2),
+            static_cast<RealType>(1.21024289017243304241e-2),
+            static_cast<RealType>(1.12871233794777525784e-3),
+            static_cast<RealType>(8.22170725751776749123e-5),
+            static_cast<RealType>(3.48879932410650101194e-6),
+            static_cast<RealType>(2.19978790407451988423e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else {
+        result = 1 / (p * p * constants::two_pi<RealType>());
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (ilogb(p) >= -2) {
+        RealType u = -log2(ldexp(p, 1));
+
+        if (u < 0.125) {
+            // Rational Approximation
+            // Maximum Relative Error: 2.5675e-36
+            static const RealType P[31] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36099130643975133156293056139850872219e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03940482189350763127508703926866548690e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00518276893354880480781640750482315271e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.55844903094077096941027360107304259099e6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04507684135310729583474324660276395831e9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28519957085041757616278379578781441623e11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26054173986187219679917530171252145632e13),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00693075272502479915569708465960917906e15),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.64153695410984136395853200311209462775e16),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64993034609287363745840801813540992383e18),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68080300629977787949474098413155901197e20),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.50632142671665246974634799849090331338e21),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11943753054362349397013211631038480307e23),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.80601829873419334580289886671478701625e24),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33441650581633426542372642262736818512e26),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.56279427934163518272441555879970370340e27),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08899113985387092689705022477814364717e28),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37750989391907347952902900750138805007e29),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.76961267256299304213687639380275530721e30),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.98417586455955659885944915688130612888e31),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40932923796679251232655132670811114351e32),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80810239916688876216017180714744912573e33),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23907429566810200929293428832485038147e33),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11441754640405256305951569489818422227e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30534222360394829628175800718529342304e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.73301799323855143458670230536670073483e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53142592196246595846485130434777396548e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81719621726393542967303806360105998384e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00188544550531824809437206713326495544e33),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62706943144847786115732327787879709587e32),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32129438774563059735783287456769609571e31),
+            };
+            static const RealType Q[32] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65910866673514847742559406762379054364e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21954860438789969160116317316418373146e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85684385746348850219351196129081986508e7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76131116920014625994371306210585646224e9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.57402411617965582839975369786525269977e11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.42213951996062253608905591667405322835e13),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55477693883842522631954327528060778834e15),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00397907346473927493255003955380711046e17),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76305959503723486331556274939198109922e19),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27926540483498824808520492399128682366e21),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.98253913105291675445666919447864520248e22),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63457445658532249936389003141915626894e24),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.51446616633910582673057455450707805902e25),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04744823698010333311911891992022528040e27),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.03400927415310540137351756981742318263e28),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28761940359662123632247441327784689568e29),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.39016138777648624292953560568071708327e30),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79639567867465767764785448609833337532e31),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23406781975678544311073661662680006588e32),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.97261483656310352862554580475760827374e33),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62715040832592600542933595577003951697e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.77359945057399130202830211722221279906e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07842295432910751940058270741081867701e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.51739306780247334064265249344359460675e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60574331076505049588401700048488577194e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.08286808700840316336961663635580879141e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27661033115008662284071342245200272702e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00465576791024249023365007797010262700e35),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83311248273885136105510175099322638440e34),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96635220211386288597285960837372073054e33),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23849744128418288892902205619933047730e32),
+            };
+
+            result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * (p * p));
+        }
+        else if (u < 0.25) {
+            RealType t = u - 0.125;
+
+            // Rational Approximation
+            // Maximum Relative Error: 9.0663e-36
+            static const RealType P[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46698650748920243663487731226111319705e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.39021286045890143123252180276484388346e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21933242816562043224009451007344301143e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33741547463966207206741888477702151242e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.29556944160837955334643715180923663741e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25261081330476435844217173674285740857e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28690563577245995896389783271544510833e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51764495004238264050843085122188741180e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00501773552098137637598813101153206656e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93991776883375928647775429233323885440e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13059418708769178567954713937745050279e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41565791250614170744069436181282300453e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35838723365672196069179944509778281549e1),
+            };
+            static const RealType Q[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63888803456697300467924455320638435538e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74785179836182339383932806919167693991e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.15133301804008879476562749311747788645e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87361675398393057971764841741518474061e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02992617475892211368309739891693879676e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36356854400440662641546588001882412251e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35807552915245783626759227539698719908e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75959389290929178190646034566377062463e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18514088996371641206828142820042918681e5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54881978220293930450469794941944831047e4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83958740186543542804045767758191509433e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26637084978098507405883170227585648985e2),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+        else if (u < 0.5) {
+            RealType t = u - 0.25;
+
+            // Rational Approximation
+            // Maximum Relative Error: 7.1265e-35
+            static const RealType P[14] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69627866689346442965083437425920959525e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.28948812330446670380449765578224539665e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.38832694133021352110245148952631526683e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70206624753427831733487031852769976576e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34677850226082773550206949299306677736e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18657422004942861459539366963056149110e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.90933843076824719761937043667767333536e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78597771586582252472927601403235921029e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76489020985978559079198751910122765603e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37662018494780327201390375334403954354e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11303058491765900888068268844399186476e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.38147649159947518976483710606042789880e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.81260575060831053615857196033574207714e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.26783311530618626413866321968979725353e-3),
+            };
+            static const RealType Q[13] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98941943311823528497840052715295329781e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70142252619301982454969690308614487433e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17472255695869018956165466705137979540e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42016169942136311355803413981032780219e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.55874385736597452997483327962434131932e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45782883079400958761816030672202996788e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05272877129840019671123017296056938361e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79833037593794381103412381177370862105e3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67388248713896792948592889733513376054e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19952164110429183557842014635391021832e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43813483967503071358907030110791934870e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21327682641358836049127780506729428797e-1),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+        else {
+            RealType t = u - 0.5;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.7048e-37
+            static const RealType P[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79518653373241051262822702930040975338e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62230291299220868262265687829866364204e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87315544620612697712513318458226575394e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.38993950875334507399211313740958438201e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54257654902026056547861805085572437922e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85673656862223617197701693270067722169e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47842193222521213922734312546590337064e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76640627287007744941009407221495229316e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71884893887802925773271837595143776207e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87432154629995817972739015224205530101e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44664933176248007092868241686074743562e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32094739938150047092982705610586287965e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18537678581395571564129512698022192316e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99365265557355974918712592061740510276e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.66467016868206844419002547523627548705e-6),
+            };
+            static const RealType Q[15] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01315080955831561204744043759079263546e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43409077070585581955481063438385546913e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09863540097812452102765922256432103612e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69971336507400724019217277303598318934e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71444880426858110981683485927452024652e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15252748520663939799185721687082682973e2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28399989835264172624148638350889215004e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73464700365199500083227290575797895127e1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.40421770918884020099427978511354197438e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.97023025282119988988976542004620759235e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38774609088015115009880504176630591783e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52748138528630655371589047000668876440e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13088455793478303045390386135591069087e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.18220605549460262119565543089703387122e-5),
+            };
+
+            result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+        }
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 2));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.8969e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.02395484493329839255216366819344305871e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02703992140456336967688958960484716694e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38779662796374026809611637926067177436e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22326903547451397450399124548020897393e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29321119874906326000117036864856138032e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60045794013093831332658415095234082115e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.75863216252160126657107771372004587438e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65658718311497180532644775193008407069e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.53225259384404343896446164609240157391e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17876243295156782920260122855798305258e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59647007234516896762020830535717539733e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64519789656979327339865975091579252352e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29566724776730544346201080459027524931e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40979492647851412567441418477263395917e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78894057948338305679452471174923939381e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.97064244496171921075006182915678263370e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13496588267213644899739513941375650458e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75224691413667093006312591320754720811e-14),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.59000688626663121310675150262772434285e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37518060227321498297232252379976917550e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96559443266702775026538144474892076437e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81865210018244220041408788510705356696e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15188291931842064325756652570456168425e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.16909307081950035111952362482113369939e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68454509269150307761046136063890222011e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06391236761753712424925832120306727169e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35744804731044427608283991933125506859e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00655928177646208520006978937806043639e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04093230988242553633939757013466501271e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.07921031269974885975846184199640060403e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61356596082773699708092475561216104426e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83968520269928804453766899533464507543e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44620973323561344735660659502096499899e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84398925760354259350870730551452956164e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.0176e-35
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39293493266195566603513288406748830312e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75724665658983779947977436518056682748e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42437549740894393207094008058345312893e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26189619865771499663660627120168211026e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.38952430871711360962228087792821341859e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09604487371653920602809626594722822237e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06215021409396534038209460967790566899e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02245531075243838209245241246011523536e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52822482024384335373072062232322682354e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.32527687997718638700761890588399465467e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54799997015944073019842889902521208940e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59368565314052950335981455903474908073e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09459594346367728583560281313278117879e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30296867679720593932307487485758431355e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04594079707862644415224596859620253913e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40274507498190913768918372242285652373e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48644117815971872777609922455371868747e-16),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88079839671202113888025645668230104601e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58898753182105924446845274197682915131e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.05418719178760837974322764299800701708e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76439568495464423890950166804368135632e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87661284201828717694596419805804620767e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29462021166220769918154388930589492957e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89960014717788045459266868996575581278e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21759236630028632465777310665839652757e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08884467282860764261728614542418632608e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60098870889198704716300891829788260654e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00120123451682223443624210304146589040e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08868117923724451329261971335574401646e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07346130275947166224129347124306950150e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57848230665832873347797099944091265220e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50841502849442327828534131901583916707e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19165038770000448560339443014882434202e-15),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.1682e-36
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57911660613037766795694241662819364797e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28799302413396670477035614399187456630e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87488304496324715063356722168914018093e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15106082041721012436439208357739139578e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91744691940169259573871742836817806248e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40707390548486625606656777332664791183e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.37047148097688601398129659532643297674e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88039545021930711122085375901243257574e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22254460725736448552173288004145978774e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.58462349007293730244197837509157696852e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95242372547984999431208546685672497090e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10113734998651793201123616276573169622e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.38963677413425618019569452771868834246e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45242599273032563942546507899265865936e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64855118157117311049698715635863670233e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31679318790012894619592273346600264199e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97289727214495789126072009268721022605e-20),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10184661848812835285809771940181522329e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06179300560230499194426573196970342618e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23171547302923911058112454487643162794e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20486436116678834807354529081908850425e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51239574861351183874145649960640500707e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48939385253081273966380467344920741615e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18148716720470800170115047757600735127e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.68156131480770927662478944117713742978e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13720275846166334505537351224097058812e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85505701632948614345319635028225905820e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.91876669388212587242659571229471930880e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12971661051277278610784329698988278013e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31096179726750865531615367639563072055e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03579138802970748888093188937926461893e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45570688568663643410924100311054014175e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23959804461200982866930072222355142173e-19),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.2158e-37
+        static const RealType P[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59150086070234561732507586188017224084e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80849532387385837583114307010320459997e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41158479406270598752210344238285334672e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88824037165656723581890282427897772492e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82912940787568736176030025420621547622e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36469458704261637785603215754389736108e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.13801486421774537025334682673091205328e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97058432407176502984043208925327069250e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60823277541385163663463406307766614689e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45016369260792040947272022706860047646e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54846457278644736871929319230398689553e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.67291749890916930953794688556299297735e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.18742803398417392282841454979723852423e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13337431668170547244474715030235433597e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37782648734897338547414800391203459036e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17863064141234633971470839644872485483e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58768205048500915346781559321978174829e-24),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27782279546086824129750042200649907991e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86934772625607907724733810228981095894e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18640923531164938140838239032346416143e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14927915778694317602192656254187608215e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.57462121236985574785071163024761935943e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11326475640883361512750692176665937785e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49479333407835032831192117009600622344e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01048164044583907219965175201239136609e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42444147056333448589159611785359705792e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.72928365136507710372724683325279209464e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30776323450676114149657959931149982200e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.51599272091669693373558919762006698549e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12120236145539526122748260176385899774e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.65713807525694136400636427188839379484e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40555520515542383952495965093730818381e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.51084407433793180162386990118245623958e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.8515e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943017783040087729009335921759322e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.35955784629344586058432079844665517425e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24333525582177610783141409282489279582e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58257137499954581519132407255793210808e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47191495695958634792434622715063010854e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06408464185207904662485396901099847317e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20796977470988464880970001894205834196e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99451680244976178843047944033382023574e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21331607817814211329055723244764031561e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16997758215752306644496702331954449485e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22151810180865778439184946086488092970e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05017329554372903197056366604190738772e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.45919279055502465343977575104142733356e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14611865933281087898817644094411667861e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66574579315129285098834562564888533591e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90098275536617376789480602467351545227e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56200324658873566425094389271790730206e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35526648761411463124801128103381691418e-26),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.99582804063194774835771688139366152937e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.81210581320456331960539046132284190053e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94358920922810097599951120081974275145e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.24831443209858422294319043037419780210e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.68584098673893150929178892200446909375e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90058244779420124535106788512940199547e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88151039746201934320258158884886191886e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.62348975553160355852344937226490493460e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62007418751593938350474825754731470453e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.67502458979132962529935588245058477825e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91648040348401277706598232576212305626e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05843052379331618504561151714467880641e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.20127592059771206959014911028588129920e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04661894930286305556240859086772458465e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19442269177165740287568170417649762849e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.81435584873372180820418114652670864136e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62145023253666168339801687459484937001e-25),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.2157e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943091895335751628149866310390641e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.91164927854420277537616294413463565970e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47557801928232619499125670863084398577e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06172621625221091203249391660455847328e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11720157411653968975956625234656001375e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70086412127379161257840749700428137407e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11069186177775505692019195793079552937e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.04581765901792649215653828121992908775e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78996797234624395264657873201296117159e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10365978021268853654282661591051834468e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76744621013787434243259445839624450867e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11110170303355425599446515240949433934e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83669090335022069229153919882930282425e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.09633460833089193733622172621696983652e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16200852052266861122422190933586966917e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47795810090424252745150042033544310609e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35722092370326505616747155207965300634e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.98381676423023212724768510437325359364e-51),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239691423485699928257808e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849140772481980360839559e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29542078693828543560388747333519393752e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33027698228265344561650492600955601983e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06868444562964057795387778972002636261e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.97868278672593071151212650783507879919e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79869926850283188785885503049178903204e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75298857713475428388051708713106549590e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.93449891515741631942400181171061740767e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36715626731277089044713008494971829270e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.98125789528264426960496891930942311971e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78234546049400950544724588355539821858e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83044000387150792693434128054414524740e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30111486296552039483196431122555524886e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28628462422858135083238952377446358986e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48108558735886480298604270981393793162e-21),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
+    }
+    else {
+        result = 1 / (p * p * constants::two_pi<RealType>());
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+{
+    if (p > 0.5) {
+        return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? saspoint5_quantile_upper_imp_prec(p, tag) : -saspoint5_quantile_upper_imp_prec(p, tag);
+}
+
+template <class RealType>
+inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+{
+    if (p > 0.5) {
+        return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? saspoint5_quantile_upper_imp_prec(p, tag) : -saspoint5_quantile_upper_imp_prec(p, tag);
+}
+
+template <class RealType, class Policy>
+inline RealType saspoint5_quantile_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+{
+    // This routine implements the quantile for the Saspoint5 distribution,
+    // the value p may be the probability, or its complement if complement=true.
+
+    static const char* function = "boost::math::quantile(saspoint5<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_probability(function, p, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = location + scale * saspoint5_quantile_imp_prec(p, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+{
+    return static_cast<RealType>(3.63992444568030649573);
+}
+
+template <class RealType>
+inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.6399244456803064957308496039071853510);
+}
+
+template <class RealType, class Policy>
+inline RealType saspoint5_entropy_imp(const saspoint5_distribution<RealType, Policy>& dist)
+{
+    // This implements the entropy for the Saspoint5 distribution,
+
+    static const char* function = "boost::math::entropy(saspoint5<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    result = saspoint5_entropy_imp_prec<RealType>(tag_type()) + log(scale);
+
+    return result;
+}
+
+} // detail
+
+template <class RealType = double, class Policy = policies::policy<> >
+class saspoint5_distribution
+{
+    public:
+    typedef RealType value_type;
+    typedef Policy policy_type;
+
+    saspoint5_distribution(RealType l_location = 0, RealType l_scale = 1)
+        : mu(l_location), c(l_scale)
+    {
+        static const char* function = "boost::math::saspoint5_distribution<%1%>::saspoint5_distribution";
+        RealType result = 0;
+        detail::check_location(function, l_location, &result, Policy());
+        detail::check_scale(function, l_scale, &result, Policy());
+    } // saspoint5_distribution
+
+    RealType location()const
+    {
+        return mu;
+    }
+    RealType scale()const
+    {
+        return c;
+    }
+
+    private:
+    RealType mu;    // The location parameter.
+    RealType c;     // The scale parameter.
+};
+
+typedef saspoint5_distribution<double> saspoint5;
+
+#ifdef __cpp_deduction_guides
+template <class RealType>
+saspoint5_distribution(RealType) -> saspoint5_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+template <class RealType>
+saspoint5_distribution(RealType, RealType) -> saspoint5_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+#endif
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> range(const saspoint5_distribution<RealType, Policy>&)
+{ // Range of permissible values for random variable x.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> support(const saspoint5_distribution<RealType, Policy>&)
+{ // Range of supported values for random variable x.
+   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType pdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::saspoint5_pdf_imp(dist, x);
+} // pdf
+
+template <class RealType, class Policy>
+inline RealType cdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::saspoint5_cdf_imp(dist, x, false);
+} // cdf
+
+template <class RealType, class Policy>
+inline RealType quantile(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p)
+{
+    return detail::saspoint5_quantile_imp(dist, p, false);
+} // quantile
+
+template <class RealType, class Policy>
+inline RealType cdf(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::saspoint5_cdf_imp(c.dist, c.param, true);
+} //  cdf complement
+
+template <class RealType, class Policy>
+inline RealType quantile(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::saspoint5_quantile_imp(c.dist, c.param, true);
+} // quantile complement
+
+template <class RealType, class Policy>
+inline RealType mean(const saspoint5_distribution<RealType, Policy> &dist)
+{
+    // There is no mean:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::mean(saspoint5<%1%>&)",
+        "The SaSpoint5 distribution does not have a mean: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType variance(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no variance:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::variance(saspoint5<%1%>&)",
+        "The SaSpoint5 distribution does not have a variance: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType mode(const saspoint5_distribution<RealType, Policy>& dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType median(const saspoint5_distribution<RealType, Policy>& dist)
+{
+    return dist.location();
+}
+
+template <class RealType, class Policy>
+inline RealType skewness(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no skewness:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::skewness(saspoint5<%1%>&)",
+        "The SaSpoint5 distribution does not have a skewness: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis(saspoint5<%1%>&)",
+        "The SaSpoint5 distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis_excess(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis excess:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "assert type is undefined");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis_excess(saspoint5<%1%>&)",
+        "The SaSpoint5 distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType entropy(const saspoint5_distribution<RealType, Policy>& dist)
+{
+    return detail::saspoint5_entropy_imp(dist);
+}
+
+}} // namespaces
+
+
+#endif // BOOST_STATS_SASPOINT5_HPP
diff --git a/test/test_saspoint5.cpp b/test/test_saspoint5.cpp
new file mode 100644
index 0000000000..97a7c43ad5
--- /dev/null
+++ b/test/test_saspoint5.cpp
@@ -0,0 +1,878 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_TEST_MODULE StatsSaSpoint5Test
+#include <boost/test/included/unit_test.hpp>
+#include <boost/multiprecision/cpp_bin_float.hpp>
+
+#include <boost/math/distributions/saspoint5.hpp>
+using boost::math::saspoint5_distribution;
+using boost::multiprecision::cpp_bin_float_quad;
+
+template<class RealType, int N>
+void do_test_saspoint5_pdf(){
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65057384221262866484014802392420311075288403543570e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79329640523490376041131493419821198600076403419386e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95852304370396879516224023732198088002401888082616e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15165745993244539388932384769132623478818505719254e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37991930003932826612228434406591616554240049257806e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65315905048420909110038030496372707676321065455853e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98514782971078642902580240066249560381976244868252e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.39569569206548434200616180477229996876301302607033e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91428580496513429479068747515164587814473831035141e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22747038893846641865142698258984886289652875016810e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58664432176873307685856460747711890398474760309135e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.00211113907132159419276991035240896253998639909692e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.48740303942235865293078214071409846807501918299929e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.06062847902700317213276816720705695621399130112975e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.74654707859965380374478388584454386653113140787247e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.57987022193031994457557921317658430036146780413966e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.61071469126041183247373313827161939453635781053656e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.22226841107155902731102159116498022415283445125970e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.91402704796678469983705063964301389721348302634810e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07020274682586388030767450697192728366834992164365e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16067678880616390663660038956460612725510361666743e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.26548452861398188870931570373322249360362213948984e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38813584257594010463041381178865326769684234839162e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53335207865128979807776513257284069794567700115319e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70762401725206223811383500786268939644546879037607e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.80837633035190650461893908063251050472045384954446e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92009924039028830545431687288769864540254439571691e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04458865222194329452641393707783622253522148720927e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18403802814813998631607652585109350067000954260159e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34114858767964975455487653703370079404113295500766e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51927454673218629749392967500746624956301580234179e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72261384495736629760803695406845321684342258638651e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.95645445681747568731488283573032414811445124048278e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08683711301287379599769504729521857091008674908403e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22747777451211671698876953149906906288207621283740e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37948342659965914836420291897431271791569870739942e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54408462624872191505363112311495187968578947455635e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72263350586688041299651258469337654343439789762344e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91658567295250072264436343404335704809676265611623e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.12745086277094097472011430871049070050383274543942e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.35668401768623200524372663239480799018368629449958e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.60546312221207321659735213679473165482665805082365e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87425051951658593562735199923143476116556674561953e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.16193612095139713576014676574899762241637086348666e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.46416716200748206779925127900698754118588044244443e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.77011156717390291621839083396306231100301720494794e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.05643252618763782827233685490846659295644445464474e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.27802677165093171536432271430054096075199851236277e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.36619772367581343075535053490057448137838582961826e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.27802677165093171536432271430054096075199851236277e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.05643252618763782827233685490846659295644445464474e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.77011156717390291621839083396306231100301720494794e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.46416716200748206779925127900698754118588044244443e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.16193612095139713576014676574899762241637086348666e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87425051951658593562735199923143476116556674561953e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.60546312221207321659735213679473165482665805082365e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.35668401768623200524372663239480799018368629449958e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.12745086277094097472011430871049070050383274543942e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91658567295250072264436343404335704809676265611623e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72263350586688041299651258469337654343439789762344e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54408462624872191505363112311495187968578947455635e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37948342659965914836420291897431271791569870739942e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22747777451211671698876953149906906288207621283740e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08683711301287379599769504729521857091008674908403e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.95645445681747568731488283573032414811445124048278e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72261384495736629760803695406845321684342258638651e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51927454673218629749392967500746624956301580234179e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34114858767964975455487653703370079404113295500766e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18403802814813998631607652585109350067000954260159e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04458865222194329452641393707783622253522148720927e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92009924039028830545431687288769864540254439571691e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.80837633035190650461893908063251050472045384954446e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70762401725206223811383500786268939644546879037607e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53335207865128979807776513257284069794567700115319e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38813584257594010463041381178865326769684234839162e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.26548452861398188870931570373322249360362213948984e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16067678880616390663660038956460612725510361666743e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.07020274682586388030767450697192728366834992164365e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.91402704796678469983705063964301389721348302634810e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.22226841107155902731102159116498022415283445125970e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.61071469126041183247373313827161939453635781053656e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.57987022193031994457557921317658430036146780413966e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.74654707859965380374478388584454386653113140787247e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.06062847902700317213276816720705695621399130112975e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.48740303942235865293078214071409846807501918299929e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.00211113907132159419276991035240896253998639909692e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58664432176873307685856460747711890398474760309135e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22747038893846641865142698258984886289652875016810e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91428580496513429479068747515164587814473831035141e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.39569569206548434200616180477229996876301302607033e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98514782971078642902580240066249560381976244868252e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65315905048420909110038030496372707676321065455853e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37991930003932826612228434406591616554240049257806e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15165745993244539388932384769132623478818505719254e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95852304370396879516224023732198088002401888082616e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79329640523490376041131493419821198600076403419386e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65057384221262866484014802392420311075288403543570e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41709229627396868333284301965586098495341505333984e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23486804023715403906392442935982382364217653266772e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08928004905124817201928007015908544910529569714342e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.70693662562544123549117032234725245555978806476399e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.72521377242204601673499906339041894791681660981780e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.90118208003638158949103509569466271651423947601700e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20122199033087670451578082577537221533524657616689e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.60044810497290557552736366450372523266254544297541e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.62568921883700157286068393009259359194911515759460e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87225538372111615796471446753804828223647849403478e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.27521869884978603565623102805698827447589635270965e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.79233594205638037575121942287372720508125859480601e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.39503653350126602107748523248767674409207708020015e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.06336366766043497753645671560287680725185122482037e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78299184327161285281451711213360177146934142134357e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54339461777955741686401041938275102206830951452701e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15681965291001751496355126714032815564803295371462e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85998635069315959390913560004569618374730778555584e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62608332259613979271666391679559272984023328035102e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43781372306723685704327334057789272970358761256651e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28356349911089078230470059243188541053449454702148e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.15527095704472843921748976306796551576061214402975e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04718107132157571106811924450948266398728667364202e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.55085695067883584460317653567009454037053097890033e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.07065059415060466523722913682664006023733154400679e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.93920671056491824666303660784084772546983031349823e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.05105752932345415433215445597062488386383300986381e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33854958380909922933873661422920090995959934982337e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.75647800724537927733394825316181366013592737695448e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.27359757459764665859327891341356484542630879530500e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.86768631746691871635029152331878689826668170171440e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.52254909340415842254122300688608224784456787996634e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.96929220521963282370464091269016751022713088743640e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54771289809160518824087477899271848785553979294988e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21766390014321750130289247373333697019024113873128e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95349215386026125880558883477711894508813402521643e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73811374936907293362277490498742346151511716286084e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55975461659552125943580943693269482505834989982945e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41006225150819455490222552628817791206744288460867e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28296324273402304808354336538549844914883481532620e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.63180321475387230691526892287847669196997380044025e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66189768326912251607424407981263646223230063365226e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.93708011998897739786377954224930716533616609090213e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.11452967162743112245198615236484567129951718982008e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.51482080833564338340856966996445313498079083789150e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66663174159211670027542189178751103023898387998523e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.45238046039194445466823557091765258247216574897413e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.34803516847185617806978815778928715951216310353916e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18523956611649861747653810989133680515605456258881e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19428394481581920558479056092124822410228982935516e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48386121491270229946980639019289494044106626390164e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.24863743761365464204033370116809431054495238229389e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85627269567198410070703889816912945617135110666962e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56441321254434701892659687588069630508140502616495e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32124514546671241752437061147193743959791071682877e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.20777750941928700289773286319085009877829580100394e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90212173401654051439660118394241371322264056105160e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02611352372467016891796952205325499928128114461973e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62800552193521241168029742332979605534754328327140e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28273024622868202243706785685607188210679822726442e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53522776159999787175268870767580373267754737032134e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60346802350897629386145672448930505388450307742542e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66917274294807913528606004426646232913424627695599e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00436953991320274750778716874695704836278902566390e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08655220551513998962815689594959332706015306211632e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85824418029941626524148561830736428793658611772587e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728389276235510083072832489179009106826041868534e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410697234730043795694534456878302211221269628364e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013503193177856102694285471291153594530345945373e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16266961272612513551592941445333504133461857377298e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333753016489787852265460543736089676535476354358e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917223411693427580584068017775560157489239248184e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396549352793655444565334974277876088154820156655e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995699246102965377026386970340969776925728507708e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994631904573126677044584818697892085174708564778e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993294785056705165902599588868178759415543962830e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162154653357770314062605026847259176035189343e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905202884892491063675049720005913844624989838025e-27), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503725850485091152332729977897011733755140179e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379732147400935170577498436447103578962194983e-29), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974711955685286218349809111390785355323964808e-30), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460542241032622871979569574240917519314612402e-32), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907118661876897809516737349031422411025903664e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604881272566803193825546858269428369981726767e-36), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013025533256374121391266749023560191365933e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198457980010827684344075634340204878641095256e-39), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590643616572397339764831428700168401193312e-41), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797900123415519497865404920881954749456838e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809226549290322908699069488543719245241219e-45), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220191945453705676879390798465474357652431e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550030836685714809779087770458087234145e-48), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609468520317755439405311521523337977429e-50), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327312273151307737011597702780857146510e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636432344828142894916983611711484679173e-54), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442824114913911543137689436308410131e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254518240301652494105481741383790265e-57), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522725985138779564208904631966988869e-59), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_cdf() {
+    //
+    // Basic sanity checks, tolerance is either 5 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 5;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.63772802979087199762340235165979754525757604354946e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68073422703516098355866522837852256596174289760926e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72758003279298484112934948051066338979626419965674e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77889244858892026253876673752518849640459231269905e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.83545491848533781581075416061045687904524946502798e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89826216632004296533051251749295777627320352902276e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96860081561627764765290065134912151446894162470366e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04817161935798121677981868384882359833404907918648e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.13928162275383718405630406427822962549133076160983e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19012422407024648274998126765803685575224367865758e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.24515968592015292591213160991283529212368507398551e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30502444449412087831256855850010593081747948385277e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37050277816586024016699127500442336442368833061485e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.44257500572741387471454711747681504603506105875273e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.52248669635662507718372623246751628200366838868998e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.61185078990430196469782036568483593931021694091782e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.71280312689343266367958859259591543958449635451967e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76849301027297680034801351032711397512725349083505e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.82824834763715399283433728056507088064285422281461e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.89261854625965316722646909500096608624627558333255e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.96226648191670403196061310683376239616840103866983e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03800118279447955882543375356729458148212335628057e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.12082296340545811234455810077892380496395042488318e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.21198706286302016964660139725707925695690953535621e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.31309550000758082761278726632760757082965788779064e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36800649890180441699589040706573844882916813862746e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.42623318957604837956085530683032551753868317236287e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.48814554885607965224431388327096964758526950639963e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55417563843010824151990624091505209837963398189766e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62483167142022658662698467701475815382565060700827e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.70071604494776495147661422048036562690579901259931e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.78254859359158098510888509896172431097522748703865e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.87119665000174806422420129219814480076318292452197e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91839717977573455659490354583900768691773107778703e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.96771371640645784475148651296909803541218278211201e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.01931503128208807344707441840522746424640776733482e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.07338815387886469109799016905025356718337763965952e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.13014030144742808960599738063482904351064602625491e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.18980066583859588646492309993087622866113891170991e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.25262169970425461499760639161103103516585531687363e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.31887921568009055676985827521151927561905069756334e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38886999325100940692217415763934459424688336515323e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.46290440538810971901075463907912052110770078557001e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.54128928252324244858536397279015277684698852998387e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.62429173448713128429248489740624277005917720602166e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.71206593195666184191280277407391829224588075252830e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.80450931389242086819408627721643501783105413645046e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.90099745314478063577240966101000818037412904585595e-1), tolerance);
+    BOOST_CHECK_EQUAL(cdf(dist, static_cast<RealType>(0)), static_cast<RealType>(0.5));
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.09900254685521936422759033898999181962587095414405e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19549068610757913180591372278356498216894586354954e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.28793406804333815808719722592608170775411924747170e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.37570826551286871570751510259375722994082279397834e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.45871071747675755141463602720984722315301147001613e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53709559461189028098924536092087947889229921442999e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.61113000674899059307782584236065540575311663484677e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68112078431990944323014172478848072438094930243666e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.74737830029574538500239360838896896483414468312637e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.81019933416140411353507690006912377133886108829009e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.86985969855257191039400261936517095648935397374509e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.92661184612113530890200983094974643281662236034048e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.98068496871791192655292558159477253575359223266518e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.03228628359354215524851348703090196458781721788799e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08160282022426544340509645416099231308226892221297e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.12880334999825193577579870780185519923681707547803e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.21745140640841901489111490103827568902477251296135e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.29928395505223504852338577951963437309420098740069e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.37516832857977341337301532298524184617434939299173e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.44582436156989175848009375908494790162036601810234e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.51185445114392034775568611672903035241473049360037e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.57376681042395162043914469316967448246131682763713e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63199350109819558300410959293426155117083186137254e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.68690449999241917238721273367239242917034211220936e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.78801293713697983035339860274292074304309046464379e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.87917703659454188765544189922107619503604957511682e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.96199881720552044117456624643270541851787664371943e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03773351808329596803938689316623760383159896133017e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.10738145374034683277353090499903391375372441666745e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.17175165236284600716566271943492911935714577718539e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.23150698972702319965198648967288602487274650916495e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.28719687310656733632041140740408456041550364548033e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.38814921009569803530217963431516406068978305908218e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.47751330364337492281627376753248371799633161131002e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55742499427258612528545288252318495396493894124727e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.62949722183413975983300872499557663557631166938515e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.69497555550587912168743144149989406918252051614723e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.75484031407984707408786839008716470787631492601449e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.80987577592975351725001873234196314424775632134242e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86071837724616281594369593572177037450866923839017e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.95182838064201878322018131615117640166595092081352e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.03139918438372235234709934865087848553105837529634e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.10173783367995703466948748250704222372679647097724e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.16454508151466218418924583938954312095475053497202e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.22110755141107973746123326247481150359540768730095e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.27241996720701515887065051948933661020373580034326e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.31926577296483901644133477162147743403825710239074e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.36227197020912800237659764834020245474242395645054e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.43871020523024507614851721583135267180360280594143e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.50483092818015575884212092733928976209364127755594e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.56280494417603102056412672973803628491156640138235e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.61420731826426116856340074125786936047174397075840e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.66021349395697519291462973006173132761227963124588e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70172157747564156568159926049840862439194389470164e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.73943162478672589326613255747804240803057053984280e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.77389877435125713385213180379500898219171021326151e-1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_ccdf() {
+    //
+    // Basic sanity checks, tolerance is either 5 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 5;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86071837724616281594369593572177037450866923839017e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.80987577592975351725001873234196314424775632134242e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.75484031407984707408786839008716470787631492601449e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.69497555550587912168743144149989406918252051614723e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.62949722183413975983300872499557663557631166938515e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55742499427258612528545288252318495396493894124727e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.47751330364337492281627376753248371799633161131002e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.38814921009569803530217963431516406068978305908218e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.28719687310656733632041140740408456041550364548033e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.23150698972702319965198648967288602487274650916495e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.17175165236284600716566271943492911935714577718539e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.10738145374034683277353090499903391375372441666745e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03773351808329596803938689316623760383159896133017e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.96199881720552044117456624643270541851787664371943e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.87917703659454188765544189922107619503604957511682e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.78801293713697983035339860274292074304309046464379e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.68690449999241917238721273367239242917034211220936e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.46875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63199350109819558300410959293426155117083186137254e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.57376681042395162043914469316967448246131682763713e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.40625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.51185445114392034775568611672903035241473049360037e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.44582436156989175848009375908494790162036601810234e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.34375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.37516832857977341337301532298524184617434939299173e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.29928395505223504852338577951963437309420098740069e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.28125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.21745140640841901489111490103827568902477251296135e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.12880334999825193577579870780185519923681707547803e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.234375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08160282022426544340509645416099231308226892221297e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.21875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.03228628359354215524851348703090196458781721788799e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.203125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.98068496871791192655292558159477253575359223266518e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.92661184612113530890200983094974643281662236034048e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.171875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.86985969855257191039400261936517095648935397374509e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.15625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.81019933416140411353507690006912377133886108829009e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.140625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.74737830029574538500239360838896896483414468312637e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68112078431990944323014172478848072438094930243666e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.109375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.61113000674899059307782584236065540575311663484677e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.09375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53709559461189028098924536092087947889229921442999e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.078125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.45871071747675755141463602720984722315301147001613e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.37570826551286871570751510259375722994082279397834e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.046875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.28793406804333815808719722592608170775411924747170e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.03125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19549068610757913180591372278356498216894586354954e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.015625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.09900254685521936422759033898999181962587095414405e-1), tolerance);
+    BOOST_CHECK_EQUAL(cdf(dist, static_cast<RealType>(0)), static_cast<RealType>(0.5));
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.015625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.90099745314478063577240966101000818037412904585595e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.03125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.80450931389242086819408627721643501783105413645046e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.046875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.71206593195666184191280277407391829224588075252830e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.62429173448713128429248489740624277005917720602166e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.078125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.54128928252324244858536397279015277684698852998387e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.09375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.46290440538810971901075463907912052110770078557001e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.109375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38886999325100940692217415763934459424688336515323e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.31887921568009055676985827521151927561905069756334e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.140625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.25262169970425461499760639161103103516585531687363e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.15625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.18980066583859588646492309993087622866113891170991e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.171875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.13014030144742808960599738063482904351064602625491e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.07338815387886469109799016905025356718337763965952e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.203125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.01931503128208807344707441840522746424640776733482e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.21875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.96771371640645784475148651296909803541218278211201e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.234375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.91839717977573455659490354583900768691773107778703e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.87119665000174806422420129219814480076318292452197e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.28125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.78254859359158098510888509896172431097522748703865e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.70071604494776495147661422048036562690579901259931e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.34375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62483167142022658662698467701475815382565060700827e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55417563843010824151990624091505209837963398189766e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.40625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.48814554885607965224431388327096964758526950639963e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.42623318957604837956085530683032551753868317236287e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.46875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36800649890180441699589040706573844882916813862746e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.31309550000758082761278726632760757082965788779064e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.21198706286302016964660139725707925695690953535621e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.12082296340545811234455810077892380496395042488318e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03800118279447955882543375356729458148212335628057e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.96226648191670403196061310683376239616840103866983e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.89261854625965316722646909500096608624627558333255e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.82824834763715399283433728056507088064285422281461e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76849301027297680034801351032711397512725349083505e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.71280312689343266367958859259591543958449635451967e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.61185078990430196469782036568483593931021694091782e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.52248669635662507718372623246751628200366838868998e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.44257500572741387471454711747681504603506105875273e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37050277816586024016699127500442336442368833061485e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30502444449412087831256855850010593081747948385277e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.24515968592015292591213160991283529212368507398551e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19012422407024648274998126765803685575224367865758e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.13928162275383718405630406427822962549133076160983e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04817161935798121677981868384882359833404907918648e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96860081561627764765290065134912151446894162470366e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89826216632004296533051251749295777627320352902276e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.83545491848533781581075416061045687904524946502798e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77889244858892026253876673752518849640459231269905e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72758003279298484112934948051066338979626419965674e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.68073422703516098355866522837852256596174289760926e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.63772802979087199762340235165979754525757604354946e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.56128979476975492385148278416864732819639719405857e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49516907181984424115787907266071023790635872244406e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43719505582396897943587327026196371508843359861765e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38579268173573883143659925874213063952825602924160e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.33978650604302480708537026993826867238772036875412e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.29827842252435843431840073950159137560805610529836e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.26056837521327410673386744252195759196942946015720e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22610122564874286614786819620499101780828978673850e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16519065397529967010603916749661994058495038701903e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.11285389689081092090080900757256655213056507935765e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06722664628240641657463412013080864534542465320880e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02697048057896404675748265840787538239835533463915e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.91095580948192894243059119812739170064298855954150e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.58851606064421509151228732938834025845710632753865e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.29657717833196446423749763633852786438048712229891e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.03056141356415128156562790092782169373827214514422e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.56233191903709448828683239881723764461808662475751e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.16188637156340219345609662100276117883253664060901e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.81416233095397134117651222065771104114974953207875e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.50842302656587649324679534871796140718152459081608e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.23677655844367661796208750471724232185503310585430e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.99327211922253387063577514052912042212460501121145e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.77332469896087134873409606852930319306153102107748e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.57333571766941514095434647381791053890536948900264e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.22230201122276543582018268125914307770458422539453e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.92306196750274052986046861933822660319647411503460e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66393766871935144778495176368042799313533760396735e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.43664512355365430998504793608427289643995825810352e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.23512057902480812783067842173364430254180391574517e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.05480824780342286194892111115606787981112335506282e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.89220914007246019306457129229565668476439227449653e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74458482861654721048545411630851774084511858223315e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48596753801598503319767014729339663622931424118435e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.26600858175294196667322269091614319302918711248774e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.07590501853150263567490077970815440178521221113294e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90943298811551585430796926339912286222583383628380e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.76204970249877025738751243150107820229031119377257e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.63035057455899788326457066144517427412403198177255e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.51172649975372596610965298504076329424502797908092e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.40413948757894194852726127978788270443438529203793e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43203077043778334466271831424077221758122536074329e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73229441904414627006839605354679934626132938387870e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23125360026260788506665554837055341098621632464561e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.73810855742053432677942037710993481024582345070051e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.19474376202028990304398162068685909212949561120262e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38834786517841980543748022239405103577545566369058e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.10703837128619218169124143528829380601241157169895e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19901414203078529527146967144846039577487804212104e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55594175267868082494169767822936567533407971376816e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10071922510385832628139939726551776872500893306030e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.78577261178721830451003518231079692441875499186244e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.50662913793980803259595258646776816982578828753293e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.89440319684962022373915418699465975439163763242915e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75407315047618220330559697044875151329985165407760e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94758093727122517797618473870421858045294374184298e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37722626166484277233388378972371910745163900023301e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73885317860649699113798763978865018837655503068780e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.88660557570383272842403146191017664814974769956447e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.86966373050763507830869601193566593204764987942763e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44342136111091391837428138940493220527760482550819e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43489115282263847728003495903341128041631655237825e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72174032467196796417055336934387675311978746399112e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21746039858699001180528503217054534969400689600469e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.60877573465331935753972340571396643508918647400950e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08733904872845891588154720869252063263709578283331e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.04367878835689816266760026397728945536920490441769e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184171018215269383027201178304809813110038062619e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60921434092694304578619454290395143640352517265958e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.80460861796838148522601893634284307293180095878460e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230467086052636671801670850090200893179111799503e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51152425899360606075482273396798501430313790237214e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.75576235566956348303137380307065627552780450075955e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788123437797396666202471539368169920940171968838e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894063132478530361545271176786170012121225204887e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.94470319196342264878568431977547823579033279922390e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235160481658539831961233459162678510644673997599e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617580461701122279770683403051652704243983949025e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43087902860685242952854599081275466963995418723234e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951568387529445493346979934712370552753482953e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771975818704991725083904340140685678094729181896e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.28859879179803026143850997564073108091243061664589e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969811127894197045507227361880900936362117960e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424537930446531251492646463803649696387208569e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.45134356135114531072734934087281275202470211834375e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890338181277331789748787296614195690507700714e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845700036860694806306823770374585029986489e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26772431461440436935874981470647001703932928470872e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653610734665125754039671239552191451228014e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403286311621332289317114802389526570992e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54331924158508592432390764336465547336588796613693e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396271716489312806849560623979223766702760e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067943835349195212917512291401637194850e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53643631497669868784011108970123778268444560432089e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417467770730159801145325661085046788106e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669786030013601997303312653750436687e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.65068174215109174689577917816952001659129997288134e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293686425909692485421878259294596496e-20), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_quantile_nearzero() {
+    //
+    // Basic sanity checks, tolerance is either 4 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 4;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.52796721097108753422708089760626414214332697170320e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.56591342761460650504994018321276991271746451691815e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.47218526924747883249737601803820876470332879082284e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.64871492892195438064623231330402224448304864505255e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.49147047287704191198103513188406591369158240312651e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.83944503273842706198239703540854699099743899944658e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.88121977453918311545713678336944882698543050262508e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.28383277518932774280834618691095083936296378494548e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.91036143728268221909726623759154622815926077224027e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.21997830440617027092737461125926863143124423787158e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.31665804788247227155363433182318290115115268840234e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.93390030300024509983060478023436359505370694478274e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.90586867715715827365143687189250571789458607638023e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.12403044179836064404720613683569098344014116798151e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.11633396058323297953641398479658668551534240629654e-2), tolerance);
+    BOOST_CHECK_EQUAL(quantile(dist, static_cast<RealType>(0.5)), static_cast<RealType>(0));
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.50390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14052785123109810231692510348602868600338388040310e-3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23083326042460532375320968182992121472721389674838e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.51171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85291421003937677871303076502465267120545270922005e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.48262870167331460723959759110260709264416995145257e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.51953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.12205802380990657930467930989682569659575359795940e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.77305954522603022893044033304410291628163249182374e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.52734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.43730759016907991505397132799991250199870494073045e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.11633396058323297953641398479658668551534240629654e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.81156327963950319747789851203804452183342931095156e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.52434225749394951914392360992042907273807357938464e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.54296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.25596345497536099309066715771745797836543079457304e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.00768452063066360042362619764345937296973490700293e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.55078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.78074386337778547450756599814721014853736307848400e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.57637357991828558350746829889151355918095876787015e-2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.55859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03958102936522630889618724151593050682836910322233e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12403044179836064404720613683569098344014116798151e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.56640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21111282406179691889755301310617804156919563608730e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30095831353205038001599004861145346134019254008840e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.57421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39370061391699662824182194486817335276363125501648e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48947760819317620418221654282830443278848716355952e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.58203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58843194157470428889620974461757508836357970580066e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69071158647072305786338619311971877757990751767576e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.58984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79647039926214909876835259387875129672714154918583e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90586867715715827365143687189250571789458607638023e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01907372223400262964766551738092686471437958693421e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.13626041895044652657368022843673732366221034591882e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.60546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25761183081873425453317860727230431668344830552276e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.38331982156037948249435913385386178518604561255635e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.61328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51358570582737493855890017214322139090955378416415e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.64862093447749446836087591919859178171321397783436e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.62109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78864781940101196225997767818887450385653350744028e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93390030300024509983060478023436359505370694478274e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.62890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08462477761234306446751675008291773968116735262918e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.24108096043381713255460633677010126705310806557902e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.63671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.40354282984953644763765300071916088017186215793874e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.57229962948879265758087216105113103390988022371525e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.64453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.74765694682819607503814996847853363329594489637064e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.92993787373911729744782959203924101663354892145487e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.11948425704142844251280879133218574177911117813611e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.31665804788247227155363433182318290115115268840234e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.66015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.52184275961932281071152630025400546639852185492776e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.73544504485420224870167294387230375351476906471546e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.66796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.95789640337012040028773901682608788684052806162084e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.18965503395137956448285166074873893264110804474852e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.67578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.43120784446902465897667277460048286927884165223763e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68307263618494854564544144712177429500269729880351e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.68359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.94580048000377446115526240745459082802949048053747e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.21997830440617027092737461125926863143124423787158e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.69140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.50623171706258215659862497663103390044283888606793e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.80522808468923275824853139897350453182651092750420e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.69921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.11767989861122001397308542198440114248503523449816e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.44434845679017252964098546334886010522317885397184e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.70703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.78604789681373771559537778013045202059314559478553e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.14364961859827390982162302693689202778040961541097e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.51808714040276392410190679405041748405632099066392e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.91036143728268221909726623759154622815926077224027e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.72265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.32154681743453457545426144342359967492966930439508e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.75279739912087792579527536186650514912572075425034e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.73046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02053542591698211050464719677242867419786774375833e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06805533335867623214314225100786133910606465280065e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.73828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.11798341618055383937616799179262778846061718089667e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.17047495787852935040070049482482614635865914736031e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.74609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22569764738178929583883189036464601993502267035808e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28383277518932774280834618691095083936296378494548e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75390625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34507656531879179894649466860868632699377270813348e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40964166091862115574755023135179331832042209281055e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.76171875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47775878407059212254277747469428558567366208287249e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54967859343857147744530902523828155595548983145552e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.76953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62567376708606422065437126777269201178590320302836e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70604134209343637939962724226064374287142808011846e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.77734375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79110534768099925573827334628551158224393429767853e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.88121977453918311545713678336944882698543050262508e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97677193016829061858313922289253621707890698703331e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.7890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.07818623846627168681622781867868137142587154742683e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.79296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18592855185448213952914641315720989891399211112618e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30051105624503972344131618629751440966474716683287e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.80078125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42249786355837299731799089007913700561632679250929e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.55251140382947389347453508427822893893843094122006e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.80859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69123974986228153051487214813181004658778348371858e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83944503273842706198239703540854699099743899944658e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.81640625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.99797313731027706223638793579547090613393780037951e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.16776490443789287489784195960321745577830473993117e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.82421875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.34986911285371709243134965339463237363883153982305e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54545757031320957733016491289957363442390624403356e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.83203125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.75584271388037850609173432108976499052095906002965e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.98249820637230758503593250844352437505576086329541e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.83984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22708312477451358281191586486620734769643769191868e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.49147047287704191198103513188406591369158240312651e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.77778092239392917026904003217947497405149113745180e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8515625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.08842290488213149257806983557860643076120157707468e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.85546875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.42614045478507551744169142637868564301201400254633e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.859375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.79407056051931174009446309499422812782537696684469e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.86328125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.19581224082198008577426461565974789703165385453255e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63551016172006234258563545412611777992137495354692e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.87109375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.11795639223606059741678567601858859535625176228939e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.64871492892195438064623231330402224448304864505255e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.87890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.23427499059001976769144078614154782774804457875826e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.88224092195729153863789585576784499265806702821498e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.88671875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60156902856277721120026862113617294726340622812143e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.890625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04028650542151264864039545865194654420659149847715e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.89453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12987606827387901549180798300970689324385087503567e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23043939515379786765482759320371211340959481379476e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90234375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34380276304930757031534891808152959303504163146383e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47218526924747883249737601803820876470332879082284e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.91015625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61830428929231043118455947432627297107033412348157e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78551541642651806413112158903680754166702207111037e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.91796875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97800037388343052469605081868946702260361591387557e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20102262690774549296442657868648686186513838548331e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.92578125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46128002888129351171085541318961326325857070786293e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9296875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76739893404884608939800784860050078072327340444416e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.93359375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13063845566677402478557805956745594172754985803934e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.56591342761460650504994018321276991271746451691815e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.94140625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.09331197973287229185946564870900349250152411988374e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9453125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74040079933008774660558150020826896333899909298154e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.94921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.54582183342592176371744225018671216049948426069910e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.953125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56507752301931033036206963972726950780990330962767e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.95703125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.88016814096703401470072036376924072379132872310869e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.61631402738793734570515994292749381948933242893841e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96484375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.19723988112353634841352379780826428736159712449728e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52796721097108753422708089760626414214332697170320e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.97265625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01231735395463433145333990641210588531111270293944e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9765625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76159370958398793120791299241979313515017333512222e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.98046875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00925470915587723915099888946681205221515647834867e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.984375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.31534559333932129219229424636026382581685146602733e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.98828125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.13177617125304414676334752220512104772421667697176e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9921875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56685855095635428319020462289713380105568378947326e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.99609375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03488985899360430847226178216145298481879311104883e4), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_quantile_lower() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.64871492892195438064623231330402224448304864505255e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.56591342761460650504994018321276991271746451691815e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.52796721097108753422708089760626414214332697170320e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.31534559333932129219229424636026382581685146602733e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.56685855095635428319020462289713380105568378947326e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.03488985899360430847226178216145298481879311104883e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.66560111810464968102166352094329039797553809013180e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.66887306794201818857999976857911823063870328368667e6), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.27176145418643796488192673589719523675773715325372e7), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -16)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.83544414827242601690013182749435284100680743652971e8), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -20)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.74992376775466783667682507089110333268769521176506e11), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -24)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.47981285598233127388251456426050883440628660913084e13), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -28)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.14683221929996578514587273759806303045535542474016e16), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -32)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.93589050191487067535089237582921756933019831739543e18), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -40)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.92406520022739246958562710299618130085960993793414e23), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -48)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.26095536962330863369654555704556352597738045353834e28), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -56)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.26379711036337395023730103376706642065822106379442e32), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -64)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.41576207424774090175793327287164715152292673169682e37), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -80)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.32605209918111709774537445734765990902394758994645e47), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -96)), BOOST_MATH_BIG_CONSTANT(RealType, N, -9.99031769477504631556283515692397586421188586846623e56), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -112)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.29080877757089340022276728331106401823387140732677e66), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -128)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.84288833730567254754590245964397936517161760904520e76), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -160)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.39952895147018642535639799349517299692324064545541e95), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.27102405389367073393026479530690706073270941007595e114), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -224)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.15679975802253118434756797269580371455350883468455e134), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.13391890807707704630144658385551537641074743396505e153), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.13391890807707704630144658385551537641074743396505e153), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -320)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.26134976857812288039693249651849278418162312282066e191), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -384)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.47090928629257240812467048839513197145079590955310e230), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -448)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.40806860386563308738645719151345111937971699513862e268), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_quantile_upper() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.64871492892195438064623231330402224448304864505255e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.56591342761460650504994018321276991271746451691815e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52796721097108753422708089760626414214332697170320e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.31534559333932129219229424636026382581685146602733e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56685855095635428319020462289713380105568378947326e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03488985899360430847226178216145298481879311104883e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66560111810464968102166352094329039797553809013180e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66887306794201818857999976857911823063870328368667e6), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.27176145418643796488192673589719523675773715325372e7), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.83544414827242601690013182749435284100680743652971e8), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74992376775466783667682507089110333268769521176506e11), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_saspoint5_locscale_param() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    saspoint5_distribution<RealType> dist_0_1(static_cast<RealType>(0), static_cast<RealType>(1));
+    saspoint5_distribution<RealType> dist_1_3(static_cast<RealType>(1), static_cast<RealType>(3));
+
+    BOOST_CHECK_CLOSE(entropy(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.6399244456803064957308496039071853510), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_1_3), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.6399244456803064957308496039071853510) + log(static_cast<RealType>(3)), tolerance);
+
+    BOOST_CHECK_EQUAL(median(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(median(dist_1_3), static_cast<RealType>(1));
+
+    BOOST_CHECK_EQUAL(mode(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(mode(dist_1_3), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.61071469126041183247373313827161939453635781053656e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.36619772367581343075535053490057448137838582961826e-1) / 3, tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86071837724616281594369593572177037450866923839017e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86071837724616281594369593572177037450866923839017e-1), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp64)
+{
+    do_test_saspoint5_pdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp128)
+{
+    do_test_saspoint5_pdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
+{
+    do_test_saspoint5_cdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp128)
+{
+    do_test_saspoint5_cdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
+{
+    do_test_saspoint5_ccdf<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp128)
+{
+    do_test_saspoint5_ccdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
+{
+    do_test_saspoint5_quantile_nearzero<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp128)
+{
+    do_test_saspoint5_quantile_nearzero<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
+{
+    do_test_saspoint5_quantile_lower<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp128)
+{
+    do_test_saspoint5_quantile_lower<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
+{
+    do_test_saspoint5_quantile_upper<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp128)
+{
+    do_test_saspoint5_quantile_upper<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
+{
+    do_test_saspoint5_locscale_param<double, 53>();
+}
+
+BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp128)
+{
+    do_test_saspoint5_locscale_param<cpp_bin_float_quad, 113>();
+}

From 8b675ac5565e63f3d8e3c7edb3ac088f3f5da28d Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 23:28:15 +0900
Subject: [PATCH 004/399] Add saspoint5 limit test case

---
 test/test_saspoint5.cpp | 250 +++++++++++++++++++++++-----------------
 1 file changed, 142 insertions(+), 108 deletions(-)

diff --git a/test/test_saspoint5.cpp b/test/test_saspoint5.cpp
index 97a7c43ad5..f66fcbfaec 100644
--- a/test/test_saspoint5.cpp
+++ b/test/test_saspoint5.cpp
@@ -164,60 +164,77 @@ void do_test_saspoint5_pdf(){
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.63180321475387230691526892287847669196997380044025e-5), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66189768326912251607424407981263646223230063365226e-5), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.93708011998897739786377954224930716533616609090213e-6), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.11452967162743112245198615236484567129951718982008e-6), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.51482080833564338340856966996445313498079083789150e-7), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66663174159211670027542189178751103023898387998523e-7), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.45238046039194445466823557091765258247216574897413e-8), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.34803516847185617806978815778928715951216310353916e-8), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18523956611649861747653810989133680515605456258881e-8), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19428394481581920558479056092124822410228982935516e-9), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48386121491270229946980639019289494044106626390164e-9), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.24863743761365464204033370116809431054495238229389e-10), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85627269567198410070703889816912945617135110666962e-10), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56441321254434701892659687588069630508140502616495e-11), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32124514546671241752437061147193743959791071682877e-11), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.20777750941928700289773286319085009877829580100394e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90212173401654051439660118394241371322264056105160e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02611352372467016891796952205325499928128114461973e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62800552193521241168029742332979605534754328327140e-13), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28273024622868202243706785685607188210679822726442e-13), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53522776159999787175268870767580373267754737032134e-14), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60346802350897629386145672448930505388450307742542e-14), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66917274294807913528606004426646232913424627695599e-15), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00436953991320274750778716874695704836278902566390e-15), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08655220551513998962815689594959332706015306211632e-16), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85824418029941626524148561830736428793658611772587e-17), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728389276235510083072832489179009106826041868534e-17), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410697234730043795694534456878302211221269628364e-18), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013503193177856102694285471291153594530345945373e-19), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16266961272612513551592941445333504133461857377298e-20), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333753016489787852265460543736089676535476354358e-21), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917223411693427580584068017775560157489239248184e-22), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396549352793655444565334974277876088154820156655e-23), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995699246102965377026386970340969776925728507708e-24), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994631904573126677044584818697892085174708564778e-25), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993294785056705165902599588868178759415543962830e-26), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162154653357770314062605026847259176035189343e-26), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905202884892491063675049720005913844624989838025e-27), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503725850485091152332729977897011733755140179e-28), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379732147400935170577498436447103578962194983e-29), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974711955685286218349809111390785355323964808e-30), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460542241032622871979569574240917519314612402e-32), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907118661876897809516737349031422411025903664e-34), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604881272566803193825546858269428369981726767e-36), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013025533256374121391266749023560191365933e-37), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198457980010827684344075634340204878641095256e-39), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590643616572397339764831428700168401193312e-41), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797900123415519497865404920881954749456838e-43), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809226549290322908699069488543719245241219e-45), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220191945453705676879390798465474357652431e-46), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550030836685714809779087770458087234145e-48), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609468520317755439405311521523337977429e-50), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327312273151307737011597702780857146510e-52), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636432344828142894916983611711484679173e-54), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442824114913911543137689436308410131e-55), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254518240301652494105481741383790265e-57), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522725985138779564208904631966988869e-59), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.11452967162743112245198615236484567129951718982008e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.51482080833564338340856966996445313498079083789150e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.66663174159211670027542189178751103023898387998523e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.45238046039194445466823557091765258247216574897413e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.34803516847185617806978815778928715951216310353916e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18523956611649861747653810989133680515605456258881e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19428394481581920558479056092124822410228982935516e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48386121491270229946980639019289494044106626390164e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.24863743761365464204033370116809431054495238229389e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85627269567198410070703889816912945617135110666962e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56441321254434701892659687588069630508140502616495e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32124514546671241752437061147193743959791071682877e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 23)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.20777750941928700289773286319085009877829580100394e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90212173401654051439660118394241371322264056105160e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02611352372467016891796952205325499928128114461973e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62800552193521241168029742332979605534754328327140e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28273024622868202243706785685607188210679822726442e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53522776159999787175268870767580373267754737032134e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 29)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60346802350897629386145672448930505388450307742542e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66917274294807913528606004426646232913424627695599e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00436953991320274750778716874695704836278902566390e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08655220551513998962815689594959332706015306211632e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85824418029941626524148561830736428793658611772587e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728389276235510083072832489179009106826041868534e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410697234730043795694534456878302211221269628364e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013503193177856102694285471291153594530345945373e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 42)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16266961272612513551592941445333504133461857377298e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333753016489787852265460543736089676535476354358e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 46)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917223411693427580584068017775560157489239248184e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396549352793655444565334974277876088154820156655e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 50)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995699246102965377026386970340969776925728507708e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994631904573126677044584818697892085174708564778e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 54)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993294785056705165902599588868178759415543962830e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162154653357770314062605026847259176035189343e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 58)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905202884892491063675049720005913844624989838025e-27), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503725850485091152332729977897011733755140179e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 62)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379732147400935170577498436447103578962194983e-29), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974711955685286218349809111390785355323964808e-30), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 68)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460542241032622871979569574240917519314612402e-32), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907118661876897809516737349031422411025903664e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 76)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604881272566803193825546858269428369981726767e-36), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013025533256374121391266749023560191365933e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 84)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198457980010827684344075634340204878641095256e-39), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590643616572397339764831428700168401193312e-41), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 92)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797900123415519497865404920881954749456838e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809226549290322908699069488543719245241219e-45), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 100)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220191945453705676879390798465474357652431e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550030836685714809779087770458087234145e-48), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 108)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609468520317755439405311521523337977429e-50), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327312273151307737011597702780857146510e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 116)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636432344828142894916983611711484679173e-54), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442824114913911543137689436308410131e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 124)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254518240301652494105481741383790265e-57), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522725985138779564208904631966988869e-59), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522725985138779564208904631966988869e-59), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 136)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.75819970600899713717946709855764494008629724492550e-63), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89409172509985281669900618169013228855150809470644e-66), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.62424737573206254076979053560233289660261329999266e-70), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 160)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12896664446583558124263581916004539046704057066258e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 168)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75626622184041889951815556079707845048600270288339e-77), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 176)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.72916558066508520390174723482957902400087321179181e-81), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 184)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64286269059206181735882501247406923061001590063666e-84), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.01089524070327592128619387871640956557675279607402e-88), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 200)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.79222470874823222970262177430243561283276571668161e-92), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 208)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.39067986053423638420474164411821626475827252277446e-95), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.83662075325741304737485752958570418264028678048960e-99), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 224)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.42495623858823560726925232655901309474567221057157e-102), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 232)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.47889706686580958805969806288821606452354641951732e-106), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 240)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.49340104215285543959887222384818382775213055976161e-110), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 248)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.07358423880684947255831841402543550598919723533894e-113), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.06246152052453484511308206549178590347199333203433e-117), tolerance);
 }
 
 template<class RealType, int N>
@@ -485,60 +502,77 @@ void do_test_saspoint5_ccdf() {
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43203077043778334466271831424077221758122536074329e-2), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73229441904414627006839605354679934626132938387870e-2), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23125360026260788506665554837055341098621632464561e-2), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.73810855742053432677942037710993481024582345070051e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.19474376202028990304398162068685909212949561120262e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38834786517841980543748022239405103577545566369058e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.10703837128619218169124143528829380601241157169895e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19901414203078529527146967144846039577487804212104e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55594175267868082494169767822936567533407971376816e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10071922510385832628139939726551776872500893306030e-3), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.78577261178721830451003518231079692441875499186244e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.50662913793980803259595258646776816982578828753293e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.89440319684962022373915418699465975439163763242915e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75407315047618220330559697044875151329985165407760e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94758093727122517797618473870421858045294374184298e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37722626166484277233388378972371910745163900023301e-4), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73885317860649699113798763978865018837655503068780e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.88660557570383272842403146191017664814974769956447e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.86966373050763507830869601193566593204764987942763e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44342136111091391837428138940493220527760482550819e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43489115282263847728003495903341128041631655237825e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72174032467196796417055336934387675311978746399112e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21746039858699001180528503217054534969400689600469e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.60877573465331935753972340571396643508918647400950e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08733904872845891588154720869252063263709578283331e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.04367878835689816266760026397728945536920490441769e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184171018215269383027201178304809813110038062619e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60921434092694304578619454290395143640352517265958e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.80460861796838148522601893634284307293180095878460e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230467086052636671801670850090200893179111799503e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51152425899360606075482273396798501430313790237214e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.75576235566956348303137380307065627552780450075955e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788123437797396666202471539368169920940171968838e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894063132478530361545271176786170012121225204887e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.94470319196342264878568431977547823579033279922390e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235160481658539831961233459162678510644673997599e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617580461701122279770683403051652704243983949025e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43087902860685242952854599081275466963995418723234e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951568387529445493346979934712370552753482953e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771975818704991725083904340140685678094729181896e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.28859879179803026143850997564073108091243061664589e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969811127894197045507227361880900936362117960e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424537930446531251492646463803649696387208569e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.45134356135114531072734934087281275202470211834375e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890338181277331789748787296614195690507700714e-13), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845700036860694806306823770374585029986489e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26772431461440436935874981470647001703932928470872e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653610734665125754039671239552191451228014e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403286311621332289317114802389526570992e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54331924158508592432390764336465547336588796613693e-16), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396271716489312806849560623979223766702760e-17), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067943835349195212917512291401637194850e-17), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53643631497669868784011108970123778268444560432089e-18), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417467770730159801145325661085046788106e-18), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669786030013601997303312653750436687e-19), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.65068174215109174689577917816952001659129997288134e-20), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293686425909692485421878259294596496e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.73810855742053432677942037710993481024582345070051e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.19474376202028990304398162068685909212949561120262e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.38834786517841980543748022239405103577545566369058e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.10703837128619218169124143528829380601241157169895e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19901414203078529527146967144846039577487804212104e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55594175267868082494169767822936567533407971376816e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10071922510385832628139939726551776872500893306030e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.78577261178721830451003518231079692441875499186244e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.50662913793980803259595258646776816982578828753293e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.89440319684962022373915418699465975439163763242915e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75407315047618220330559697044875151329985165407760e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94758093727122517797618473870421858045294374184298e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 23))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37722626166484277233388378972371910745163900023301e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73885317860649699113798763978865018837655503068780e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.88660557570383272842403146191017664814974769956447e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.86966373050763507830869601193566593204764987942763e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44342136111091391837428138940493220527760482550819e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.43489115282263847728003495903341128041631655237825e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 29))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72174032467196796417055336934387675311978746399112e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21746039858699001180528503217054534969400689600469e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.60877573465331935753972340571396643508918647400950e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08733904872845891588154720869252063263709578283331e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.04367878835689816266760026397728945536920490441769e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184171018215269383027201178304809813110038062619e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60921434092694304578619454290395143640352517265958e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.80460861796838148522601893634284307293180095878460e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 42))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230467086052636671801670850090200893179111799503e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51152425899360606075482273396798501430313790237214e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 46))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.75576235566956348303137380307065627552780450075955e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788123437797396666202471539368169920940171968838e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 50))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894063132478530361545271176786170012121225204887e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.94470319196342264878568431977547823579033279922390e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 54))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235160481658539831961233459162678510644673997599e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617580461701122279770683403051652704243983949025e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 58))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.43087902860685242952854599081275466963995418723234e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951568387529445493346979934712370552753482953e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 62))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771975818704991725083904340140685678094729181896e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.28859879179803026143850997564073108091243061664589e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 68))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969811127894197045507227361880900936362117960e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424537930446531251492646463803649696387208569e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 76))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.45134356135114531072734934087281275202470211834375e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890338181277331789748787296614195690507700714e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 84))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845700036860694806306823770374585029986489e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26772431461440436935874981470647001703932928470872e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 92))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653610734665125754039671239552191451228014e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403286311621332289317114802389526570992e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 100))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.54331924158508592432390764336465547336588796613693e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396271716489312806849560623979223766702760e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 108))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067943835349195212917512291401637194850e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.53643631497669868784011108970123778268444560432089e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 116))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417467770730159801145325661085046788106e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669786030013601997303312653750436687e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 124))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.65068174215109174689577917816952001659129997288134e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293686425909692485421878259294596496e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293686425909692485421878259294596496e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 136))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.35166902221110808556756707276211088178619562345223e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44793138881942553480799933647572308735410707938645e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995711801214095925541775450484763569750411131894e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.29997319875758809953465243130019854989301769477462e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 168))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06248324922349256220915840763819709280743596647028e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 176))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905203076468285138072402969870025328294044417034e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 184))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.05657519227926782112952519535313715734583596556713e-29), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.03535949517454238820595324747603340202581381400690e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 200))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.14709968448408899262872077968737723090225341248585e-31), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 208))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96693730280255562039295048730519109566688181166036e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22933581425159726274559405456576710378996415685244e-33), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.68334883907248289215996284103605325376468341179834e-35), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 232))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.80209302442030180759997677564753362950438836016578e-36), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 240))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00130814026268862974998548477970853195201855431423e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 248))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87581758766418039359374092798731783299781533977493e-38), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.17238599229011274599608807999207364564425192108311e-39), tolerance);
 }
 
 template<class RealType, int N>

From 098ded39b06745b892abae72755eea6b2a8b95f1 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 23:34:31 +0900
Subject: [PATCH 005/399] Add holtsmark limit test case

---
 test/test_holtsmark.cpp | 250 +++++++++++++++++++++++-----------------
 1 file changed, 142 insertions(+), 108 deletions(-)

diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index 8f34124d14..ad81478f11 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -132,60 +132,77 @@ void do_test_holtsmark_pdf(){
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85568203412051586615998003517909621954036193765824e-7), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.04563780918059698346140819518179336362098891429611e-8), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.91792339891869109849236922708731694322153177924824e-9), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57638176923363231335450711092364627257129748508825e-9), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78661356398095539721893167504764083609118624639856e-10), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.92604459926540711296353370623384343787650705186643e-11), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70807462044367666228538283653300633948804226008283e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53938313936621297172285881159282265471330118114236e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72126969520581558576219170420297785383800313247716e-13), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.81057004571925961169117504945825287978291651680376e-14), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.50396638201843310535816082381660912483279969324341e-15), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50330305081854272655464104542050109297998338121296e-15), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65748943908780839905864199570025333227786061957216e-16), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.69782199924985143903444545973473854205301886566784e-17), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.30465447555059221873312238790689561215989143051468e-18), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46806937341565301230797169380667244412810953871153e-18), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.59520452276585659227559942516968833301265805493281e-19), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58771679139660099100514647692148711295768774585921e-20), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.11001413331373018059574227843565648889473010676660e-21), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43366149729083958029796238740037446793377590904146e-21), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.53437941664766678806680232945039585344994407777604e-22), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48019217902582750507529988918628139079404963189635e-23), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.91993567701892984811136675864172386794777828712695e-24), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40006005594525679129869441468227938628239752074460e-24), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.47497989906821913751146663525981445654490373951224e-25), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.73431218458810807033921781897016124929992555367139e-27), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.41697255768378077454412606000376285104775580444420e-28), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55303924276181374957661287953452523234530316565188e-30), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36032476336306675100543445227730858361169873925804e-31), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37601488550958357902586661939110889053699438042016e-33), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30500465172174486774768816059192932509423715417166e-34), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20313953663045271143891020576861031160487434865093e-36), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25098110519701647231401040429952006498171313622520e-37), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03431595374067647597712273413788666502302011992057e-39), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19822373554396139874268836303925702273981755123190e-40), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.86944917357487937107083766130282172728072819621788e-42), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14670286674214980345963428973545770896346187182759e-43), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.70844645856921813581135618689921390269372237700480e-45), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09638951830288066744104877057303202280205793138993e-46), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55121724469650208575327739326222025805731763269349e-48), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04725538896765690179789918481715848637732139291593e-49), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.99927284078872744316201092259372825667966088624440e-52), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95241488358274164371290129159422806319923560612665e-55), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90665515974877113643838016757246988460215123083510e-58), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86196792944215931292810563239498984002947733280447e-61), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.81832805609585870403135315663573226135611325562940e-64), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77571099228111201565561831702708228641500206234884e-67), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73409276589952345278868976272176004532614982149466e-70), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69344996669875337186395484640796879426380291665101e-73), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65375973310425133971089340469528202564824480281467e-76), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61499973935962044893641934052273635317211406169375e-79), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57714818296837934466447201222923471989464263831856e-82), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54018377243005795377389844944261203114711195148214e-85), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50408571526372847048232270453380081166710151511926e-88), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46883370631223483445539326614628985514365382335866e-91), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43440791632054183052284498647098618666372443687369e-94), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40078898078177913136996580710057244791379339538446e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57638176923363231335450711092364627257129748508825e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.78661356398095539721893167504764083609118624639856e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.92604459926540711296353370623384343787650705186643e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.70807462044367666228538283653300633948804226008283e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.53938313936621297172285881159282265471330118114236e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72126969520581558576219170420297785383800313247716e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.81057004571925961169117504945825287978291651680376e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.50396638201843310535816082381660912483279969324341e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50330305081854272655464104542050109297998338121296e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65748943908780839905864199570025333227786061957216e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.69782199924985143903444545973473854205301886566784e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.30465447555059221873312238790689561215989143051468e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 23)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46806937341565301230797169380667244412810953871153e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.59520452276585659227559942516968833301265805493281e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58771679139660099100514647692148711295768774585921e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.11001413331373018059574227843565648889473010676660e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43366149729083958029796238740037446793377590904146e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.53437941664766678806680232945039585344994407777604e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 29)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48019217902582750507529988918628139079404963189635e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.91993567701892984811136675864172386794777828712695e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40006005594525679129869441468227938628239752074460e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.47497989906821913751146663525981445654490373951224e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.73431218458810807033921781897016124929992555367139e-27), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.41697255768378077454412606000376285104775580444420e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55303924276181374957661287953452523234530316565188e-30), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36032476336306675100543445227730858361169873925804e-31), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 42)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37601488550958357902586661939110889053699438042016e-33), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.30500465172174486774768816059192932509423715417166e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 46)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20313953663045271143891020576861031160487434865093e-36), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25098110519701647231401040429952006498171313622520e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 50)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03431595374067647597712273413788666502302011992057e-39), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19822373554396139874268836303925702273981755123190e-40), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 54)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.86944917357487937107083766130282172728072819621788e-42), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.14670286674214980345963428973545770896346187182759e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 58)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.70844645856921813581135618689921390269372237700480e-45), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09638951830288066744104877057303202280205793138993e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 62)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55121724469650208575327739326222025805731763269349e-48), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.04725538896765690179789918481715848637732139291593e-49), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 68)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.99927284078872744316201092259372825667966088624440e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95241488358274164371290129159422806319923560612665e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 76)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90665515974877113643838016757246988460215123083510e-58), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86196792944215931292810563239498984002947733280447e-61), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 84)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.81832805609585870403135315663573226135611325562940e-64), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77571099228111201565561831702708228641500206234884e-67), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 92)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73409276589952345278868976272176004532614982149466e-70), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69344996669875337186395484640796879426380291665101e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 100)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65375973310425133971089340469528202564824480281467e-76), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61499973935962044893641934052273635317211406169375e-79), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 108)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57714818296837934466447201222923471989464263831856e-82), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54018377243005795377389844944261203114711195148214e-85), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 116)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50408571526372847048232270453380081166710151511926e-88), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.46883370631223483445539326614628985514365382335866e-91), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 124)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43440791632054183052284498647098618666372443687369e-94), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40078898078177913136996580710057244791379339538446e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40078898078177913136996580710057244791379339538446e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 136)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.33589647367647088181492405614907498160724010027357e-103), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.27401015632292831593983083357722757492755899455411e-109), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21499076492588836282713969571802861683612727599536e-115), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 160)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.15870548718060337336267442294886457141506888961350e-121), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 168)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10502766340313279472606127066503960744387520753240e-127), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 176)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05383650150597838852506758753303490394961853745690e-133), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 184)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.00501680517766798832422980073264589686357358689966e-139), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.58458714654605854343633461697240731109212481403024e-146), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 200)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.14057459501844267219193898865929347142422181513809e-152), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 208)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.71713122846454875201410197130135867254659825815019e-158), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.31330416532950282288942525034080378775272203269023e-164), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 224)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.92818466694784433640425229105072382712623790043853e-170), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 232)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.56090609259399827614236096482345946037887373012402e-176), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 240)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.21064194926643207182155701143594690359008191120531e-182), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 248)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.87660403181689459974437428611368837698944274063617e-188), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55804064923943958258092335330361211489624284804933e-194), tolerance);
 }
 
 template<class RealType, int N>
@@ -389,60 +406,77 @@ void do_test_holtsmark_ccdf() {
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.87179879353850251536193247663317269917137569329013e-5), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.72200715673082274403568012456413425331659480927047e-5), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.08767256634253255597053159005214917567906016620942e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15224951834965340756402503731619739933629215689572e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60926645137475638433041259135060814007792759468100e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69027136710097153757239920401079588116557633592788e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51153240121827639330112195094153363441740650435701e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36283287602527689849064009106938913094716520594050e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894075854698171408179022464997418218329601220535e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.20354010552543796231728241342645692784842686349965e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617582449547816069323420820736862370145659607645e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25442497729649541267939242007563203416972765165476e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771976129306035185873711236944017216967773980517e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56803119746276025902637885330726865801883592203156e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969859659307190062902673645385449168267230206e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.21003899305378486738410997502574389330326609057126e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90268712277390815798081242324390081166198190434103e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02625487407274396069298698869802596448489279633645e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890339366126281650716118851052269284048205938e-13), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28281859258171445903392888079435183340041265714998e-13), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53544862923055721373031196622890601888700626111182e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60352324072570315319362346398633880353985161880622e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653639661641440656550426788294070266782671e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00440405090690395389846895694672344247801107283103e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08663848317021453602605776312368607691806298813143e-16), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396272422714320494875293186097734524880995e-17), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728726299533984178525425523566315206520781873938e-17), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417469494912307476988489629927133322828e-18), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013634843021835192352185216943643167993641440545e-19), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293728520200407227686276581114275508e-20), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333804442221617119725245647479628568092558840977e-21), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917255552777021393262025049731570198920941773050e-22), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396569440971276740578385685661655637545268535833e-23), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995711801214095925566865602936005935821644314758e-24), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994639751517619906934188799897966230541134026964e-25), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993299689397024883663924561783076352358304956329e-26), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162461174628110457931016502737959110130110786e-26), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905203076468285138072404465359649544991622324619e-27), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503845585356422590504127751316165005771606733e-28), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379806981695528238129932509731805283190086691e-29), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974758727119410297662380140381412701796292469e-30), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460560511124078590097461169759773383672872924e-32), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907125798631372797027282887330061342582520339e-34), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604884060361519995355129506804305208883665969e-36), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013134431487499274238985426822797191535889e-37), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198458022549199217615998414729133523646527342e-39), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590660233123777524997523014264365635070860e-41), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797906614255902382808629709787906142136400e-43), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809229084774847473138483921543599314796577e-45), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220192044496069917677888112741187383092503e-46), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550069525109246371700176158105285841693e-48), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609483632983197455781525247039509121778e-50), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327318176536246024658633198499233002634e-52), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636434650837884413529114372655051566613e-54), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442914193419439613924120727351807283e-55), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254553427217874396756438636487198880e-57), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522739730027928744931935369511248250e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15224951834965340756402503731619739933629215689572e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60926645137475638433041259135060814007792759468100e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.69027136710097153757239920401079588116557633592788e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51153240121827639330112195094153363441740650435701e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.36283287602527689849064009106938913094716520594050e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18894075854698171408179022464997418218329601220535e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.20354010552543796231728241342645692784842686349965e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48617582449547816069323420820736862370145659607645e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.25442497729649541267939242007563203416972765165476e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.85771976129306035185873711236944017216967773980517e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.56803119746276025902637885330726865801883592203156e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.32214969859659307190062902673645385449168267230206e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 23))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.21003899305378486738410997502574389330326609057126e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90268712277390815798081242324390081166198190434103e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.02625487407274396069298698869802596448489279633645e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.62835890339366126281650716118851052269284048205938e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28281859258171445903392888079435183340041265714998e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.53544862923055721373031196622890601888700626111182e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 29))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60352324072570315319362346398633880353985161880622e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.66931078653639661641440656550426788294070266782671e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.00440405090690395389846895694672344247801107283103e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08663848317021453602605776312368607691806298813143e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.85829810396272422714320494875293186097734524880995e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10728726299533984178525425523566315206520781873938e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38410907874417469494912307476988489629927133322828e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73013634843021835192352185216943643167993641440545e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 42))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16267043553777293728520200407227686276581114275508e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.70333804442221617119725245647479628568092558840977e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 46))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.37917255552777021393262025049731570198920941773050e-22), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22396569440971276740578385685661655637545268535833e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 50))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.27995711801214095925566865602936005935821644314758e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.59994639751517619906934188799897966230541134026964e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 54))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.24993299689397024883663924561783076352358304956329e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03124162461174628110457931016502737959110130110786e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 58))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28905203076468285138072404465359649544991622324619e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61131503845585356422590504127751316165005771606733e-28), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 62))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01414379806981695528238129932509731805283190086691e-29), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51767974758727119410297662380140381412701796292469e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 68))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.93387460560511124078590097461169759773383672872924e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.14667907125798631372797027282887330061342582520339e-34), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 76))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.60418604884060361519995355129506804305208883665969e-36), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.50065407013134431487499274238985426822797191535889e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 84))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.34477198458022549199217615998414729133523646527342e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66370622590660233123777524997523014264365635070860e-41), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 92))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72454097797906614255902382808629709787906142136400e-43), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.94459527809229084774847473138483921543599314796577e-45), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 100))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.39759301220192044496069917677888112741187383092503e-46), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18373908156550069525109246371700176158105285841693e-48), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 108))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.41209231494609483632983197455781525247039509121778e-50), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.33139424210327318176536246024658633198499233002634e-52), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 116))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.33030350328636434650837884413529114372655051566613e-54), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30160992238849442914193419439613924120727351807283e-55), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 124))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03376550373202254553427217874396756438636487198880e-57), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522739730027928744931935369511248250e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17775859958128522739730027928744931935369511248250e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 136))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.75819970600899713720044013497912431482835720820923e-63), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89409172509985281669932620482888777217489189653546e-66), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.62424737573206254076983936725802678753635716927602e-70), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12896664446583558124263656427197919617586844953028e-73), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 168))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.75626622184041889951815567449213670941374133186103e-77), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 176))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.72916558066508520390174725217806813821714192348884e-81), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 184))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64286269059206181735882501273878616655691941491427e-84), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.01089524070327592128619387875680216444560404031804e-88), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 200))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.79222470874823222970262177430859903429102548905771e-92), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 208))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.39067986053423638420474164411831031110620739478948e-95), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.83662075325741304737485752958571853297413914743525e-99), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.42495623858823560726925232655901331371438944029181e-102), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 232))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.47889706686580958805969806288821609793552109446243e-106), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 240))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.49340104215285543959887222384818383285039329702741e-110), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 248))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.07358423880684947255831841402543550606699055103208e-113), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.06246152052453484511308206549178590348386364998067e-117), tolerance);
 
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 600))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.35984768491636685338723260976696756010081951066709e-272), tolerance);
 

From 681ee060ecbf87037627d06a5ec6cd7f79f473f8 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 16 Jul 2024 23:43:12 +0900
Subject: [PATCH 006/399] Add mapairy limit test case

---
 test/test_mapairy.cpp | 250 ++++++++++++++++++++++++------------------
 1 file changed, 142 insertions(+), 108 deletions(-)

diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index 8f5b98d587..ccae24c30f 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -163,60 +163,77 @@ void do_test_mapairy_pdf(){
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.70691063363569289518344600523741530561019748614806e-7), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.00884949274594535609095332297684714775260624951825e-7), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78341094639115825398956813042728307580960455542744e-8), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15265496830848341113806943808080759239756631409525e-9), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.57315927453204720744811655603371636021315489208197e-10), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.85204679078224624495444948682547526667095102524654e-11), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16384)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74161227361870459284450362091832192677055853279409e-11), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32768)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.07876462219180661771716253718191722284989080940137e-12), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(65536)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.44253835507444012610805302754717855328014016707006e-13), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(131072)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.62113944435292862305033337145279742309373660330666e-14), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(262144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70079323596084060715031479698836179832962876226040e-14), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(524288)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00660607636030744539992938919621601865776189138704e-15), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1048576)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.31497886237763070924617652541844323609885629317601e-16), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2097152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.39564398862596160919395415621974601387332621717152e-17), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4194304)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66093089449300961525223017779109302708950139673730e-17), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8388608)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93613874644561300698599726959494859627890174964948e-18), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16777216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19040904529065504857204743126112225011195501281143e-19), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(33554432)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.17543358264254064703206600829360293655988827362640e-20), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(67108864)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62200282665332970268320245960144424095679956397013e-20), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.34217728e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86732299457579395219850121616992176031753071031156e-21), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.68435456e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.06875883329165532088522436776488158979648490753308e-22), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.36870912e8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.96038435804935610062036418083267399916819002834560e-23), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.073741824e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58398713540364228777663367294171284220596445493878e-23), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.147483648e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80012011189042378144386404030074611545380892760386e-24), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.294967296e9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.94995979813638214930198027960375045149298281432705e-25), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7179869184e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54686243691761942165686883762842249372631955082800e-26), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.8719476736e10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.83394511536756069267771511760113721074800848019252e-28), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.74877906944e11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51060784855236271646178597425041551955920802058680e-29), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.099511627776e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.72064952672613348894308116953255143520457854922274e-31), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.398046511104e12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47520297710191671529471286547892233784021035466379e-32), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.7592186044416e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.61000930344348973529597770462163230645079307893137e-34), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.0368744177664e13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44062790732609054227999303269426009576929146861433e-35), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.81474976710656e14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.50196221039403294462497822716956279927920276478346e-37), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125899906842624e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40686319074813529519530569599048837477475167906008e-38), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.503599627370496e15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.39644747108792279748533029997027617117109903686087e-40), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8014398509481984e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37388983471497587421416571874071130349096844921335e-41), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.2057594037927936e16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.29340573348429960691926787106472282340927640380120e-43), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.88230376151711744e17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34168929171384362716227120970772588231539887618792e-44), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.152921504606846976e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19277903660576133488209753033664338223562148808726e-46), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.611686018427387904e18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31024344893930041715065547823020105694863171502727e-47), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.8446744073709551616e19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.09451077793531380359579836946937830296447410946021e-49), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.95147905179352825856e20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99854568157745488632402184518493974898874424751974e-52), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.722366482869645213696e21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90482976716548328742580258318841772362182055421850e-55), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5557863725914323419136e22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.81331031949754227287676033514493918322443413497900e-58), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.208925819614629174706176e24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72393585888431862585621126478997967111761145994043e-61), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.9342813113834066795298816e25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.63665611219171740806270631327146452257579244134808e-64), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.09485009821345068724781056e26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55142198456222403131123663405416457282792230600398e-67), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.951760157141521099596496896e27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46818553179904690557737952544352009065226787695701e-70), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.9228162514264337593543950336e28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.38689993339750674372790969281593758852760534859083e-73), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.267650600228229401496703205376e30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.30751946620850267942178680939056405129648959823324e-76), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.0282409603651670423947251286016e31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22999947871924089787283868104547270634422812327464e-79), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.24518553658426726783156020576256e32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15429636593675868932894402445846943978928527663539e-82), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.192296858534827628530496329220096e33)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08036754486011590754779689888522406229422390296425e-85), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00817143052745694096464540906760162333420303023853e-88), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93766741262446966891078653229257971028730764671731e-91), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86881583264108366104568997294197237332744887374738e-94), tolerance);
-    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80157796156355826273993161420114489582758679076892e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15265496830848341113806943808080759239756631409525e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.57315927453204720744811655603371636021315489208197e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.85204679078224624495444948682547526667095102524654e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74161227361870459284450362091832192677055853279409e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.07876462219180661771716253718191722284989080940137e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.44253835507444012610805302754717855328014016707006e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.62113944435292862305033337145279742309373660330666e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70079323596084060715031479698836179832962876226040e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00660607636030744539992938919621601865776189138704e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.31497886237763070924617652541844323609885629317601e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.39564398862596160919395415621974601387332621717152e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66093089449300961525223017779109302708950139673730e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 23)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93613874644561300698599726959494859627890174964948e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.19040904529065504857204743126112225011195501281143e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.17543358264254064703206600829360293655988827362640e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.62200282665332970268320245960144424095679956397013e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86732299457579395219850121616992176031753071031156e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.06875883329165532088522436776488158979648490753308e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 29)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.96038435804935610062036418083267399916819002834560e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58398713540364228777663367294171284220596445493878e-23), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80012011189042378144386404030074611545380892760386e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.94995979813638214930198027960375045149298281432705e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54686243691761942165686883762842249372631955082800e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.83394511536756069267771511760113721074800848019252e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51060784855236271646178597425041551955920802058680e-29), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.72064952672613348894308116953255143520457854922274e-31), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 42)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.47520297710191671529471286547892233784021035466379e-32), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.61000930344348973529597770462163230645079307893137e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 46)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44062790732609054227999303269426009576929146861433e-35), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.50196221039403294462497822716956279927920276478346e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 50)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40686319074813529519530569599048837477475167906008e-38), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.39644747108792279748533029997027617117109903686087e-40), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 54)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37388983471497587421416571874071130349096844921335e-41), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.29340573348429960691926787106472282340927640380120e-43), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 58)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34168929171384362716227120970772588231539887618792e-44), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.19277903660576133488209753033664338223562148808726e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 62)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31024344893930041715065547823020105694863171502727e-47), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.09451077793531380359579836946937830296447410946021e-49), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 68)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99854568157745488632402184518493974898874424751974e-52), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.90482976716548328742580258318841772362182055421850e-55), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 76)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.81331031949754227287676033514493918322443413497900e-58), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72393585888431862585621126478997967111761145994043e-61), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 84)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.63665611219171740806270631327146452257579244134808e-64), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.55142198456222403131123663405416457282792230600398e-67), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 92)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46818553179904690557737952544352009065226787695701e-70), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.38689993339750674372790969281593758852760534859083e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 100)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.30751946620850267942178680939056405129648959823324e-76), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22999947871924089787283868104547270634422812327464e-79), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 108)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.15429636593675868932894402445846943978928527663539e-82), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08036754486011590754779689888522406229422390296425e-85), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 116)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00817143052745694096464540906760162333420303023853e-88), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.93766741262446966891078653229257971028730764671731e-91), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 124)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.86881583264108366104568997294197237332744887374738e-94), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80157796156355826273993161420114489582758679076892e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80157796156355826273993161420114489582758679076892e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 136)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.67179294735294176362984811229814996321448020054714e-103), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.54802031264585663187966166715445514985511798910822e-109), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42998152985177672565427939143605723367225455199072e-115), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 160)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31741097436120674672534884589772914283013777922699e-121), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 168)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21005532680626558945212254133007921488775041506480e-127), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 176)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.10767300301195677705013517506606980789923707491379e-133), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 184)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.01003361035533597664845960146529179372714717379932e-139), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.91691742930921170868726692339448146221842496280605e-145), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 200)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.82811491900368853443838779773185869428484436302762e-151), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 208)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74342624569290975040282039426027173450931965163004e-157), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66266083306590056457788505006816075755054440653805e-163), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 224)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.58563693338956886728085045821014476542524758008771e-169), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 232)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51218121851879965522847219296469189207577474602480e-175), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 240)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44212838985328641436431140228718938071801638224106e-181), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 248)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.37532080636337891994887485722273767539788854812723e-187), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31160812984788791651618467066072242297924856960987e-193), tolerance);
 }
 
 template<class RealType, int N>
@@ -451,60 +468,77 @@ void do_test_mapairy_ccdf() {
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.73979922776430555363554632966080889507162029820752e-5), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44353982639936003430898773389958569528340214901924e-5), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21747521599099094720054911524728128905331418743558e-5), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2048))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.30442492111514986227593224497576120783344940470632e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4096))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184402609265962838062304205455964936542503385355e-6), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.38053115409151479601077504716814204054241984396579e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16384))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230503273504174320645323659877052404533613091567e-7), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32768))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.72566394266708055503723315148592640827491725732841e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(65536))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788129092113064009710124961268854372530077851514e-8), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(131072))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40707992833487973793766069223107728401530584918012e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(262144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235161365145877787702193738699569533619914113956e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(524288))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05088499104186197709404571098840228587836479911802e-9), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1048576))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951706432436058369237052221627684485231071286e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2097152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31360623880232751062247585210413319083311528997997e-10), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4194304))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64429939633040546807800247387131067206560952703714e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8388608))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64200779850290938904479244625064763530742033320990e-11), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16777216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424541300683543633877614223483555123688801843e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(33554432))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05250974812863673632096512092113144155816177586613e-12), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(67108864))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.25671780676625854430204135462707277286762193086669e-13), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.34217728e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56563718516079592040149887308711394838177046916383e-13), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.68435456e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845782318037768094883949095101477347530653e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.36870912e8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.20704648145099490050187930370138656919662848438144e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.073741824e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.13386215730722789754721037105719349775366357126605e-14), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.147483648e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00880810181374362562734924119592255004499293746830e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.294967296e9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403487193401296875220001924045479390391e-15), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7179869184e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77165962079254358991751621103655291754760707304047e-16), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.8719476736e10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067948739689526379757206282312287607911e-17), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.74877906944e11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76821815748834935924611907974700181516735308796565e-18), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.099511627776e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669905764884968375298647166107661462e-19), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.398046511104e12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.32534087107554587382206106210469124710349176992174e-20), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.7592186044416e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.40667608884443234227757632763086405915307399803018e-21), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.0368744177664e13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.75834511105554042784697040953858007394668838202264e-22), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.81474976710656e14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44793138881942553480871301192322509243346488933465e-23), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125899906842624e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05599142360242819185108912649040313655418331509614e-23), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.503599627370496e15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31998927950303523981386140811300392069272914785317e-24), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8014398509481984e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64998659937879404976732676014125490086591143489426e-25), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.2057594037927936e16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06248324922349256220915845017656862608238929361934e-26), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.88230376151711744e17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.57810406152936570276144806272071078260298661702420e-27), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.152921504606846976e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22263007691170712845181007840088847825373327128025e-28), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.611686018427387904e18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.02828759613963391056476259800111059781716658910032e-29), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.8446744073709551616e19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.03535949517454238820595324750138824727145823637540e-30), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.95147905179352825856e20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86774921121022248157180194922091913636165349433656e-32), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.722366482869645213696e21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22933581425159726274559405456576861505650835849009e-33), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5557863725914323419136e22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92083720976812072303999071025901346102579431014076e-35), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.208925819614629174706176e24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00130814026268862974998548477970853285280360959494e-37), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.9342813113834066795298816e25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.68954396916045098398435231996829458258250563999209e-39), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.09485009821345068724781056e26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.32741245181320466247555049995046028528516506248764e-41), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.951760157141521099596496896e27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.14490819559581322851180476561725941957580704101369e-42), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.9228162514264337593543950336e28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78891905561845816954969494627696784308719850158390e-44), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.267650600228229401496703205376e30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79518602440384088992139835355776225482374765872484e-46), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.0282409603651670423947251286016e31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.36747816313100139050218492743400352316210571675756e-48), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.24518553658426726783156020576256e32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.82418462989218967265966394911563050494079018243369e-50), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.192296858534827628530496329220096e33))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06627884842065463635307249204931726639699846600526e-51), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8.3076749736557242056487941267521536e34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66606070065727286930167576882705822874531010313323e-53), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.329227995784915872903807060280344576e36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.60321984477698885828386838879227848241454703614566e-55), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.1267647932558653966460912964485513216e37))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.06753100746404509106854435748793512877272974397760e-57), tolerance);
-    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.40282366920938463463374607431768211456e38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.35551719916257045479460055857489863870739022496500e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.30442492111514986227593224497576120783344940470632e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52184402609265962838062304205455964936542503385355e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.38053115409151479601077504716814204054241984396579e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90230503273504174320645323659877052404533613091567e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.72566394266708055503723315148592640827491725732841e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37788129092113064009710124961268854372530077851514e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40707992833487973793766069223107728401530584918012e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97235161365145877787702193738699569533619914113956e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05088499104186197709404571098840228587836479911802e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.71543951706432436058369237052221627684485231071286e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31360623880232751062247585210413319083311528997997e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.64429939633040546807800247387131067206560952703714e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 23))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64200779850290938904479244625064763530742033320990e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.80537424541300683543633877614223483555123688801843e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05250974812863673632096512092113144155816177586613e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.25671780676625854430204135462707277286762193086669e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56563718516079592040149887308711394838177046916383e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.07089725845782318037768094883949095101477347530653e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 29))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.20704648145099490050187930370138656919662848438144e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.13386215730722789754721037105719349775366357126605e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.00880810181374362562734924119592255004499293746830e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41732769663403487193401296875220001924045479390391e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.77165962079254358991751621103655291754760707304047e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21457452599067948739689526379757206282312287607911e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76821815748834935924611907974700181516735308796565e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.46027269686043669905764884968375298647166107661462e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 42))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.32534087107554587382206106210469124710349176992174e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.40667608884443234227757632763086405915307399803018e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 46))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.75834511105554042784697040953858007394668838202264e-22), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44793138881942553480871301192322509243346488933465e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 50))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05599142360242819185108912649040313655418331509614e-23), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31998927950303523981386140811300392069272914785317e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 54))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.64998659937879404976732676014125490086591143489426e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06248324922349256220915845017656862608238929361934e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 58))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.57810406152936570276144806272071078260298661702420e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.22263007691170712845181007840088847825373327128025e-28), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 62))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.02828759613963391056476259800111059781716658910032e-29), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.03535949517454238820595324750138824727145823637540e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 68))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.86774921121022248157180194922091913636165349433656e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22933581425159726274559405456576861505650835849009e-33), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 76))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92083720976812072303999071025901346102579431014076e-35), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.00130814026268862974998548477970853285280360959494e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 84))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.68954396916045098398435231996829458258250563999209e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.32741245181320466247555049995046028528516506248764e-41), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 92))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.14490819559581322851180476561725941957580704101369e-42), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.78891905561845816954969494627696784308719850158390e-44), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 100))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79518602440384088992139835355776225482374765872484e-46), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.36747816313100139050218492743400352316210571675756e-48), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 108))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.82418462989218967265966394911563050494079018243369e-50), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06627884842065463635307249204931726639699846600526e-51), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 116))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66606070065727286930167576882705822874531010313323e-53), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.60321984477698885828386838879227848241454703614566e-55), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 124))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.06753100746404509106854435748793512877272974397760e-57), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.35551719916257045479460055857489863870739022496500e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.35551719916257045479460055857489863870739022496500e-59), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 136))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55163994120179942744008802699582486296567144164185e-62), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.78818345019970563339865240965777554434978379307091e-66), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.24849475146412508153967873451605357507271433855203e-70), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25793328893167116248527312854395839235173689906056e-73), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 168))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.51253244368083779903631134898427341882748266372206e-77), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 176))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34583311613301704078034945043561362764342838469777e-80), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 184))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.28572538118412363471765002547757233311383882982854e-84), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.02179048140655184257238775751360432889120808063607e-88), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 200))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95844494174964644594052435486171980685820509781154e-91), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 208))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.78135972106847276840948328823662062221241478957896e-95), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16732415065148260947497150591714370659482782948705e-98), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.84991247717647121453850465311802662742877888058362e-102), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 232))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.95779413373161917611939612577643219587104218892485e-106), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 240))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69868020843057108791977444476963676657007865940548e-109), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 248))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.14716847761369894511663682805087101213398110206416e-113), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01249230410490696902261641309835718069677272999613e-116), tolerance);
 
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 600))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.71969536983273370677446521953393512020163902133418e-272), tolerance);
 

From edfa58f0c38e80bffc57e8b079f764131b27c759 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Thu, 18 Jul 2024 22:28:30 +0900
Subject: [PATCH 007/399] Add mapairy document

---
 doc/distributions/mapairy.qbk | 106 ++++++++++++++++++++++++++++++++++
 1 file changed, 106 insertions(+)
 create mode 100644 doc/distributions/mapairy.qbk

diff --git a/doc/distributions/mapairy.qbk b/doc/distributions/mapairy.qbk
new file mode 100644
index 0000000000..41e50be0cd
--- /dev/null
+++ b/doc/distributions/mapairy.qbk
@@ -0,0 +1,106 @@
+[section:mapairy_dist Map-Airy Distribution]
+
+``#include <boost/math/distributions/mapairy.hpp>``
+
+   template <class RealType = double,
+             class ``__Policy``   = ``__policy_class`` >
+   class mapairy_distribution;
+
+   typedef mapairy_distribution<> mapairy;
+
+   template <class RealType, class ``__Policy``>
+   class mapairy_distribution
+   {
+   public:
+      typedef RealType  value_type;
+      typedef Policy    policy_type;
+
+      mapairy_distribution(RealType location = 0, RealType scale = 1);
+
+      RealType location()const;
+      RealType scale()const;
+   };
+
+It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
+with shape parameter [alpha]=3/2, [beta]=1.
+
+This distribution is also defined as [beta] = −1, which is inverted about the x-axis.
+
+[@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
+given by:
+
+[equation mapairy_ref1]
+
+The location parameter [mu] is the location of the distribution,
+while the scale parameter [c] determines the width of the distribution.  If the location is
+zero, and the scale 1, then the result is a standard mapairy
+distribution.
+
+The distribution describes the probability distribution of the area under a Brownian excursion over a unit interval.
+
+The following graph shows how the distributions moves as the
+location parameter changes:
+
+[graph mapairy_pdf1]
+
+While the following graph shows how the shape (scale) parameter alters
+the distribution:
+
+[graph mapairy_pdf2]
+
+[h4 Member Functions]
+
+   mapairy_distribution(RealType location = 0, RealType scale = 1);
+
+Constructs a mapairy distribution, with location parameter /location/
+and scale parameter /scale/.  When these parameters take their default
+values (location = 0, scale = 1)
+then the result is a Standard mapairy Distribution.
+
+Requires scale > 0, otherwise calls __domain_error.
+
+   RealType location()const;
+
+Returns the location parameter of the distribution.
+
+   RealType scale()const;
+
+Returns the scale parameter of the distribution.
+
+[h4 Non-member Accessors]
+
+All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
+that are generic to all distributions are supported: __usual_accessors.
+
+Note however that the mapairy distribution does not have a mean,
+standard deviation, etc. See __math_undefined
+[/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
+to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
+which is the default.
+
+Alternately, the functions __skewness, __kurtosis and __kurtosis_excess will all
+return a __domain_error if called.
+
+The domain of the random variable is \[-[max_value], +[min_value]\].
+
+[h4 Accuracy]
+
+The error is within 4 epsilon except for the rapidly decaying left tail.
+
+[h4 Implementation]
+
+See references.
+
+[h4 References]
+
+* [@https://mathworld.wolfram.com/Map-AiryDistribution.html Wolfram MathWorld: Map-Airy Distribution]
+* T. Yoshimura, Numerical Evaluation and High Precision Approximation Formula for Map-Airy Distribution,
+DOI: 10.36227/techrxiv.172053942.27675733/v1, 2024.
+
+[endsect][/section:mapairy_dist mapairy]
+
+[/ mapairy.qbk
+  Distributed under the Boost Software License, Version 1.0.
+  (See accompanying file LICENSE_1_0.txt or copy at
+  http://www.boost.org/LICENSE_1_0.txt).
+]

From 765e0c1e88c0f2600d912119cded9c537b059d71 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Thu, 18 Jul 2024 22:40:22 +0900
Subject: [PATCH 008/399] Add holtsmark document

---
 doc/distributions/holtsmark.qbk | 107 ++++++++++++++++++++++++++++++++
 1 file changed, 107 insertions(+)
 create mode 100644 doc/distributions/holtsmark.qbk

diff --git a/doc/distributions/holtsmark.qbk b/doc/distributions/holtsmark.qbk
new file mode 100644
index 0000000000..5a0d41fb2b
--- /dev/null
+++ b/doc/distributions/holtsmark.qbk
@@ -0,0 +1,107 @@
+[section:holtsmark_dist Holtsmark Distribution]
+
+``#include <boost/math/distributions/holtsmark.hpp>``
+
+   template <class RealType = double,
+             class ``__Policy``   = ``__policy_class`` >
+   class holtsmark_distribution;
+
+   typedef holtsmark_distribution<> holtsmark;
+
+   template <class RealType, class ``__Policy``>
+   class holtsmark_distribution
+   {
+   public:
+      typedef RealType  value_type;
+      typedef Policy    policy_type;
+
+      holtsmark_distribution(RealType location = 0, RealType scale = 1);
+
+      RealType location()const;
+      RealType scale()const;
+   };
+
+The [@http://en.wikipedia.org/wiki/holtsmark_distribution Holtsmark distribution]
+is named after Johan Peter Holtsmark.
+It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
+with shape parameter [alpha]=3/2, [beta]=0.
+
+[@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
+given by:
+
+[equation holtsmark_ref1]
+
+The location parameter [mu] is the location of the distribution,
+while the scale parameter [c] determines the width of the distribution.
+If the location is
+zero, and the scale 1, then the result is a standard holtsmark
+distribution.
+
+The distribution especially used in astrophysics for modeling gravitational bodies.
+
+The following graph shows how the distributions moves as the
+location parameter changes:
+
+[graph holtsmark_pdf1]
+
+While the following graph shows how the shape (scale) parameter alters
+the distribution:
+
+[graph holtsmark_pdf2]
+
+[h4 Member Functions]
+
+   holtsmark_distribution(RealType location = 0, RealType scale = 1);
+
+Constructs a holtsmark distribution, with location parameter /location/
+and scale parameter /scale/.  When these parameters take their default
+values (location = 0, scale = 1)
+then the result is a Standard holtsmark Distribution.
+
+Requires scale > 0, otherwise calls __domain_error.
+
+   RealType location()const;
+
+Returns the location parameter of the distribution.
+
+   RealType scale()const;
+
+Returns the scale parameter of the distribution.
+
+[h4 Non-member Accessors]
+
+All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
+that are generic to all distributions are supported: __usual_accessors.
+
+Note however that the holtsmark distribution does not have a skewness,
+kurtosis, etc. See __math_undefined
+[/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
+to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
+which is the default.
+
+Alternately, the functions __skewness, __kurtosis and __kurtosis_excess will all
+return a __domain_error if called.
+
+The domain of the random variable is \[-[max_value], +[min_value]\].
+
+[h4 Accuracy]
+
+The error is within 4 epsilon.
+
+[h4 Implementation]
+
+See references.
+
+[h4 References]
+
+* [@http://en.wikipedia.org/wiki/holtsmark_distribution Holtsmark Distribution]
+* T. Yoshimura, Numerical Evaluation and High Precision Approximation Formula for Holtsmark Distribution,
+DOI: 10.36227/techrxiv.172054657.73020014/v1, 2024.
+
+[endsect][/section:holtsmark_dist holtsmark]
+
+[/ holtsmark.qbk
+  Distributed under the Boost Software License, Version 1.0.
+  (See accompanying file LICENSE_1_0.txt or copy at
+  http://www.boost.org/LICENSE_1_0.txt).
+]

From 18e035a34e6c23729e43dbb841785388250bc689 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Thu, 18 Jul 2024 22:41:30 +0900
Subject: [PATCH 009/399] Fix mapairy document

---
 doc/distributions/mapairy.qbk | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/distributions/mapairy.qbk b/doc/distributions/mapairy.qbk
index 41e50be0cd..e10f598cec 100644
--- a/doc/distributions/mapairy.qbk
+++ b/doc/distributions/mapairy.qbk
@@ -72,8 +72,8 @@ Returns the scale parameter of the distribution.
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
 
-Note however that the mapairy distribution does not have a mean,
-standard deviation, etc. See __math_undefined
+Note however that the mapairy distribution does not have a skewness,
+kurtosis, etc. See __math_undefined
 [/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
 to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
 which is the default.

From d378f70bdb334fbdb4d5268bde70a3ea53bfdba1 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Thu, 18 Jul 2024 22:48:15 +0900
Subject: [PATCH 010/399] Add saspoint5 document

---
 doc/distributions/saspoint5.qbk | 105 ++++++++++++++++++++++++++++++++
 1 file changed, 105 insertions(+)
 create mode 100644 doc/distributions/saspoint5.qbk

diff --git a/doc/distributions/saspoint5.qbk b/doc/distributions/saspoint5.qbk
new file mode 100644
index 0000000000..ff977b378d
--- /dev/null
+++ b/doc/distributions/saspoint5.qbk
@@ -0,0 +1,105 @@
+[section:saspoint5_dist S[alpha]S Point5 Distribution]
+
+``#include <boost/math/distributions/saspoint5.hpp>``
+
+   template <class RealType = double,
+             class ``__Policy``   = ``__policy_class`` >
+   class saspoint5_distribution;
+
+   typedef saspoint5_distribution<> saspoint5;
+
+   template <class RealType, class ``__Policy``>
+   class saspoint5_distribution
+   {
+   public:
+      typedef RealType  value_type;
+      typedef Policy    policy_type;
+
+      saspoint5_distribution(RealType location = 0, RealType scale = 1);
+
+      RealType location()const;
+      RealType scale()const;
+   };
+
+It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
+with shape parameter [alpha]=1/2, [beta]=0.
+
+[@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
+given by:
+
+[equation saspoint5_ref1]
+
+The location parameter [mu] is the location of the distribution,
+while the scale parameter [c] determines the width of the distribution.
+If the location is
+zero, and the scale 1, then the result is a standard S[alpha]S Point5
+distribution.
+
+This distribution has heavier tails than the Cauchy distribution.
+
+The following graph shows how the distributions moves as the
+location parameter changes:
+
+[graph saspoint5_pdf1]
+
+While the following graph shows how the shape (scale) parameter alters
+the distribution:
+
+[graph saspoint5_pdf2]
+
+[h4 Member Functions]
+
+   saspoint5_distribution(RealType location = 0, RealType scale = 1);
+
+Constructs a S[alpha]S Point5 distribution, with location parameter /location/
+and scale parameter /scale/.  When these parameters take their default
+values (location = 0, scale = 1)
+then the result is a Standard S[alpha]S Point5 Distribution.
+
+Requires scale > 0, otherwise calls __domain_error.
+
+   RealType location()const;
+
+Returns the location parameter of the distribution.
+
+   RealType scale()const;
+
+Returns the scale parameter of the distribution.
+
+[h4 Non-member Accessors]
+
+All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
+that are generic to all distributions are supported: __usual_accessors.
+
+Note however that the S[alpha]S Point5 distribution does not have a mean,
+standard deviation, etc. See __math_undefined
+[/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
+to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
+which is the default.
+
+Alternately, the functions __mean, __sd,
+__variance, __skewness, __kurtosis and __kurtosis_excess will all
+return a __domain_error if called.
+
+The domain of the random variable is \[-[max_value], +[min_value]\].
+
+[h4 Accuracy]
+
+The error is within 4 epsilon.
+
+[h4 Implementation]
+
+See references.
+
+[h4 References]
+
+* T. Yoshimura, Numerical Evaluation and High Precision Approximation Formula for S[alpha]S Point5 Distribution,
+DOI: 10.36227/techrxiv.172055253.37208198/v1, 2024.
+
+[endsect][/section:saspoint5_dist saspoint5]
+
+[/ saspoint5.qbk
+  Distributed under the Boost Software License, Version 1.0.
+  (See accompanying file LICENSE_1_0.txt or copy at
+  http://www.boost.org/LICENSE_1_0.txt).
+]

From 5e58843aece2a5af528923d4cf167aa5c8291e12 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Sun, 21 Jul 2024 02:03:34 +0900
Subject: [PATCH 011/399] Fix saspoint5 minor corrections

---
 .../boost/math/distributions/saspoint5.hpp    | 201 +++++++++---------
 test/test_saspoint5.cpp                       |  56 +++++
 2 files changed, 162 insertions(+), 95 deletions(-)

diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
index 231b8f4939..597421af83 100644
--- a/include/boost/math/distributions/saspoint5.hpp
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -13,8 +13,11 @@
 
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
+#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/distributions/detail/derived_accessors.hpp>
+#include <boost/math/tools/rational.hpp>
 #include <utility>
 #include <cmath>
 
@@ -49,7 +52,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(4.19828222275972713819e14),
         };
         static const RealType Q[15] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.41295871011779138155e2),
             static_cast<RealType>(5.48907134827349102297e4),
             static_cast<RealType>(5.36641455324410261980e6),
@@ -69,7 +72,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 0.25) {
-        RealType t = x - 0.125;
+        RealType t = x - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Relative Error: 2.1471e-17
@@ -83,7 +86,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-6.59304802132933325219e-1),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.98623818041545101115e1),
             static_cast<RealType>(1.52856383017632616759e2),
             static_cast<RealType>(5.70706902111659740041e2),
@@ -95,7 +98,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.5) {
-        RealType t = x - 0.25;
+        RealType t = x - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Relative Error: 5.3265e-17
@@ -110,7 +113,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.37294648777729527395e-3),
         };
         static const RealType Q[6] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.02879626214781666701e1),
             static_cast<RealType>(3.85125274509784615691e1),
             static_cast<RealType>(6.18474367367800231625e1),
@@ -121,7 +124,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 1) {
-        RealType t = x - 0.5;
+        RealType t = x - static_cast <RealType>(0.5);
 
         // Rational Approximation
         // Maximum Relative Error: 2.7947e-17
@@ -135,7 +138,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.03693607694266081126e-4),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.73363440952557318819e0),
             static_cast<RealType>(1.74288966619209299976e1),
             static_cast<RealType>(2.15943268035083671893e1),
@@ -161,7 +164,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-2.63561415158954865283e-7),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.04082856018856244947e0),
             static_cast<RealType>(3.52558663323956252986e0),
             static_cast<RealType>(1.94795523079701426332e0),
@@ -187,7 +190,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-3.56598940936439037087e-9),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.63904431617187026619e0),
             static_cast<RealType>(1.03812003196677309121e0),
             static_cast<RealType>(3.18144310790210668797e-1),
@@ -213,7 +216,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.94913182592441292094e-11),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.10113554189626079232e-1),
             static_cast<RealType>(2.54175325409968367580e-1),
             static_cast<RealType>(3.87119072807894983910e-2),
@@ -239,7 +242,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.16300443044165216564e-13),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.10446485803039594111e-1),
             static_cast<RealType>(6.51887342399859289520e-2),
             static_cast<RealType>(5.02151225308643905366e-3),
@@ -265,7 +268,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-7.42649416356965421308e-16),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.09203384450859785642e-1),
             static_cast<RealType>(1.69422626897631306130e-2),
             static_cast<RealType>(6.65649059670689720386e-4),
@@ -291,7 +294,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.53975807317403152058e-18),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.05980850386474826374e-1),
             static_cast<RealType>(4.34966042652000070674e-3),
             static_cast<RealType>(8.66341538387446465700e-5),
@@ -315,7 +318,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.05398011689821941383e-4),
         };
         static const RealType Q[5] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.00973251258577238892e-1),
             static_cast<RealType>(2.66969681258835723157e-1),
             static_cast<RealType>(5.51785147503612200456e-2),
@@ -368,7 +371,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64877082086372991309408001661535573441e35),
         };
         static const RealType Q[28] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18981461118065892086304195732751798634e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01761929839041982958990681130944341399e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69465252239913021973760046507387620537e8),
@@ -401,7 +404,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 0.125) {
-        RealType t = x - 0.0625;
+        RealType t = x - static_cast <RealType>(0.0625);
 
         // Rational Approximation
         // Maximum Relative Error: 3.4585e-35
@@ -422,7 +425,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05543800791717482823610940401201712196e4),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.44407579416524903840331499438398472639e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15911780811299460009161345260146251462e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88457596285725454686358792906273558406e4),
@@ -440,7 +443,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.25) {
-        RealType t = x - 0.125;
+        RealType t = x - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Relative Error: 6.9278e-35
@@ -461,7 +464,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96874547436310030183519174847668703774e0),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.63164311578114868477819520857286165076e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34964379844144961683927306966955217328e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82966031793809959278519002412667883288e4),
@@ -479,7 +482,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.5) {
-        RealType t = x - 0.25;
+        RealType t = x - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Relative Error: 6.9378e-36
@@ -500,7 +503,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72254289950537680833853394958874977464e-3),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58291085070053442257438623486099473087e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95618461039379226195473938654286975682e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97427161745150579714266897556974326502e3),
@@ -519,7 +522,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 1) {
-        RealType t = x - 0.5;
+        RealType t = x - static_cast <RealType>(0.5);
 
         // Rational Approximation
         // Maximum Relative Error: 6.4363e-35
@@ -540,7 +543,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.02669738424010290973023004028523684766e-7),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46404480283267324138113869370306506431e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.54550184643308468933661600211579108422e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63602410602063476726031476852965502123e2),
@@ -579,7 +582,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21403900721572475664926557233205232491e-10),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13172035933794917563324458011617112124e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65687100738157412154132860910003018338e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59672433683883998168388916533196510994e1),
@@ -618,7 +621,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08663671047376684678494625068451888284e-14),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07443397096591141329212291707948432414e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16665031056584124503224711639009530348e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27666060511630720485121299731204403783e0),
@@ -658,7 +661,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37760675743046300528308203869876086823e-22),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49023284463742780238035958819642738891e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76284367953836866133894756472541395734e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69932155343422362573146811195224195135e-1),
@@ -697,7 +700,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.46784746963816915795587433372284530785e-25),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.16012189991825507132967712656930682478e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95202772611563835130347051925062280272e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23801477561401113332870463345197159418e-2),
@@ -737,7 +740,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.03558202009465610972808653993060437679e-29),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08809672969012756295937194823378109391e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.41148083436617376855422685448827300528e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.85101541143091590863368934606849033688e-3),
@@ -777,7 +780,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.93970406521541790658675747195982964585e-34),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04722757068068234153968603374387493579e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85854131835804458353300285777969427206e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.85809281481040288085436275150792074968e-4),
@@ -811,7 +814,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53567129749337040254350979652515879881e-7),
         };
         static const RealType Q[9] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.89815449697874475254942178935516387239e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.21223228867921988134838870379132038419e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79514417558927397512722128659468888701e-1),
@@ -876,6 +879,8 @@ inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The SaS point5 distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = saspoint5_pdf_imp_prec(u, tag_type()) / scale;
@@ -884,7 +889,7 @@ inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -911,7 +916,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.70766655065405022702e9),
         };
         static const RealType Q[16] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.24333404643898143947e2),
             static_cast<RealType>(2.39984636687021023600e4),
             static_cast<RealType>(1.53353791432086858132e6),
@@ -932,7 +937,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 1) {
-        RealType t = x - 0.5;
+        RealType t = x - static_cast <RealType>(0.5);
 
         // Rational Approximation
         // Maximum Relative Error: 9.2135e-19
@@ -947,7 +952,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.82051978765960490940e-5),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.43565383128046471592e0),
             static_cast<RealType>(1.13265160672130133152e1),
             static_cast<RealType>(1.13352316246726435292e1),
@@ -973,7 +978,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.60407071021044908690e-5),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.06221257507188300824e0),
             static_cast<RealType>(3.44827372231472308047e0),
             static_cast<RealType>(1.78166113338930668519e0),
@@ -999,7 +1004,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.17021346758965979212e-7),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.28212183177829510267e0),
             static_cast<RealType>(6.17321009406850420793e-1),
             static_cast<RealType>(1.38400318019319970893e-1),
@@ -1025,7 +1030,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.25932082770588727842e-9),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.92463563872865541733e-1),
             static_cast<RealType>(1.80720987166755982366e-1),
             static_cast<RealType>(2.20416647324531054557e-2),
@@ -1051,7 +1056,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.96850126180387702894e-11),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.55825191301363023576e-1),
             static_cast<RealType>(4.77251766176046719729e-2),
             static_cast<RealType>(2.99136605131226103925e-3),
@@ -1077,7 +1082,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(3.58808434477817122371e-13),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.80501347735272292079e-1),
             static_cast<RealType>(1.22807958286146936376e-2),
             static_cast<RealType>(3.90421541115275676253e-4),
@@ -1103,7 +1108,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(4.17711709622960498456e-15),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.10198637347368265508e-2),
             static_cast<RealType>(3.12263472357578263712e-3),
             static_cast<RealType>(5.00524795130325614005e-5),
@@ -1127,7 +1132,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-5.63321705854968264807e-5),
         };
         static const RealType Q[5] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.02536240902768558315e-1),
             static_cast<RealType>(1.99284471400121092380e-1),
             static_cast<RealType>(3.48012577961755452113e-2),
@@ -1142,7 +1147,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1183,7 +1188,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54662474187354179772157464533408058525e33),
         };
         static const RealType Q[31] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05231337496532137901354609636674085703e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43071888317491317900094470796567113997e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80864482202910830302921131771345102044e8),
@@ -1219,7 +1224,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 0.25) {
-        RealType t = x - 0.125;
+        RealType t = x - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Relative Error: 9.6106e-35
@@ -1240,7 +1245,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.73617450590346508706222885401965820190e1),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18558935411552146390814444666395959919e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49210559503096368944407109881023223654e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93959323596111340518285858313038058302e4),
@@ -1258,7 +1263,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.5) {
-        RealType t = x - 0.25;
+        RealType t = x - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Relative Error: 3.1519e-35
@@ -1279,7 +1284,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.73529976407853894192156335785920329181e-4),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04157569499592889296640733909653747983e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82248883130787159161541119440215325308e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.35191216924911901198168794737654512677e2),
@@ -1297,7 +1302,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 1) {
-        RealType t = x - 0.5;
+        RealType t = x - static_cast <RealType>(0.5);
 
         // Rational Approximation
         // Maximum Relative Error: 7.1196e-37
@@ -1319,7 +1324,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.76395009419307902351328300308365369814e-8),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28073115520716780203055949058270715651e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.20245752585870752942356137496087189194e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34548337034735803039553186623067144497e2),
@@ -1359,7 +1364,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22093548539863254922531707899658394458e-10),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.83305694892673455436552817409325835774e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49922543669955056754932640312490112609e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23488972536322019584648241457582608908e1),
@@ -1399,7 +1404,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21044098237798939057079316997065892072e-14),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94437702178976797218081686254875998984e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82068837586514484653828718675654460991e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87606058269189306593797764456467061128e0),
@@ -1439,7 +1444,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72380245500539326441037770757072641975e-18),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51702400281458104713682413542736419584e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01375164846907815766683647295932603968e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92796007869834847612192314006582598557e-1),
@@ -1479,7 +1484,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41010917905686427164414364663355769988e-22),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31062773739451672808456319166347015167e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35386721434011881226168110614121649232e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.39357338312443465616015226804775178232e-2),
@@ -1519,7 +1524,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96483118060215455299182487430511998831e-26),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77347004038951368607085827825968614455e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27559305780716801070924630708599448466e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.05452382624230160738008550961679711827e-3),
@@ -1559,7 +1564,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86984591055448991335081550609451649866e-30),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90112824856612652807095815199496602262e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59291524937386142936420775839969648652e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.74245361925275011235694006013677228467e-4),
@@ -1594,7 +1599,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35099582728548602389917143511323566818e-8),
         };
         static const RealType Q[7] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.34601617336219074065534356705298927390e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82954035780824611941899463895040327299e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70929001162671283123255408612494541378e-2),
@@ -1668,6 +1673,8 @@ inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The SaS point5 distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = saspoint5_cdf_imp_prec(u, complement, tag_type());
@@ -1676,7 +1683,7 @@ inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1703,7 +1710,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(-6.17325587219357123900e8),
             };
             static const RealType Q[13] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.63111146753825227716e2),
                 static_cast<RealType>(1.27864461509685444043e4),
                 static_cast<RealType>(6.10371533241799228037e5),
@@ -1721,7 +1728,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * (p * p));
         }
         else if (u < 0.25) {
-            RealType t = u - 0.125;
+            RealType t = u - static_cast <RealType>(0.125);
 
             // Rational Approximation
             // Maximum Relative Error: 2.3770e-19
@@ -1736,7 +1743,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(-7.76665288232972435969e-2),
             };
             static const RealType Q[7] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.72584280323876188464e1),
                 static_cast<RealType>(1.11983518800147654866e2),
                 static_cast<RealType>(3.25969893054048132145e2),
@@ -1748,7 +1755,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else if (u < 0.5) {
-            RealType t = u - 0.25;
+            RealType t = u - static_cast <RealType>(0.25);
 
             // Rational Approximation
             // Maximum Relative Error: 9.2445e-18
@@ -1763,7 +1770,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(3.02683750470398342224e-3),
             };
             static const RealType Q[6] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(8.55049920135376003042e0),
                 static_cast<RealType>(2.48726119139047911316e1),
                 static_cast<RealType>(2.79519589592198994574e1),
@@ -1774,7 +1781,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else {
-            RealType t = u - 0.5;
+            RealType t = u - static_cast <RealType>(0.5);
 
             // Rational Approximation
             // Maximum Relative Error: 2.2918e-20
@@ -1790,7 +1797,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(-3.63491208733876986098e-5),
             };
             static const RealType Q[8] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(6.36954463000253710936e0),
                 static_cast<RealType>(1.40601897306833147611e1),
                 static_cast<RealType>(1.33838075106916667084e1),
@@ -1821,7 +1828,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(6.77986548138011345849e-9),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.39244329037830026691e0),
             static_cast<RealType>(2.12683465416376620896e0),
             static_cast<RealType>(9.02612272334554457823e-1),
@@ -1850,7 +1857,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-6.40223609013005302318e-11),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.11234548272888947555e-1),
             static_cast<RealType>(2.63525516991753831892e-1),
             static_cast<RealType>(4.77118226533147280522e-2),
@@ -1879,7 +1886,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-7.82035413331699873450e-14),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.49007782566002620811e-1),
             static_cast<RealType>(5.65303702876260444572e-2),
             static_cast<RealType>(5.54316442661801299351e-3),
@@ -1909,7 +1916,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(1.48083450629432857655e-18),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.81470315977341203351e-1),
             static_cast<RealType>(6.91330250512167919573e-2),
             static_cast<RealType>(7.84712209182587717077e-3),
@@ -1939,7 +1946,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-1.47102592933729597720e-22),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.34486357752330500669e-1),
             static_cast<RealType>(9.08486933075320995164e-2),
             static_cast<RealType>(1.21024289017243304241e-2),
@@ -1960,7 +1967,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
 
 template <class RealType>
-inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2005,7 +2012,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32129438774563059735783287456769609571e31),
             };
             static const RealType Q[32] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65910866673514847742559406762379054364e2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21954860438789969160116317316418373146e5),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85684385746348850219351196129081986508e7),
@@ -2042,7 +2049,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * (p * p));
         }
         else if (u < 0.25) {
-            RealType t = u - 0.125;
+            RealType t = u - static_cast <RealType>(0.125);
 
             // Rational Approximation
             // Maximum Relative Error: 9.0663e-36
@@ -2062,7 +2069,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35838723365672196069179944509778281549e1),
             };
             static const RealType Q[13] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63888803456697300467924455320638435538e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74785179836182339383932806919167693991e2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.15133301804008879476562749311747788645e3),
@@ -2080,7 +2087,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else if (u < 0.5) {
-            RealType t = u - 0.25;
+            RealType t = u - static_cast <RealType>(0.25);
 
             // Rational Approximation
             // Maximum Relative Error: 7.1265e-35
@@ -2101,7 +2108,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.26783311530618626413866321968979725353e-3),
             };
             static const RealType Q[13] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98941943311823528497840052715295329781e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70142252619301982454969690308614487433e2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17472255695869018956165466705137979540e2),
@@ -2119,7 +2126,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else {
-            RealType t = u - 0.5;
+            RealType t = u - static_cast <RealType>(0.5);
 
             // Rational Approximation
             // Maximum Relative Error: 2.7048e-37
@@ -2141,7 +2148,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.66467016868206844419002547523627548705e-6),
             };
             static const RealType Q[15] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01315080955831561204744043759079263546e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43409077070585581955481063438385546913e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09863540097812452102765922256432103612e2),
@@ -2187,7 +2194,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75224691413667093006312591320754720811e-14),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.59000688626663121310675150262772434285e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37518060227321498297232252379976917550e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96559443266702775026538144474892076437e1),
@@ -2233,7 +2240,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48644117815971872777609922455371868747e-16),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88079839671202113888025645668230104601e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58898753182105924446845274197682915131e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.05418719178760837974322764299800701708e-1),
@@ -2279,7 +2286,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97289727214495789126072009268721022605e-20),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10184661848812835285809771940181522329e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06179300560230499194426573196970342618e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23171547302923911058112454487643162794e-2),
@@ -2325,7 +2332,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58768205048500915346781559321978174829e-24),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27782279546086824129750042200649907991e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86934772625607907724733810228981095894e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18640923531164938140838239032346416143e-2),
@@ -2372,7 +2379,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35526648761411463124801128103381691418e-26),
         };
         static const RealType Q[18] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.99582804063194774835771688139366152937e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.81210581320456331960539046132284190053e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94358920922810097599951120081974275145e-3),
@@ -2420,7 +2427,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.98381676423023212724768510437325359364e-51),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239691423485699928257808e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849140772481980360839559e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29542078693828543560388747333519393752e-2),
@@ -2502,19 +2509,21 @@ inline RealType saspoint5_quantile_imp(const saspoint5_distribution<RealType, Po
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The SaS point5 distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = location + scale * saspoint5_quantile_imp_prec(p, complement, tag_type());
 
     return result;
 }
 
 template <class RealType>
-inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(3.63992444568030649573);
 }
 
 template <class RealType>
-inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.6399244456803064957308496039071853510);
 }
@@ -2543,6 +2552,8 @@ inline RealType saspoint5_entropy_imp(const saspoint5_distribution<RealType, Pol
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The SaS point5 distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = saspoint5_entropy_imp_prec<RealType>(tag_type()) + log(scale);
 
     return result;
@@ -2653,11 +2664,11 @@ inline RealType mean(const saspoint5_distribution<RealType, Policy> &dist)
 {
     // There is no mean:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The SaS point5 Distribution has no mean");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::mean(saspoint5<%1%>&)",
-        "The SaSpoint5 distribution does not have a mean: "
+        "The SaS point5 distribution does not have a mean: "
         "the only possible return value is %1%.",
         std::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
@@ -2667,11 +2678,11 @@ inline RealType variance(const saspoint5_distribution<RealType, Policy>& /*dist*
 {
     // There is no variance:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The SaS point5 Distribution has no variance");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::variance(saspoint5<%1%>&)",
-        "The SaSpoint5 distribution does not have a variance: "
+        "The SaS point5 distribution does not have a variance: "
         "the only possible return value is %1%.",
         std::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
@@ -2693,11 +2704,11 @@ inline RealType skewness(const saspoint5_distribution<RealType, Policy>& /*dist*
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The SaS point5 Distribution has no skewness");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::skewness(saspoint5<%1%>&)",
-        "The SaSpoint5 distribution does not have a skewness: "
+        "The SaS point5 distribution does not have a skewness: "
         "the only possible return value is %1%.",
         std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
@@ -2707,11 +2718,11 @@ inline RealType kurtosis(const saspoint5_distribution<RealType, Policy>& /*dist*
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The SaS point5 Distribution has no kurtosis");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis(saspoint5<%1%>&)",
-        "The SaSpoint5 distribution does not have a kurtosis: "
+        "The SaS point5 distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
         std::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
@@ -2721,11 +2732,11 @@ inline RealType kurtosis_excess(const saspoint5_distribution<RealType, Policy>&
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The SaS point5 Distribution has no kurtosis excess");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis_excess(saspoint5<%1%>&)",
-        "The SaSpoint5 distribution does not have a kurtosis: "
+        "The SaS point5 distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
         std::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
diff --git a/test/test_saspoint5.cpp b/test/test_saspoint5.cpp
index f66fcbfaec..281cad8e25 100644
--- a/test/test_saspoint5.cpp
+++ b/test/test_saspoint5.cpp
@@ -3,11 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsSaSpoint5Test
 #include <boost/test/included/unit_test.hpp>
+#include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/saspoint5.hpp>
+
+#if __has_include(<stdfloat>)
+# include <stdfloat>
+#endif
+
 using boost::math::saspoint5_distribution;
 using boost::multiprecision::cpp_bin_float_quad;
 
@@ -846,6 +853,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp64)
     do_test_saspoint5_pdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp64)
+{
+    do_test_saspoint5_pdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp128)
 {
     do_test_saspoint5_pdf<cpp_bin_float_quad, 113>();
@@ -856,6 +870,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
     do_test_saspoint5_cdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
+{
+    do_test_saspoint5_cdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp128)
 {
     do_test_saspoint5_cdf<cpp_bin_float_quad, 113>();
@@ -866,6 +887,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
     do_test_saspoint5_ccdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
+{
+    do_test_saspoint5_ccdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp128)
 {
     do_test_saspoint5_ccdf<cpp_bin_float_quad, 113>();
@@ -876,6 +904,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
     do_test_saspoint5_quantile_nearzero<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
+{
+    do_test_saspoint5_quantile_nearzero<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp128)
 {
     do_test_saspoint5_quantile_nearzero<cpp_bin_float_quad, 113>();
@@ -886,6 +921,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
     do_test_saspoint5_quantile_lower<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
+{
+    do_test_saspoint5_quantile_lower<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp128)
 {
     do_test_saspoint5_quantile_lower<cpp_bin_float_quad, 113>();
@@ -896,6 +938,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
     do_test_saspoint5_quantile_upper<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
+{
+    do_test_saspoint5_quantile_upper<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp128)
 {
     do_test_saspoint5_quantile_upper<cpp_bin_float_quad, 113>();
@@ -906,6 +955,13 @@ BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
     do_test_saspoint5_locscale_param<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
+{
+    do_test_saspoint5_locscale_param<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp128)
 {
     do_test_saspoint5_locscale_param<cpp_bin_float_quad, 113>();

From c64db569a05ad694c84bb608c12b95aee7947c92 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Sun, 21 Jul 2024 02:05:03 +0900
Subject: [PATCH 012/399] Fix mapairy minor corrections

---
 include/boost/math/distributions/mapairy.hpp | 275 ++++++++++---------
 test/test_mapairy.cpp                        |  57 +++-
 2 files changed, 201 insertions(+), 131 deletions(-)

diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index d7d56ed77f..481db570f6 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -13,8 +13,11 @@
 
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
+#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/distributions/detail/derived_accessors.hpp>
+#include <boost/math/tools/rational.hpp>
 #include <utility>
 #include <cmath>
 
@@ -44,7 +47,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-6.58470237954242016920e-7),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.09464351647314165710e-1),
             static_cast<RealType>(3.66413036246461392316e-1),
             static_cast<RealType>(1.10947882302862241488e-1),
@@ -71,7 +74,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(5.24801123304330014713e-8),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.10853683888611687140e-1),
             static_cast<RealType>(3.89361261627717143905e-1),
             static_cast<RealType>(1.15124062681082170577e-1),
@@ -100,7 +103,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-3.14068002815368247985e-10),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.08772985520393226044e-1),
             static_cast<RealType>(4.26418573702560818267e-1),
             static_cast<RealType>(1.22033746594868893316e-1),
@@ -127,7 +130,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(1.30762989300333026019e-11),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.95505437381674174441e-1),
             static_cast<RealType>(4.58882737262511297099e-1),
             static_cast<RealType>(1.25031310192148865496e-1),
@@ -155,7 +158,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(6.41838355699777435924e-15),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.53390465399680164234e-1),
             static_cast<RealType>(1.82759048270449018482e-1),
             static_cast<RealType>(2.80407546367978533849e-2),
@@ -183,7 +186,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(5.32472028720777735712e-19),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.74018883667663396766e-1),
             static_cast<RealType>(2.95901195665990089660e-2),
             static_cast<RealType>(1.57901733512147920251e-3),
@@ -210,7 +213,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-7.38047553655951666420e-22),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.29920843258164337377e-1),
             static_cast<RealType>(6.75018577147646502386e-3),
             static_cast<RealType>(1.77694968039695671819e-4),
@@ -234,7 +237,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.06404478702135751872e2),
         };
         static const RealType Q[3] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.25696892802060720079e-5),
             static_cast<RealType>(4.03600055498020483920e1),
         };
@@ -271,7 +274,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46130347604880355784938321408765318948e-13),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11845869711743584628289654085905424438e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.80391154854347711297249357734993136108e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75628443538173255184583966965162835227e-1),
@@ -308,7 +311,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.65915115243311285178083515017249358853e-12),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33250387018216706082200927591739589024e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.71707718560216685629188467984384070512e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81316277289673837399162302797006618384e-1),
@@ -346,7 +349,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19376016170255697546854583591494809062e-13),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52686177278870816414637961315363468426e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19872083945442288336636376283295310445e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26633866969676511944680471882188527224e-1),
@@ -388,7 +391,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53569375838863862590910010617140120876e-18),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94337325681904859647161946168957959628e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77120402023938328899162557073347121463e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01644685191130734907530007424741314392e0),
@@ -433,7 +436,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42496376687241918803028631991083570963e-26),
         };
         static const RealType Q[16] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19213376162053391168605415200906099633e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65578261958732385181558047087365997878e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30046653564394292929001223763106276016e-1),
@@ -476,7 +479,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52190981930441828041102818178755246228e-31),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.70564782441895707961338319466546005093e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47770566490107388849474183308889339231e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29364672385303439788399215507370006639e-2),
@@ -518,7 +521,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33468198065176301137949068264633336529e-37),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51951069241510130465691156908893803280e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84647597299970149588010858770320631739e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90239396588176334117512714878489376365e-3),
@@ -552,7 +555,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.59558963351172885545760841064831356701e3),
         };
         static const RealType Q[7] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.51965956124978480521462518750569617550e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61700833299761977287211297600922591853e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.94988298508869748383898344668918510537e1),
@@ -589,7 +592,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(2.94270091008508492304e-6),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.98673671503410894284e-1),
             static_cast<RealType>(3.15907666864554716291e-1),
             static_cast<RealType>(8.34463558393629855977e-2),
@@ -616,7 +619,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(-6.13516242712196835055e-5),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.06478618107122200489e0),
             static_cast<RealType>(4.08809060854459518663e-1),
             static_cast<RealType>(2.66617598099501800866e-1),
@@ -647,7 +650,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(6.97462693097107007719e-5),
             };
             static const RealType Q[8] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.81256903248465876424e0),
                 static_cast<RealType>(1.43959302060852067876e0),
                 static_cast<RealType>(6.65882284117861804351e-1),
@@ -675,7 +678,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(-4.92754650783224582641e-13),
             };
             static const RealType Q[7] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.27271216837333318516e0),
                 static_cast<RealType>(6.96551952883867277759e-1),
                 static_cast<RealType>(2.11871363524516350422e-1),
@@ -700,7 +703,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(9.21758454778883157515e-6),
             };
             static const RealType Q[6] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(6.23092941554668369107e-1),
                 static_cast<RealType>(1.57829914506366827914e-1),
                 static_cast<RealType>(2.02787979758160988615e-2),
@@ -723,7 +726,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(5.40508013573989841127e-6),
             };
             static const RealType Q[5] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(2.70578525590448009961e-1),
                 static_cast<RealType>(2.73082032706004833847e-2),
                 static_cast<RealType>(1.21926059813954504560e-3),
@@ -768,7 +771,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00448215148716947837105979735199471601e-11),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.69069814466926608209872727645156315374e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89657828158127300370734997707096744077e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62713433978940724622996782534485162816e-1),
@@ -806,7 +809,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49023728251751416730708805268921994420e-10),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.11919889346080886194925406930280687022e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99082771425048574611745923487528183522e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99525320878512488641033584061027063035e-1),
@@ -851,7 +854,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78908322579081615215057968216358892954e-9),
             };
             static const RealType Q[15] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15777668058369565739250784347385217839e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58275582332060589146223977924181161908e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08890987062755381429904193744273374370e0),
@@ -893,7 +896,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06306499345515479193219487228315566344e-11),
             };
             static const RealType Q[15] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13521398369589479131299586715604029947e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17680254721938920978999949995837883884e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40693619288419980101309080614788657638e0),
@@ -933,7 +936,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36635313919771528255819112450043338510e-12),
             };
             static const RealType Q[13] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32484755553196872705775494679365596205e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17714315014480774542066462899317631393e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10789882607024692577764888497624620277e-1),
@@ -970,7 +973,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.02405342795439598418033139109649640085e-35),
             };
             static const RealType Q[11] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78286317363568496229516074305435186276e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06519013547074134846431611115576250187e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71907733798006110542919988654989891098e-2),
@@ -1003,7 +1006,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.46207029637607033398822620480584537642e-38),
             };
             static const RealType Q[9] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54906717312241693103173902792310528801e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84408124581401290943345932332007045483e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81403744024723164669745491417804917709e-3),
@@ -1083,6 +1086,8 @@ inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& di
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = mapairy_pdf_imp_prec(u, tag_type()) / scale;
@@ -1091,7 +1096,7 @@ inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& di
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1109,7 +1114,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-3.97941251650023182117e-6),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.17408156824742736411e-1),
             static_cast<RealType>(3.57041011418415988268e-1),
             static_cast<RealType>(1.04580353775369716002e-1),
@@ -1135,7 +1140,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(5.35982226125013888796e-7),
         };
         static const RealType Q[6] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.70352826101668448273e-1),
             static_cast<RealType>(1.98852010141232271304e-1),
             static_cast<RealType>(3.64864882318453496161e-2),
@@ -1161,7 +1166,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.06076300080048408251e-9),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.54435380513870673497e-1),
             static_cast<RealType>(3.66021233157880878411e-1),
             static_cast<RealType>(9.42985570806905160687e-2),
@@ -1188,7 +1193,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-5.16172854149066643529e-11),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.05317644829451086870e-1),
             static_cast<RealType>(3.73713496637025562492e-1),
             static_cast<RealType>(8.94434672792094976627e-2),
@@ -1216,7 +1221,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(2.98763969872672156104e-14),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.27732094554221674504e-1),
             static_cast<RealType>(1.14330643482604301178e-1),
             static_cast<RealType>(1.27722341942374066265e-2),
@@ -1243,7 +1248,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(9.11626234402148561268e-17),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.09895694991285975774e-1),
             static_cast<RealType>(3.69874670435930773471e-2),
             static_cast<RealType>(2.15708854325146400153e-3),
@@ -1269,7 +1274,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.48321866072033823195e-17),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.12851983233980279746e-1),
             static_cast<RealType>(4.94650928817638043712e-3),
             static_cast<RealType>(1.05447405092956497114e-4),
@@ -1293,7 +1298,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.26770824563800250704e-1),
         };
         static const RealType Q[3] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.26301023103568827709e-2),
             static_cast<RealType>(1.60899894281099149848e1),
         };
@@ -1306,7 +1311,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
 
 template <class RealType>
-inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1331,7 +1336,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13807083548358335699029971528179486964e-13),
         };
         static const RealType Q[12] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00810772528427939684296334977783425582e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.24383652800043768524894854013745098654e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64696616559657052516796844068580626381e-1),
@@ -1368,7 +1373,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00479393063394570750334218362674723065e-13),
         };
         static const RealType Q[12] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24929390929112144560152115661603117364e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.34853762543033883106055186520573363290e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.73783624941936412984356492130276742707e-1),
@@ -1406,7 +1411,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45008884108655511268690849420714428764e-15),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42652074703683973183213296310906006173e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03479786698331153607905223548719296572e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.95556520914240562719970700900964416000e-1),
@@ -1446,7 +1451,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70140037580287364298206334732060874507e-16),
         };
         static const RealType Q[16] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36848014038411798213992770858203510748e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.15373052017549822413011375404872359177e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92705544967513282963463451395766172671e-1),
@@ -1490,7 +1495,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98451733054622166748935243139556132704e-26),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08148065380582488495702136465010348576e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42385352331252779422725444021027377277e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66510412535270623169792008730183916611e-1),
@@ -1532,7 +1537,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65549196385656698597261688277898043367e-30),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03426141030409708635168766288764563749e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13808987755928828118915442251025992769e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52253239792170999949444502938290297674e-2),
@@ -1571,7 +1576,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31961589164397397724611386366339562789e-28),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26440207646105117747875545474828367516e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27872879091838733280518786463281413334e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34256572873114675776148923422025029494e-3),
@@ -1607,7 +1612,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07224810408790092272497403739984510394e2),
         };
         static const RealType Q[7] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32474438135610721926278423612948794250e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27594461167587027771303292526448542806e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49207539478843628626934249487055017677e1),
@@ -1623,7 +1628,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1644,7 +1649,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(3.09442180091323751049e-6),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.16241922223786900600e-1),
             static_cast<RealType>(2.75690727171711638879e-1),
             static_cast<RealType>(7.18707184893542884080e-2),
@@ -1671,7 +1676,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(1.22071311320012805777e-5),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.63771793313770952352e-2),
             static_cast<RealType>(2.23602260938227310054e-1),
             static_cast<RealType>(9.21944797677283179038e-3),
@@ -1701,7 +1706,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.13854052826846329787e-4),
             };
             static const RealType Q[8] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.29694286517571741097e0),
                 static_cast<RealType>(7.99686735441213882518e-1),
                 static_cast<RealType>(3.08198207583883597188e-1),
@@ -1729,7 +1734,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.42364413902075896503e-5),
             };
             static const RealType Q[8] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(1.09709853682665798542e0),
                 static_cast<RealType>(5.63687797989627787500e-1),
                 static_cast<RealType>(1.73604358560002859604e-1),
@@ -1756,7 +1761,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(4.43354791268634655473e-6),
             };
             static const RealType Q[7] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(7.07103973315808077783e-1),
                 static_cast<RealType>(2.13664682181055450396e-1),
                 static_cast<RealType>(3.52218225168465984709e-2),
@@ -1781,7 +1786,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.48743616420183584738e-6),
             };
             static const RealType Q[6] = {
-                static_cast<RealType>(1),
+                static_cast<RealType>(1.),
                 static_cast<RealType>(3.26493785348088598123e-1),
                 static_cast<RealType>(4.28813205161574223713e-2),
                 static_cast<RealType>(2.82893073845390254969e-3),
@@ -1800,7 +1805,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1827,7 +1832,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.46723648594704078875476888175530463986e-12),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.98700317671474659677458220091101276158e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00405631175818416028878082789095587658e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04189939150805562128632256692765842568e-1),
@@ -1866,7 +1871,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41870129065056783732691371215602982173e-9),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.75919235734607601884356783586727272494e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.57656678936617227532275100649989944452e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72617552401870454676736869003112018648e-1),
@@ -1911,7 +1916,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88472819535099746216179119978362211227e-10),
             };
             static const RealType Q[16] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68923525157720774962908922391133419863e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40714902096062779527207435671907059131e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73120596883364361220343183559076165363e0),
@@ -1955,7 +1960,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36407983918582149239548869529460234702e-12),
             };
             static const RealType Q[16] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99867960957804580209868321228347067213e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94236623527818880544030470097296139679e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21644866845440678050425616384656052588e0),
@@ -1998,7 +2003,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83956842740198388242245209024484381888e-29),
             };
             static const RealType Q[14] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50056124032615852703112365430040751173e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05112559537845833793684655693572118348e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.55609497026127521043140534271852131858e-1),
@@ -2036,7 +2041,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53666531487585211574942518181922132884e-14),
             };
             static const RealType Q[12] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.82230649578130958108098853863277631065e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12412482738973738235656376802445565005e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98320116955422615960870363549721494683e-2),
@@ -2070,7 +2075,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48798342894235412426464893852098239746e-14),
             };
             static const RealType Q[10] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81588658109851219975949691772676519853e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52583331848892383968186924120872369151e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57644670426430994363913234422346706991e-3),
@@ -2151,6 +2156,8 @@ inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& di
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = mapairy_cdf_imp_prec(u, complement, tag_type());
@@ -2159,13 +2166,13 @@ inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& di
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
 
     if (p >= 0.375) {
-        RealType t = p - 0.375;
+        RealType t = p - static_cast <RealType>(0.375);
 
         // Rational Approximation
         // Maximum Relative Error: 1.5488e-18
@@ -2179,7 +2186,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(4.79284243496552841508e0),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.76268072706610602584e0),
             static_cast<RealType>(-4.88492535243404839734e0),
             static_cast<RealType>(-5.67524172432687656881e0),
@@ -2191,7 +2198,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
-        RealType t = p - 0.25;
+        RealType t = p - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Relative Error: 7.5181e-17
@@ -2205,7 +2212,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(1.31575930750093554120e1),
         };
         static const RealType Q[6] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.38761652244702318296e0),
             static_cast<RealType>(2.40932080746189543284e0),
             static_cast<RealType>(-1.69465870062123632126e1),
@@ -2216,7 +2223,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
-        RealType t = p - 0.125;
+        RealType t = p - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Relative Error: 2.3028e-18
@@ -2231,7 +2238,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.33786726970025938837e2),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.91797638291395345792e1),
             static_cast<RealType>(1.24293724082506952768e2),
             static_cast<RealType>(2.82393116012902543276e2),
@@ -2257,7 +2264,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-9.74212491048543799073e-5),
         };
         static const RealType Q[6] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.91919722132624625590e-1),
             static_cast<RealType>(2.17415447268626558639e-1),
             static_cast<RealType>(2.41474762519410575392e-2),
@@ -2283,7 +2290,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-4.19292241201527861927e-9),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.23065798041556418844e-1),
             static_cast<RealType>(1.96731305131315877264e-1),
             static_cast<RealType>(2.49952034298034383781e-2),
@@ -2310,7 +2317,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-3.78061321691170114390e-11),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.57770840766081587688e-1),
             static_cast<RealType>(4.81290550545412209056e-2),
             static_cast<RealType>(3.02079969075162071807e-3),
@@ -2337,7 +2344,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-3.46758191090170732580e-13),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.77270673840643360017e-1),
             static_cast<RealType>(1.18099604045834575786e-2),
             static_cast<RealType>(3.66889581757166584963e-4),
@@ -2364,7 +2371,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-3.23343844538964435927e-15),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.79845511272943785289e-2),
             static_cast<RealType>(2.90839059356197474893e-3),
             static_cast<RealType>(4.48172838083912540123e-5),
@@ -2391,7 +2398,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-3.05720104049292610799e-17),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.37395212065018405474e-2),
             static_cast<RealType>(7.18654254114820140590e-4),
             static_cast<RealType>(5.50371158026951899491e-6),
@@ -2418,7 +2425,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.92218240202835807955e-19),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.17740414929742679904e-2),
             static_cast<RealType>(1.78084231709097280884e-4),
             static_cast<RealType>(6.78870668961146609668e-7),
@@ -2445,7 +2452,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.81661279271583206526e-21),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.08518414679241420227e-2),
             static_cast<RealType>(4.42335224797004486239e-5),
             static_cast<RealType>(8.40387821972524402121e-8),
@@ -2472,7 +2479,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.73260616170245224789e-23),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.41357843707822974161e-3),
             static_cast<RealType>(1.10082540037527566536e-5),
             static_cast<RealType>(1.04338126042963003178e-8),
@@ -2492,13 +2499,13 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
 
 template <class RealType>
-inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
 
     if (p >= 0.4375) {
-        RealType t = p - 0.4375;
+        RealType t = p - static_cast <RealType>(0.4375);
 
         // Rational Approximation
         // Maximum Relative Error: 4.2901e-35
@@ -2515,7 +2522,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.04356966421177683585461937085598186805e1),
         };
         static const RealType Q[11] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75444066345435020043849341970820565274e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.95105673975812427406540024601734210826e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.20381124524894051002242766595737443257e0),
@@ -2531,7 +2538,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.375) {
-        RealType t = p - 0.375;
+        RealType t = p - static_cast <RealType>(0.375);
 
         // Rational Approximation
         // Maximum Relative Error: 2.8433e-36
@@ -2549,7 +2556,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62979741122708118776725634304028246971e0),
         };
         static const RealType Q[10] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10550060286464202595779024353437346419e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.15893254630199957990897452211066782021e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.58964066823516762861256609311733069353e1),
@@ -2564,7 +2571,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
-        RealType t = p - 0.25;
+        RealType t = p - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Relative Error: 5.9072e-35
@@ -2584,7 +2591,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03293129698111279047104766073456412318e1),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29511778027351594854005887702013466376e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66155745848864270109281703659789474448e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25628362783798417463294553777015370203e1),
@@ -2602,7 +2609,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
-        RealType t = p - 0.125;
+        RealType t = p - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Relative Error: 9.9092e-36
@@ -2624,7 +2631,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.96914697182030973966321601422851730384e4),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98063872144867195074924232601423646991e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65911346382127464683324945513128779971e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02451223307009464199634546540152067898e3),
@@ -2662,7 +2669,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.61008160195204632725691076288641221707e-10),
         };
         static const RealType Q[11] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59109221235949005113322202980300291082e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07119192591092503378838510797916225920e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97313678065269932508447079892684333156e-1),
@@ -2700,7 +2707,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51102540845397821195190063256442894688e-18),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51733661576324699382035973518172469602e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01435607980568082538278883569729476204e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93274478117803447229185270863587786287e-1),
@@ -2741,7 +2748,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54464319402577486444841981479085908190e-22),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.56568169258142086426383908572004868200e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52144703581828715720555168887427064424e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87268567039210776554113754014224005739e-2),
@@ -2782,7 +2789,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84098833615882764168840211033822541979e-26),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76933186134913044021577076301874622292e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25794095712489484166470336696962749356e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02367257449622569623375613790000874499e-3),
@@ -2823,7 +2830,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34400562353945663460416286570988365992e-30),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87838171063584994806998206766890809367e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55395225505766120991458653457272783334e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.45282436421694718640472363162421055686e-4),
@@ -2864,7 +2871,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.92396730553947142987611521115040472261e-35),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36599681872296382199486815169747516110e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.86330544720458446620644055149504593514e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.23793435123936109978741252388806998743e-5),
@@ -2905,7 +2912,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.40321396496046206171642334628524367374e-39),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67292043485384876322219919215413286868e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61652550158809553935603664087740554258e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14722810796821047167211543031044501921e-5),
@@ -2946,7 +2953,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56848486878078288956741060120464349537e-43),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33267370502089423930888060969568705647e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39632352029900752622967578086289898150e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42703739831525305516280300008439396218e-6),
@@ -2987,7 +2994,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.21480186561579326423946788448005430367e-47),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16494591376838053609854716130343599036e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.97651667629616309497454026431358820357e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77741398674456235952879526959641925087e-7),
@@ -3028,7 +3035,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20516030880916148179297554212609531432e-51),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81973541224235020744673910266545976833e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49156990107280109344880219729275939242e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21606730563542176411852745162267260946e-8),
@@ -3069,7 +3076,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.44601448994095786447982489957909713982e-55),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90814053669730896497462224007523900520e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72450689508305973756255440356759005330e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76517273086984384225845151573287252506e-9),
@@ -3110,7 +3117,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.87159268409640967747617639113346310759e-59),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45350026842128595165328480395513258721e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.30398532102631290226106936127181928207e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45242264812189519858570105609209495630e-10),
@@ -3151,7 +3158,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.43473066278196981345209422626769148425e-63),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26570199429958856038191879713341034013e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32484776300757286079244074394356908390e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31234182027812869096733088981702059020e-11),
@@ -3177,13 +3184,13 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
 
     if (p >= 0.25) {
-        RealType t = p - 0.25;
+        RealType t = p - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Absolute Error: 1.8559e-18
@@ -3198,7 +3205,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-4.28101952511581488588e1),
         };
         static const RealType Q[10] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.20189490825315245036e0),
             static_cast<RealType>(1.63469912146101848441e1),
             static_cast<RealType>(-1.52740920318273920072e1),
@@ -3213,7 +3220,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
-        RealType t = p - 0.125;
+        RealType t = p - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Absolute Error: 4.6019e-17
@@ -3227,7 +3234,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(1.54245210917147215257e3),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.13092357122115486375e1),
             static_cast<RealType>(1.57318281834689144053e2),
             static_cast<RealType>(4.42261730187813035957e2),
@@ -3255,7 +3262,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(4.74040834029330213692e-6),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.14801234415100707213e-1),
             static_cast<RealType>(1.04693730144480856638e-1),
             static_cast<RealType>(3.81581484862997435076e-2),
@@ -3286,7 +3293,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(2.62304611053075404923e-7),
         };
         static const RealType Q[11] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.28225379952156944029e-1),
             static_cast<RealType>(3.49662079845715371907e-1),
             static_cast<RealType>(1.45408903426879603625e-1),
@@ -3319,7 +3326,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(2.51255632629650930196e-14),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.58341767924960527280e-1),
             static_cast<RealType>(2.73511775500642961539e-1),
             static_cast<RealType>(6.16011987856129890130e-2),
@@ -3349,7 +3356,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(1.87458213915373906356e-6),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.98511036742503939380e-1),
             static_cast<RealType>(3.91130673008184655152e-1),
             static_cast<RealType>(1.09277016228474605069e-1),
@@ -3381,13 +3388,13 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
 
 template <class RealType>
-inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
 
     if (p >= 0.375) {
-        RealType t = p - 0.375;
+        RealType t = p - static_cast <RealType>(0.375);
 
         // Rational Approximation
         // Maximum Absolute Error: 4.0835e-35
@@ -3407,7 +3414,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10895417312529385966062255102265009972e0),
         };
         static const RealType Q[12] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88252553879196710256650370298744093367e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54875259600848880869571364891152935969e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.78589587338618424770295921221996471887e1),
@@ -3424,7 +3431,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
-        RealType t = p - 0.25;
+        RealType t = p - static_cast <RealType>(0.25);
 
         // Rational Approximation
         // Maximum Absolute Error: 5.7633e-36
@@ -3445,7 +3452,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.54255748148299874514839812717054396793e2),
         };
         static const RealType Q[13] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64823387375875361292425741663822893626e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02973633484731117050245517938177308809e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71288209768693917630236009171518272534e2),
@@ -3463,7 +3470,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
-        RealType t = p - 0.125;
+        RealType t = p - static_cast <RealType>(0.125);
 
         // Rational Approximation
         // Maximum Absolute Error: 2.1140e-36
@@ -3485,7 +3492,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95604329277359828898502487252547842378e6),
         };
         static const RealType Q[16] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79208640567193066236912382037923299779e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94775812217734059201656828286490832145e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16467934643564936346029555887148320030e4),
@@ -3527,7 +3534,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10466412567107519640190849286913680449e-10),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31914248618040435028023418981527961171e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.73578090645412656850163531828709850171e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57329813782272411333511950903192234311e-2),
@@ -3576,7 +3583,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05739751797738770096482688062542436470e-15),
         };
         static const RealType Q[23] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43370372582239919321785765900615222895e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52872159582703775260145036441128318159e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28243735290178057451806192890274584778e-1),
@@ -3632,7 +3639,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.82128612844034824876694595066123093042e-27),
         };
         static const RealType Q[20] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65414405277042133067228113526697909557e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32179221250476209346757936207079534440e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.74217392682100275524983756207618144313e-1),
@@ -3683,7 +3690,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73701196181204039400706651811524874455e-34),
         };
         static const RealType Q[18] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77119890916406072259446489508263892540e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95177888809731859578167185583119074026e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.29131027214559081111011582466619105016e-2),
@@ -3731,7 +3738,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96470010392255781222480229189380065951e-18),
         };
         static const RealType Q[18] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.82841492468725267177870050157374330523e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83703946702662950408034486958999188355e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09320896703777230915306208582393356690e-1),
@@ -3824,19 +3831,21 @@ inline RealType mapairy_quantile_imp(const mapairy_distribution<RealType, Policy
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = location + scale * mapairy_quantile_imp_prec(p, complement, tag_type());
 
     return result;
 }
 
 template <class RealType>
-inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-1.16158727113597068525);
 }
 
 template <class RealType>
-inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.1615872711359706852500000803029112987);
 }
@@ -3870,19 +3879,21 @@ inline RealType mapairy_mode_imp(const mapairy_distribution<RealType, Policy>& d
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = location + scale * mapairy_mode_imp_prec<RealType>(tag_type());
 
     return result;
 }
 
 template <class RealType>
-inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-0.71671068545502205332);
 }
 
 template <class RealType>
-inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.71671068545502205331700196278067230944440);
 }
@@ -3916,19 +3927,21 @@ inline RealType mapairy_median_imp(const mapairy_distribution<RealType, Policy>&
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = location + scale * mapairy_median_imp_prec<RealType>(tag_type());
 
     return result;
 }
 
 template <class RealType>
-inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.00727681841065634600);
 }
 
 template <class RealType>
-inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0072768184106563460003025875575283708);
 }
@@ -3957,6 +3970,8 @@ inline RealType mapairy_entropy_imp(const mapairy_distribution<RealType, Policy>
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Map-Airy distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = mapairy_entropy_imp_prec<RealType>(tag_type()) + log(scale);
 
     return result;
@@ -4091,7 +4106,7 @@ inline RealType skewness(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Map-Airy Distribution has no skewness");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::skewness(mapairy<%1%>&)",
@@ -4105,7 +4120,7 @@ inline RealType kurtosis(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Map-Airy Distribution has no kurtosis");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis(mapairy<%1%>&)",
@@ -4119,7 +4134,7 @@ inline RealType kurtosis_excess(const mapairy_distribution<RealType, Policy>& /*
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Map-Airy Distribution has no kurtosis excess");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis_excess(mapairy<%1%>&)",
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index ccae24c30f..cfa3a712de 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -3,11 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsMapAiryTest
 #include <boost/test/included/unit_test.hpp>
+#include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/mapairy.hpp>
+
+#if __has_include(<stdfloat>)
+# include <stdfloat>
+#endif
+
 using boost::math::mapairy_distribution;
 using boost::multiprecision::cpp_bin_float_quad;
 
@@ -539,7 +546,6 @@ void do_test_mapairy_ccdf() {
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 240))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69868020843057108791977444476963676657007865940548e-109), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 248))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.14716847761369894511663682805087101213398110206416e-113), tolerance);
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01249230410490696902261641309835718069677272999613e-116), tolerance);
-
     BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 600))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.71969536983273370677446521953393512020163902133418e-272), tolerance);
 
     // The test is terminated because x is inf after this in fp64.
@@ -790,6 +796,13 @@ BOOST_AUTO_TEST_CASE(mapairy_pdf_fp64)
     do_test_mapairy_pdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_pdf_fp64)
+{
+    do_test_mapairy_pdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_pdf_fp128)
 {
     do_test_mapairy_pdf<cpp_bin_float_quad, 113>();
@@ -800,6 +813,13 @@ BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
     do_test_mapairy_cdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
+{
+    do_test_mapairy_cdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_cdf_fp128)
 {
     do_test_mapairy_cdf<cpp_bin_float_quad, 113>();
@@ -810,6 +830,13 @@ BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
     do_test_mapairy_ccdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
+{
+    do_test_mapairy_ccdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp128)
 {
     do_test_mapairy_ccdf<cpp_bin_float_quad, 113>();
@@ -820,6 +847,13 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
     do_test_mapairy_quantile_nearzero<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
+{
+    do_test_mapairy_quantile_nearzero<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp128)
 {
     do_test_mapairy_quantile_nearzero<cpp_bin_float_quad, 113>();
@@ -830,6 +864,13 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
     do_test_mapairy_quantile_lower<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
+{
+    do_test_mapairy_quantile_lower<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp128)
 {
     do_test_mapairy_quantile_lower<cpp_bin_float_quad, 113>();
@@ -840,6 +881,13 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
     do_test_mapairy_quantile_upper<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
+{
+    do_test_mapairy_quantile_upper<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp128)
 {
     do_test_mapairy_quantile_upper<cpp_bin_float_quad, 113>();
@@ -850,6 +898,13 @@ BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
     do_test_mapairy_locscale_param<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
+{
+    do_test_mapairy_locscale_param<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(mapairy_locscale_fp128)
 {
     do_test_mapairy_locscale_param<cpp_bin_float_quad, 113>();

From 953cc377f1ddb0d9d21c9ab3859b85e545e38af2 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Sun, 21 Jul 2024 02:06:36 +0900
Subject: [PATCH 013/399] Fix holtsmark minor corrections

---
 .../boost/math/distributions/holtsmark.hpp    | 145 ++++++++++--------
 test/test_holtsmark.cpp                       |  56 +++++++
 2 files changed, 134 insertions(+), 67 deletions(-)

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index 5e759cb3e3..d53a2ac701 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -13,8 +13,11 @@
 
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
+#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/distributions/detail/derived_accessors.hpp>
+#include <boost/math/tools/rational.hpp>
 #include <utility>
 #include <cmath>
 
@@ -44,7 +47,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.74679078247026597959e-5),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.12654472808214997252e-3),
             static_cast<RealType>(2.93891863033354755743e-1),
             static_cast<RealType>(8.70867222155141724171e-3),
@@ -72,7 +75,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-8.45210544648986348854e-6),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.11634701234079515138e-1),
             static_cast<RealType>(4.39922162828115412952e-1),
             static_cast<RealType>(1.73609068791154078128e-1),
@@ -102,7 +105,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(7.24351142163396584236e-9),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.88099527896838765666e-1),
             static_cast<RealType>(6.53896948546877341992e-1),
             static_cast<RealType>(2.96296982585381844864e-1),
@@ -134,7 +137,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.12196487201928768038e-13),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.61334003864149486454e0),
             static_cast<RealType>(1.28348868912975898501e0),
             static_cast<RealType>(6.36594545291321210154e-1),
@@ -163,7 +166,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.17784858891714869163e-15),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(7.29383849235788831455e-1),
             static_cast<RealType>(2.16287201867831015266e-1),
             static_cast<RealType>(3.28789040872705709070e-2),
@@ -191,7 +194,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-9.00826023095223871551e-21),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.28966789835486457746e-1),
             static_cast<RealType>(4.46981634258601621625e-2),
             static_cast<RealType>(3.22521297380474263906e-3),
@@ -219,7 +222,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-4.61828164399178360925e-23),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.23544974283127158019e-1),
             static_cast<RealType>(6.01210465184576626802e-3),
             static_cast<RealType>(1.45390926665383063500e-4),
@@ -242,7 +245,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(8.75909164947413479137e-1),
         };
         static const RealType Q[3] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(-6.07405848111002255020e0),
             static_cast<RealType>(1.34068401972703571636e1),
         };
@@ -280,7 +283,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.49208308902369087634036371223527932419e-11),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07053963271862256947338846403373278592e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30146528469038357598785392812229655811e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.22168809220570888957518451361426420755e-2),
@@ -321,7 +324,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77430867682132459087084564268263825239e-11),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30030169049261634787262795838348954434e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45935676273909940847479638179887855033e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14724239378269259016679286177700667008e-1),
@@ -365,7 +368,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05561259222780127064607109581719435800e-15),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08902510590064634965634560548380735284e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.60127698266075086782895988567899172787e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.73299227011247478433171171063045855612e-1),
@@ -414,7 +417,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.22157263424086267338486564980223658130e-22),
         };
         static const RealType Q[19] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24254809760594824834854946949546737102e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66740386908805016172202899592418717176e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17175023341071972435947261868288366592e0),
@@ -462,7 +465,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33878078951302606409419167741041897986e-26),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75629880937514507004822969528240262723e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43883005193126748135739157335919076027e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26826935326347315479579835343751624245e-1),
@@ -506,7 +509,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46357124817620384236108395837490629563e-31),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02259092175256156108200465685980768901e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63438230616954606028022008517920766366e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63880061357592661176130881772975919418e-2),
@@ -548,7 +551,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.72047006026700174884151916064158941262e-38),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50985661940624198574968436548711898948e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81705882167596649186405364717835589894e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86537779048672498307196786015602357729e-3),
@@ -582,7 +585,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.80591252844738626580182351673066365090e1),
         };
         static const RealType Q[7] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.57593243741246726197476469913307836496e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99458751269722094414105565700775283458e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.91043982880665229427553316951582511317e3),
@@ -645,6 +648,8 @@ inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Holtsmark distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = holtsmark_pdf_imp_prec(u, tag_type()) / scale;
@@ -653,7 +658,7 @@ inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>& tag)
+inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -670,7 +675,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.38823662364438342844e-4),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.05200341554753776087e-1),
             static_cast<RealType>(2.12663999430421346175e-1),
             static_cast<RealType>(7.23836000984872591553e-2),
@@ -696,7 +701,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(6.01511310581302829460e-6),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.32264360456739861886e0),
             static_cast<RealType>(6.39715443864749851087e-1),
             static_cast<RealType>(5.03940458163958921325e-1),
@@ -723,7 +728,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.29521832683440044997e-6),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(5.82002427359748247121e-1),
             static_cast<RealType>(3.96529686558825119743e-1),
             static_cast<RealType>(1.49690294526117385174e-1),
@@ -753,7 +758,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.69306881760242775488e-8),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(9.63461239051296108254e-1),
             static_cast<RealType>(6.54183344973801096611e-1),
             static_cast<RealType>(2.92007762594247903696e-1),
@@ -782,7 +787,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.09016076876928010898e-8),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.51164395622515150122e0),
             static_cast<RealType>(1.09391911233213526071e0),
             static_cast<RealType>(4.77950346062744800732e-1),
@@ -811,7 +816,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-8.80541360484428526226e-14),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.98261117346347123707e-1),
             static_cast<RealType>(1.97823959738695249267e-1),
             static_cast<RealType>(2.89311735096848395080e-2),
@@ -839,7 +844,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.20433396121606479712e-17),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.56283944667056551858e-1),
             static_cast<RealType>(2.56811818304462676948e-2),
             static_cast<RealType>(1.26678062261253559927e-3),
@@ -866,7 +871,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.03424457039308806437e-20),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.17861198759233241198e-1),
             static_cast<RealType>(5.45962263583663240699e-3),
             static_cast<RealType>(1.25274651876378267111e-4),
@@ -890,7 +895,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(3.52790131116013716885e-1),
         };
         static const RealType Q[3] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(-5.05959751628952574534e0),
             static_cast<RealType>(8.04408113719341786819e0),
         };
@@ -902,7 +907,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag)
+inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -925,7 +930,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.63937253747323898965514197114021890186e-8),
         };
         static const RealType Q[12] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76090180430550757765787254935343576341e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07685236907561593034104428156351640194e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27770556484351179553611274487979706736e-2),
@@ -961,7 +966,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.22300086876618079439960709120163780513e-8),
         };
         static const RealType Q[12] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19740977756009966244249035150363085180e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39394884078938560974435920719979860046e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.97107758486905601309707335353809421910e-2),
@@ -999,7 +1004,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59245311730292556271235324976832000740e-10),
         };
         static const RealType Q[16] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.49800491033591771256676595185869442663e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35827615015880595229881139361463765537e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41657125931991211322147702760511651998e-1),
@@ -1044,7 +1049,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.43891156389092896219387988411277617045e-15),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30840297297890638941129884491157396207e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16059271948787750556465175239345182035e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.32333703228724830516425197803770832978e-1),
@@ -1093,7 +1098,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23007623135952181561484264810647517912e-21),
         };
         static const RealType Q[19] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17760389606658547971193065026711073898e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49565543987559264712057768584303008339e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94822569926563661124528478579051628722e0),
@@ -1141,7 +1146,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.37645700309533972676063947195650607935e-26),
         };
         static const RealType Q[16] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59608758824065179587008165265773042260e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17347162462484266250945490058846704988e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.24511137251392519285309985668265122633e-1),
@@ -1185,7 +1190,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47298013808154174645356607027685011183e-32),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42561659771176310412113991024326129105e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83353398513931409985504410958429204317e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07254121026393428163401481487563215753e-2),
@@ -1227,7 +1232,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54663422572657744572284839697818435372e-36),
         };
         static const RealType Q[14] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35632539169215377884393376342532721825e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.46975491055790597767445011183622230556e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51806800870130779095309105834725930741e-3),
@@ -1261,7 +1266,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.61127812511057623691896118746981066174e0),
         };
         static const RealType Q[6] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90660291309478542795359451748753358123e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60631500002415936739518466837931659008e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.88655117367497147850617559832966816275e2),
@@ -1334,6 +1339,8 @@ inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Holtsmark distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     RealType u = (x - location) / scale;
 
     result = holtsmark_cdf_imp_prec(u, complement, tag_type());
@@ -1342,7 +1349,7 @@ inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>& tag)
+inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1363,7 +1370,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(6.57491277860092595148e-5),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.48696501912062288766e0),
             static_cast<RealType>(2.06239370128871696850e0),
             static_cast<RealType>(5.67577904795053902651e-1),
@@ -1392,7 +1399,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(3.93093062843177374871e-5),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(6.76193897442484823754e-1),
             static_cast<RealType>(3.70953499602257825764e-2),
             static_cast<RealType>(-2.84211795745477605398e-2),
@@ -1419,7 +1426,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-2.88688017391292485867e-5),
         };
         static const RealType Q[7] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(-2.72809429017073648893e-2),
             static_cast<RealType>(-7.85526213469762960803e-2),
             static_cast<RealType>(2.41360900478283465241e-2),
@@ -1448,7 +1455,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(9.66690587477825432174e-6),
         };
         static const RealType Q[10] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(1.60044610004497775009e-1),
             static_cast<RealType>(2.41675490962065446592e-1),
             static_cast<RealType>(1.13752642382290596388e-1),
@@ -1479,7 +1486,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(9.71371309261213597491e-8),
         };
         static const RealType Q[8] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(2.29132755303753682133e0),
             static_cast<RealType>(1.95530118226232968288e0),
             static_cast<RealType>(9.55029685883545321419e-1),
@@ -1509,7 +1516,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(5.58003465656339818416e-10),
         };
         static const RealType Q[10] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(8.73938978582311007855e-1),
             static_cast<RealType>(3.21771888210250878162e-1),
             static_cast<RealType>(6.70432401844821772827e-2),
@@ -1541,7 +1548,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-8.46510608386806647654e-18),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(3.81461950831351846380e-1),
             static_cast<RealType>(6.91390438866520696447e-2),
             static_cast<RealType>(7.84798596829449138229e-3),
@@ -1571,7 +1578,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(4.61294046336533026640e-9),
         };
         static const RealType Q[9] = {
-            static_cast<RealType>(1),
+            static_cast<RealType>(1.),
             static_cast<RealType>(4.49255524669251621744e-1),
             static_cast<RealType>(9.77826688966262423974e-2),
             static_cast<RealType>(1.36596271675764346980e-2),
@@ -1605,7 +1612,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
 
 template <class RealType>
-inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>& tag)
+inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1633,7 +1640,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54871597065387376666252643921309051097e-7),
             };
             static const RealType Q[13] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06310038178166385607814371094968073940e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06144046990424238286303107360481469219e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17860081295611631017119482265353540470e1),
@@ -1651,7 +1658,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
-            RealType t = u - 0.5;
+            RealType t = u - static_cast <RealType>(0.5);
 
             // Rational Approximation
             // Maximum Relative Error: 2.5554e-35
@@ -1671,7 +1678,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91383571211375811878311159248551586411e-8),
             };
             static const RealType Q[12] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96820655322136936855997114940653763917e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30209571878469737819039455443404070107e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61235660141139249931521613001554108034e-1),
@@ -1709,7 +1716,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05702214080592377840761032481067834813e-7),
             };
             static const RealType Q[12] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33954869248363301881659953529609341564e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73738626674455393272550888585363920917e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.90708494363306682523722238824373341707e-2),
@@ -1726,7 +1733,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
-            RealType t = u - 0.5;
+            RealType t = u - static_cast <RealType>(0.5);
 
             // Rational Approximation
             // Maximum Relative Error: 1.3688e-35
@@ -1745,7 +1752,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.99636080473697209793683863161785312159e-8),
             };
             static const RealType Q[12] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95056572065373808001002483348789719155e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.55702988004729812458415992666809422570e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.07586989542594910084052301521098115194e-2),
@@ -1785,7 +1792,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72723306533295983872420985773212608299e-9),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.23756826160440280076231428938184359865e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46557011055563840763437682311082689407e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18907861669025579159409035585375166964e-1),
@@ -1825,7 +1832,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29311341249565125992213260043135188072e-8),
             };
             static const RealType Q[12] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54021943144355190773797361537886598583e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30965787836836308380896385568728211303e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19314242976592846926644622802257778872e-2),
@@ -1842,7 +1849,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
-            RealType t = u - 0.5;
+            RealType t = u - static_cast <RealType>(0.5);
 
             // Rational Approximation
             // Maximum Relative Error: 8.3743e-35
@@ -1862,7 +1869,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23210708203609461650368387780135568863e-8),
             };
             static const RealType Q[11] = {
-                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.93402256203255215539822867473993726421e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42452702043886045884356307934634512995e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.16981055684612802160174937997247813645e-2),
@@ -1902,7 +1909,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17836139198065889244530078295061548097e-10),
         };
         static const RealType Q[15] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78065342260594920160228973261455037923e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08575070304822733863613657779515344137e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81185785915044621118680763035984134530e-1),
@@ -1947,7 +1954,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.88084230973635340409728710734906398080e-11),
         };
         static const RealType Q[18] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49319798750825059930589954921919984293e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90218243410186000622818205955425584848e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25384789213915993855434876209137054104e0),
@@ -1999,7 +2006,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72241483171311778625855302356391965266e-26),
         };
         static const RealType Q[21] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18341916009800042837726003154518652168e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19215655980509256344434487727207541208e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34380326549827252189214516628038733750e0),
@@ -2051,7 +2058,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.79744248200459077556218062241428072826e-32),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68930884381361438749954611436694811868e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54944129151720429074748655153760118465e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68493670923968273171437877298940102712e-2),
@@ -2099,7 +2106,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21485411177823993142696645934560017341e-40),
         };
         static const RealType Q[18] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.88559444380290379529260819350179144435e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.37942717465159991856146428659881557553e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.11409915376157429952160202733757574026e-3),
@@ -2147,7 +2154,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.13881361534205323565985756195674181203e-50),
         };
         static const RealType Q[17] = {
-            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239599863811873205236246e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849060586077266046297964e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29542078693828543540010668640353491847e-2),
@@ -2241,19 +2248,21 @@ inline RealType holtsmark_quantile_imp(const holtsmark_distribution<RealType, Po
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Holtsmark distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = location + scale * holtsmark_quantile_imp_prec(p, complement, tag_type());
 
     return result;
 }
 
 template <class RealType>
-inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>& tag)
+inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.06944850513462440032);
 }
 
 template <class RealType>
-inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>& tag)
+inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0694485051346244003155800384542166381);
 }
@@ -2282,6 +2291,8 @@ inline RealType holtsmark_entropy_imp(const holtsmark_distribution<RealType, Pol
         precision_type::value <= 113 ? 113 : 0
     > tag_type;
 
+    static_assert(tag_type::value, "The Holtsmark distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
     result = holtsmark_entropy_imp_prec<RealType>(tag_type()) + log(scale);
 
     return result;
@@ -2416,7 +2427,7 @@ inline RealType skewness(const holtsmark_distribution<RealType, Policy>& /*dist*
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Holtsmark Distribution has no skewness");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::skewness(holtsmark<%1%>&)",
@@ -2430,7 +2441,7 @@ inline RealType kurtosis(const holtsmark_distribution<RealType, Policy>& /*dist*
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Holtsmark Distribution has no kurtosis");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis(holtsmark<%1%>&)",
@@ -2444,7 +2455,7 @@ inline RealType kurtosis_excess(const holtsmark_distribution<RealType, Policy>&
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
-    static_assert(assert_type::value == 0, "assert type is undefined");
+    static_assert(assert_type::value == 0, "The Holtsmark Distribution has no kurtosis excess");
 
     return policies::raise_domain_error<RealType>(
         "boost::math::kurtosis_excess(holtsmark<%1%>&)",
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index ad81478f11..b5e17dacec 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -3,11 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsHoltsmarkTest
 #include <boost/test/included/unit_test.hpp>
+#include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/holtsmark.hpp>
+
+#if __has_include(<stdfloat>)
+# include <stdfloat>
+#endif
+
 using boost::math::holtsmark_distribution;
 using boost::multiprecision::cpp_bin_float_quad;
 
@@ -763,6 +770,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp64)
     do_test_holtsmark_pdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp64)
+{
+    do_test_holtsmark_pdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp128)
 {
     do_test_holtsmark_pdf<cpp_bin_float_quad, 113>();
@@ -773,6 +787,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
     do_test_holtsmark_cdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
+{
+    do_test_holtsmark_cdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp128)
 {
     do_test_holtsmark_cdf<cpp_bin_float_quad, 113>();
@@ -783,6 +804,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
     do_test_holtsmark_ccdf<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
+{
+    do_test_holtsmark_ccdf<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp128)
 {
     do_test_holtsmark_ccdf<cpp_bin_float_quad, 113>();
@@ -793,6 +821,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
     do_test_holtsmark_quantile_nearzero<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
+{
+    do_test_holtsmark_quantile_nearzero<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp128)
 {
     do_test_holtsmark_quantile_nearzero<cpp_bin_float_quad, 113>();
@@ -803,6 +838,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
     do_test_holtsmark_quantile_lower<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
+{
+    do_test_holtsmark_quantile_lower<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp128)
 {
     do_test_holtsmark_quantile_lower<cpp_bin_float_quad, 113>();
@@ -813,6 +855,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
     do_test_holtsmark_quantile_upper<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
+{
+    do_test_holtsmark_quantile_upper<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp128)
 {
     do_test_holtsmark_quantile_upper<cpp_bin_float_quad, 113>();
@@ -823,6 +872,13 @@ BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
     do_test_holtsmark_locscale_param<double, 53>();
 }
 
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
+{
+    do_test_holtsmark_locscale_param<std::float64_t, 53>();
+}
+#endif
+
 BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp128)
 {
     do_test_holtsmark_locscale_param<cpp_bin_float_quad, 113>();

From 07d97df50ceb04bafbeb29182dcaaf5c4b1163b6 Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Sun, 21 Jul 2024 11:54:58 +0100
Subject: [PATCH 014/399] Landau Integration testing (#1159)

* Add landau distribution

* Add landau limit test case

* Add landau document

* Landau integration testing.
Hook up tests to Jamfile.
Hook up docs by adding to dist_reference.qbk.
Add std::float64_t tests.
Hook up concept tests in instantiate.hpp.
Add to distributions.hpp
Update static_asserts with better error messages.
Add header inclusion test in dist_landau_incl_test.cpp (and fix resulting errors)

* Add missing #include.

* More Landau test fixes.

* Fix C++23 stdfloat test names.

* Final (doc) update to Landau.

---------

Co-authored-by: tk-yoshimura <yoshimura8192@gmail.com>
---
 doc/distributions/dist_reference.qbk          |    1 +
 doc/distributions/landau.qbk                  |  129 +
 doc/equations/landau_ref1.svg                 |   88 +
 doc/graphs/landau_ccdf_accuracy_64.png        |  Bin 0 -> 41960 bytes
 doc/graphs/landau_cdf_accuracy_64.png         |  Bin 0 -> 39335 bytes
 doc/graphs/landau_pdf1.svg                    | 1355 +++++
 doc/graphs/landau_pdf2.svg                    | 1313 +++++
 doc/graphs/landau_pdf_accuracy_64.png         |  Bin 0 -> 44144 bytes
 .../boost/math/concepts/std_real_concept.hpp  |   13 +-
 include/boost/math/distributions.hpp          |    1 +
 include/boost/math/distributions/cauchy.hpp   |   10 +-
 include/boost/math/distributions/fwd.hpp      |    4 +
 include/boost/math/distributions/landau.hpp   | 4570 +++++++++++++++++
 .../math/distributions/non_central_beta.hpp   |    4 +-
 include/boost/math/tools/config.hpp           |    4 +-
 test/Jamfile.v2                               |    2 +
 test/compile_test/dist_landau_incl_test.cpp   |   26 +
 test/compile_test/instantiate.hpp             |   22 +
 test/test_landau.cpp                          |  847 +++
 19 files changed, 8376 insertions(+), 13 deletions(-)
 create mode 100644 doc/distributions/landau.qbk
 create mode 100644 doc/equations/landau_ref1.svg
 create mode 100644 doc/graphs/landau_ccdf_accuracy_64.png
 create mode 100644 doc/graphs/landau_cdf_accuracy_64.png
 create mode 100644 doc/graphs/landau_pdf1.svg
 create mode 100644 doc/graphs/landau_pdf2.svg
 create mode 100644 doc/graphs/landau_pdf_accuracy_64.png
 create mode 100644 include/boost/math/distributions/landau.hpp
 create mode 100644 test/compile_test/dist_landau_incl_test.cpp
 create mode 100644 test/test_landau.cpp

diff --git a/doc/distributions/dist_reference.qbk b/doc/distributions/dist_reference.qbk
index c225d1953e..75e4d5759c 100644
--- a/doc/distributions/dist_reference.qbk
+++ b/doc/distributions/dist_reference.qbk
@@ -22,6 +22,7 @@
 [include inverse_gamma.qbk]
 [include inverse_gaussian.qbk]
 [include kolmogorov_smirnov.qbk]
+[include landau.qbk]
 [include laplace.qbk]
 [include logistic.qbk]
 [include lognormal.qbk]
diff --git a/doc/distributions/landau.qbk b/doc/distributions/landau.qbk
new file mode 100644
index 0000000000..b734505047
--- /dev/null
+++ b/doc/distributions/landau.qbk
@@ -0,0 +1,129 @@
+[section:landau_dist Landau Distribution]
+
+``#include <boost/math/distributions/landau.hpp>``
+
+   template <class RealType = double,
+             class ``__Policy``   = ``__policy_class`` >
+   class landau_distribution;
+
+   typedef landau_distribution<> landau;
+
+   template <class RealType, class ``__Policy``>
+   class landau_distribution
+   {
+   public:
+      typedef RealType  value_type;
+      typedef Policy    policy_type;
+
+      landau_distribution(RealType location = 0, RealType scale = 1);
+
+      RealType location()const;
+      RealType scale()const;
+      RealType bias()const;
+   };
+
+The [@http://en.wikipedia.org/wiki/landau_distribution Landau distribution]
+is named after Lev Landau.
+It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
+with shape parameter [alpha]=1, [beta]=1.
+
+[@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
+given by:
+
+[equation landau_ref1]  [/f(x; \mu, c)=\frac{1}{\pi c} \int_{0}^{\infty} \exp(-t) \cos \left( t \left( \frac{x-\mu}{c}\right) + \frac{2t}{\pi} \log \left( \frac{t}{c} \right)  \right) dt]
+
+The location parameter [mu] is the location of the distribution,
+while the scale parameter [c] determines the width of the distribution,
+but unlike other scalable distributions,
+it has a peculiarity that changes the location of the distribution.  If the location is
+zero, and the scale 1, then the result is a standard landau
+distribution.
+
+The distribution describe the statistical property of the energy loss by
+charged particles as they traversing a thin layer of matter.
+
+The following graph shows how the distributions moves as the
+location parameter changes:
+
+[graph landau_pdf1]
+
+While the following graph shows how the shape (scale) parameter alters
+the distribution:
+
+[graph landau_pdf2]
+
+[h4 Member Functions]
+
+   landau_distribution(RealType location = 0, RealType scale = 1);
+
+Constructs a landau distribution, with location parameter /location/
+and scale parameter /scale/.  When these parameters take their default
+values (location = 0, scale = 1)
+then the result is a Standard landau Distribution.
+
+Requires scale > 0, otherwise calls __domain_error.
+
+   RealType location()const;
+
+Returns the location parameter of the distribution.
+
+   RealType scale()const;
+
+Returns the scale parameter of the distribution.
+
+   RealType bias()const;
+
+Returns the amount of translation by the scale parameter.
+[expression bias = - 2 / [pi] log(c)]
+
+[h4 Non-member Accessors]
+
+All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
+that are generic to all distributions are supported: __usual_accessors.
+
+Note however that the landau distribution does not have a mean,
+standard deviation, etc. See __math_undefined
+[/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
+to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
+which is the default.
+
+Alternately, the functions __mean, __sd,
+__variance, __skewness, __kurtosis and __kurtosis_excess will all
+return a __domain_error if called.
+
+The domain of the random variable is \[-[max_value], +[min_value]\].
+
+[h4 Accuracy]
+
+The error is within 4 epsilon except for the rapidly decaying left tail.
+
+Errors in the PDF at 64-bit double precision:
+
+[$../graphs/landau_pdf_accuracy_64.png]
+
+Errors in the CDF at 64-bit double precision:
+
+[$../graphs/landau_cdf_accuracy_64.png]
+
+Errors in the CDF-complement at 64-bit double precision:
+
+[$../graphs/landau_ccdf_accuracy_64.png]
+
+[h4 Implementation]
+
+See references.
+
+[h4 References]
+
+* [@http://en.wikipedia.org/wiki/landau_distribution landau distribution]
+* T. Yoshimura, Numerical Evaluation and High Precision Approximation Formula for Landau Distribution,
+DOI: 10.36227/techrxiv.171822215.53612870/v2, 2024.
+
+[endsect][/section:landau_dist landau]
+
+[/ landau.qbk
+  Copyright Takuma Yoshimura 2024.
+  Distributed under the Boost Software License, Version 1.0.
+  (See accompanying file LICENSE_1_0.txt or copy at
+  http://www.boost.org/LICENSE_1_0.txt).
+]
diff --git a/doc/equations/landau_ref1.svg b/doc/equations/landau_ref1.svg
new file mode 100644
index 0000000000..19939a829f
--- /dev/null
+++ b/doc/equations/landau_ref1.svg
@@ -0,0 +1,88 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<!-- This file was generated by dvisvgm 3.0.3 -->
+<svg version='1.1' xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='269.290323pt' height='23.910579pt' viewBox='98.97879 63.760885 269.290323 23.910579'>
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new file mode 100644
index 0000000000..f07e248b15
--- /dev/null
+++ b/doc/graphs/landau_pdf1.svg
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HcmV?d00001

diff --git a/include/boost/math/concepts/std_real_concept.hpp b/include/boost/math/concepts/std_real_concept.hpp
index f77935c7fb..43f562efe1 100644
--- a/include/boost/math/concepts/std_real_concept.hpp
+++ b/include/boost/math/concepts/std_real_concept.hpp
@@ -229,19 +229,22 @@ inline boost::math::concepts::std_real_concept (nextafter)(boost::math::concepts
 { return (boost::math::nextafter)(a, b); }
 //
 // C++11 ism's
-// Note that these must not actually call the std:: versions as that precludes using this
-// header to test in C++03 mode, call the Boost versions instead:
+// Now that we only support C++11 and later, we can allow use of these:
 //
 inline boost::math::concepts::std_real_concept asinh(boost::math::concepts::std_real_concept a)
-{ return boost::math::asinh(a.value(), boost::math::policies::make_policy(boost::math::policies::overflow_error<boost::math::policies::ignore_error>())); }
+{ return std::asinh(a.value()); }
 inline boost::math::concepts::std_real_concept acosh(boost::math::concepts::std_real_concept a)
-{ return boost::math::acosh(a.value(), boost::math::policies::make_policy(boost::math::policies::overflow_error<boost::math::policies::ignore_error>())); }
+{ return std::acosh(a.value()); }
 inline boost::math::concepts::std_real_concept atanh(boost::math::concepts::std_real_concept a)
-{ return boost::math::atanh(a.value(), boost::math::policies::make_policy(boost::math::policies::overflow_error<boost::math::policies::ignore_error>())); }
+{ return std::atanh(a.value()); }
 inline bool (isfinite)(boost::math::concepts::std_real_concept a)
 {
    return (boost::math::isfinite)(a.value());
 }
+inline boost::math::concepts::std_real_concept log2(boost::math::concepts::std_real_concept a)
+{ return std::log2(a.value()); }
+inline int ilogb(boost::math::concepts::std_real_concept a)
+{ return std::ilogb(a.value()); }
 
 
 } // namespace std
diff --git a/include/boost/math/distributions.hpp b/include/boost/math/distributions.hpp
index 64da99415e..e7789319b4 100644
--- a/include/boost/math/distributions.hpp
+++ b/include/boost/math/distributions.hpp
@@ -30,6 +30,7 @@
 #include <boost/math/distributions/inverse_gamma.hpp>
 #include <boost/math/distributions/inverse_gaussian.hpp>
 #include <boost/math/distributions/kolmogorov_smirnov.hpp>
+#include <boost/math/distributions/landau.hpp>
 #include <boost/math/distributions/laplace.hpp>
 #include <boost/math/distributions/logistic.hpp>
 #include <boost/math/distributions/lognormal.hpp>
diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index d914cca77e..a18f1dc9b1 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -277,7 +277,7 @@ template <class RealType, class Policy>
 inline RealType mean(const cauchy_distribution<RealType, Policy>&)
 {  // There is no mean:
    typedef typename Policy::assert_undefined_type assert_type;
-   static_assert(assert_type::value == 0, "assert type is undefined");
+   static_assert(assert_type::value == 0, "The Cauchy Distribution has no mean");
 
    return policies::raise_domain_error<RealType>(
       "boost::math::mean(cauchy<%1%>&)",
@@ -291,7 +291,7 @@ inline RealType variance(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no variance:
    typedef typename Policy::assert_undefined_type assert_type;
-   static_assert(assert_type::value == 0, "assert type is undefined");
+   static_assert(assert_type::value == 0, "The Cauchy Distribution has no variance");
 
    return policies::raise_domain_error<RealType>(
       "boost::math::variance(cauchy<%1%>&)",
@@ -316,7 +316,7 @@ inline RealType skewness(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no skewness:
    typedef typename Policy::assert_undefined_type assert_type;
-   static_assert(assert_type::value == 0, "assert type is undefined");
+   static_assert(assert_type::value == 0, "The Cauchy Distribution has no skewness");
 
    return policies::raise_domain_error<RealType>(
       "boost::math::skewness(cauchy<%1%>&)",
@@ -330,7 +330,7 @@ inline RealType kurtosis(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no kurtosis:
    typedef typename Policy::assert_undefined_type assert_type;
-   static_assert(assert_type::value == 0, "assert type is undefined");
+   static_assert(assert_type::value == 0, "The Cauchy Distribution has no kurtosis");
 
    return policies::raise_domain_error<RealType>(
       "boost::math::kurtosis(cauchy<%1%>&)",
@@ -344,7 +344,7 @@ inline RealType kurtosis_excess(const cauchy_distribution<RealType, Policy>& /*d
 {
    // There is no kurtosis excess:
    typedef typename Policy::assert_undefined_type assert_type;
-   static_assert(assert_type::value == 0, "assert type is undefined");
+   static_assert(assert_type::value == 0, "The Cauchy Distribution has no kurtosis excess");
 
    return policies::raise_domain_error<RealType>(
       "boost::math::kurtosis_excess(cauchy<%1%>&)",
diff --git a/include/boost/math/distributions/fwd.hpp b/include/boost/math/distributions/fwd.hpp
index a3c1a41df5..72ac24335a 100644
--- a/include/boost/math/distributions/fwd.hpp
+++ b/include/boost/math/distributions/fwd.hpp
@@ -66,6 +66,9 @@ class inverse_gaussian_distribution;
 template <class RealType, class Policy>
 class kolmogorov_smirnov_distribution;
 
+template <class RealType, class Policy>
+class landau_distribution;
+
 template <class RealType, class Policy>
 class laplace_distribution;
 
@@ -136,6 +139,7 @@ class weibull_distribution;
    typedef boost::math::inverse_chi_squared_distribution<Type, Policy> inverse_chi_squared;\
    typedef boost::math::inverse_gaussian_distribution<Type, Policy> inverse_gaussian;\
    typedef boost::math::inverse_gamma_distribution<Type, Policy> inverse_gamma;\
+   typedef boost::math::landau_distribution<Type, Policy> landau;\
    typedef boost::math::laplace_distribution<Type, Policy> laplace;\
    typedef boost::math::logistic_distribution<Type, Policy> logistic;\
    typedef boost::math::lognormal_distribution<Type, Policy> lognormal;\
diff --git a/include/boost/math/distributions/landau.hpp b/include/boost/math/distributions/landau.hpp
new file mode 100644
index 0000000000..e84c95e4a3
--- /dev/null
+++ b/include/boost/math/distributions/landau.hpp
@@ -0,0 +1,4570 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_STATS_LANDAU_HPP
+#define BOOST_STATS_LANDAU_HPP
+
+#ifdef _MSC_VER
+#pragma warning(push)
+#pragma warning(disable : 4127) // conditional expression is constant
+#endif
+
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/tools/big_constant.hpp>
+#include <boost/math/distributions/complement.hpp>
+#include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/distributions/detail/derived_accessors.hpp>
+#include <boost/math/tools/rational.hpp>
+#include <utility>
+#include <cmath>
+
+namespace boost { namespace math {
+template <class RealType, class Policy>
+class landau_distribution;
+
+namespace detail {
+
+template <class RealType>
+inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 6.1179e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(2.62240126375351657026e-1),
+            static_cast<RealType>(3.37943593381366824691e-1),
+            static_cast<RealType>(1.53537606095123787618e-1),
+            static_cast<RealType>(3.01423783265555668011e-2),
+            static_cast<RealType>(2.66982581491576132363e-3),
+            static_cast<RealType>(-1.57344124519315009970e-5),
+            static_cast<RealType>(3.46237168332264544791e-7),
+            static_cast<RealType>(2.54512306953704347532e-8),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(1.61596691542333069131e0),
+            static_cast<RealType>(1.31560197919990191004e0),
+            static_cast<RealType>(6.37865139714920275881e-1),
+            static_cast<RealType>(1.99051021258743986875e-1),
+            static_cast<RealType>(3.73788085017437528274e-2),
+            static_cast<RealType>(3.72580876403774116752e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if(x < 2){
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.1560e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(1.63531240868022603476e-1),
+            static_cast<RealType>(1.42818648212508067982e-1),
+            static_cast<RealType>(4.95816076364679661943e-2),
+            static_cast<RealType>(8.59234710489723831273e-3),
+            static_cast<RealType>(5.76649181954629544285e-4),
+            static_cast<RealType>(-5.66279925274108366994e-7),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(1.41478104966077351483e0),
+            static_cast<RealType>(9.41180365857002724714e-1),
+            static_cast<RealType>(3.65084346985789448244e-1),
+            static_cast<RealType>(8.77396986274371571301e-2),
+            static_cast<RealType>(1.24233749817860139205e-2),
+            static_cast<RealType>(8.57476298543168142524e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.1732e-19
+        static const RealType P[8] = {
+            static_cast<RealType>(9.55242261334771588094e-2),
+            static_cast<RealType>(6.66529732353979943139e-2),
+            static_cast<RealType>(1.80958840194356287100e-2),
+            static_cast<RealType>(2.34205449064047793618e-3),
+            static_cast<RealType>(1.16859089123286557482e-4),
+            static_cast<RealType>(-1.48761065213531458940e-7),
+            static_cast<RealType>(4.37245276130361710865e-9),
+            static_cast<RealType>(-8.10479404400603805292e-11),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(1.21670723402658089612e0),
+            static_cast<RealType>(6.58224466688607822769e-1),
+            static_cast<RealType>(2.00828142796698077403e-1),
+            static_cast<RealType>(3.64962053761472303153e-2),
+            static_cast<RealType>(3.76034152661165826061e-3),
+            static_cast<RealType>(1.74723754509505656326e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.6621e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(3.83643820409470770350e-2),
+            static_cast<RealType>(1.97555000044256883088e-2),
+            static_cast<RealType>(3.71748668368617282698e-3),
+            static_cast<RealType>(3.04022677703754827113e-4),
+            static_cast<RealType>(8.76328889784070114569e-6),
+            static_cast<RealType>(-3.34900379044743745961e-9),
+            static_cast<RealType>(5.36581791174380716937e-11),
+            static_cast<RealType>(-5.50656207669255770963e-13),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(9.09290785092251223006e-1),
+            static_cast<RealType>(3.49404120360701349529e-1),
+            static_cast<RealType>(7.23730835206014275634e-2),
+            static_cast<RealType>(8.47875744543245845354e-3),
+            static_cast<RealType>(5.28021165718081084884e-4),
+            static_cast<RealType>(1.33941126695887244822e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.6311e-19
+        static const RealType P[8] = {
+            static_cast<RealType>(1.12656323880287532947e-2),
+            static_cast<RealType>(2.87311140580416132088e-3),
+            static_cast<RealType>(2.61788674390925516376e-4),
+            static_cast<RealType>(9.74096895307400300508e-6),
+            static_cast<RealType>(1.19317564431052244154e-7),
+            static_cast<RealType>(-6.99543778035110375565e-12),
+            static_cast<RealType>(4.33383971045699197233e-14),
+            static_cast<RealType>(-1.75185581239955717728e-16),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(4.94430267268436822392e-1),
+            static_cast<RealType>(1.00370783567964448346e-1),
+            static_cast<RealType>(1.05989564733662652696e-2),
+            static_cast<RealType>(6.04942184472254239897e-4),
+            static_cast<RealType>(1.72741008294864428917e-5),
+            static_cast<RealType>(1.85398104367945191152e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.6459e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(2.83847488747490686627e-3),
+            static_cast<RealType>(4.95641151588714788287e-4),
+            static_cast<RealType>(2.79159792287747766415e-5),
+            static_cast<RealType>(5.93951761884139733619e-7),
+            static_cast<RealType>(3.89602689555407749477e-9),
+            static_cast<RealType>(-4.86595415551823027835e-14),
+            static_cast<RealType>(9.68524606019510324447e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(3.01847536766892219351e-1),
+            static_cast<RealType>(3.63152433272831196527e-2),
+            static_cast<RealType>(2.20938897517130866817e-3),
+            static_cast<RealType>(7.05424834024833384294e-5),
+            static_cast<RealType>(1.09010608366510938768e-6),
+            static_cast<RealType>(6.08711307451776092405e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5205e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(6.85767880395157523315e-4),
+            static_cast<RealType>(4.08288098461672797376e-5),
+            static_cast<RealType>(8.10640732723079320426e-7),
+            static_cast<RealType>(6.10891161505083972565e-9),
+            static_cast<RealType>(1.37951861368789813737e-11),
+            static_cast<RealType>(-1.25906441382637535543e-17),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(1.23722380864018634550e-1),
+            static_cast<RealType>(6.05800403141772433527e-3),
+            static_cast<RealType>(1.47809654123655473551e-4),
+            static_cast<RealType>(1.84909364620926802201e-6),
+            static_cast<RealType>(1.08158235309005492372e-8),
+            static_cast<RealType>(2.16335841791921214702e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(x) < 8) {
+        RealType t = log2(ldexp(x, -6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.5572e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(6.78613480244945294595e-1),
+            static_cast<RealType>(9.61675759893298556080e-1),
+            static_cast<RealType>(3.45159462006746978086e-1),
+            static_cast<RealType>(6.32803373041761027814e-2),
+            static_cast<RealType>(6.93646175256407852991e-3),
+            static_cast<RealType>(4.69867700169714338273e-4),
+            static_cast<RealType>(1.76219117171149694118e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(1.44693640094228656726e0),
+            static_cast<RealType>(5.46298626321591162873e-1),
+            static_cast<RealType>(1.01572892952421447864e-1),
+            static_cast<RealType>(1.04982575345680980744e-2),
+            static_cast<RealType>(7.65591730392359463367e-4),
+            static_cast<RealType>(2.69383817793665674679e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 16) {
+        RealType t = log2(ldexp(x, -8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.7408e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.51438485661317103070e-1),
+            static_cast<RealType>(2.67941671074735988081e-1),
+            static_cast<RealType>(5.18564629295719783781e-2),
+            static_cast<RealType>(6.18976337233135940231e-3),
+            static_cast<RealType>(5.08042228681335953236e-4),
+            static_cast<RealType>(2.97268230746003939324e-5),
+            static_cast<RealType>(1.24283200336057908183e-6),
+            static_cast<RealType>(3.35670921544537716055e-8),
+            static_cast<RealType>(5.06987792821954864905e-10),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(4.23792506680780833665e-1),
+            static_cast<RealType>(8.17040643791396371682e-2),
+            static_cast<RealType>(9.63961713981621216197e-3),
+            static_cast<RealType>(8.06584713485725204135e-4),
+            static_cast<RealType>(4.62050471704120102023e-5),
+            static_cast<RealType>(1.96919734048024406173e-6),
+            static_cast<RealType>(5.23890369587103685278e-8),
+            static_cast<RealType>(7.99399970089366802728e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 32) {
+        RealType t = log2(ldexp(x, -16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0195e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(6.36745544906925230102e-1),
+            static_cast<RealType>(2.06319686601209029700e-1),
+            static_cast<RealType>(3.27498059700133287053e-2),
+            static_cast<RealType>(3.30913729536910108000e-3),
+            static_cast<RealType>(2.34809665750270531592e-4),
+            static_cast<RealType>(1.21234086846551635407e-5),
+            static_cast<RealType>(4.55253563898240922019e-7),
+            static_cast<RealType>(1.17544434819877511707e-8),
+            static_cast<RealType>(1.76754192209232807941e-10),
+            static_cast<RealType>(-2.78616504641875874275e-17),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(3.24145654925686670201e-1),
+            static_cast<RealType>(5.14350019501887110402e-2),
+            static_cast<RealType>(5.19867984016649969928e-3),
+            static_cast<RealType>(3.68798608372265018587e-4),
+            static_cast<RealType>(1.90449594112666257344e-5),
+            static_cast<RealType>(7.15068261954120746192e-7),
+            static_cast<RealType>(1.84646096630493837656e-8),
+            static_cast<RealType>(2.77636277083994601941e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 64) {
+        RealType t = log2(ldexp(x, -32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.0433e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.36619776379492082324e-1),
+            static_cast<RealType>(2.68158440168597706495e-1),
+            static_cast<RealType>(5.49040993767853738389e-2),
+            static_cast<RealType>(7.23458585096723552751e-3),
+            static_cast<RealType>(6.85438876301780090281e-4),
+            static_cast<RealType>(4.84561891424380633578e-5),
+            static_cast<RealType>(2.82092117716081590941e-6),
+            static_cast<RealType>(9.57557353473514565245e-8),
+            static_cast<RealType>(5.16773829224576217348e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1.),
+            static_cast<RealType>(4.21222294324039934056e-1),
+            static_cast<RealType>(8.62431574655015481812e-2),
+            static_cast<RealType>(1.13640608906815986975e-2),
+            static_cast<RealType>(1.07668486873466248474e-3),
+            static_cast<RealType>(7.61148039258802068270e-5),
+            static_cast<RealType>(4.43109262308946031382e-6),
+            static_cast<RealType>(1.50412757354817481381e-7),
+            static_cast<RealType>(8.11746432728995551732e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else{
+        result = 2 / (constants::pi<RealType>() * x * x);
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 7.4629e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62240126375351657025589608183516471315e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94698530837122818345222883832757839888e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06728003509081587907620543204047536319e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.41256254272104786752190871391781331271e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34420233794664437979710204055323742199e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55021337841765667713712845735938627884e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90557752737535583908921594594761570259e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.89899202021818926241643215600800085123e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.19635143827754893815649685600837995626e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90989458941330917626663002392683325107e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92038069341802550019371049232152823407e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.40251964644989324856906264776204142653e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55873076454666680466531097660277995317e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.80771940886011613393622410616035955976e-13),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35771004134750535117224809381897395331e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37002484862962406489509174332580745411e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.40833952846707180337506160933176158766e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81709029902887471895588386777029652661e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98824705588020901032379932614151640505e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.83767868823957223030472664574235892682e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35718995485026064249286377096427165287e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37305148463792922843850823142976586205e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06575764439154972544253668821920460826e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07663693811543002088092708395572161856e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09711221791106684926377106608027279057e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91302186546138009232520527964387543006e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.6684e-38
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63531240868022603475813051802104652763e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17803013130262393286657457221415701909e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77780575692956605214628767143941600132e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44224824965135546671876867759691622832e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.93294212655117265065191070995706405837e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16021988737209938284910541133167243163e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89245591723934954825306673917695058577e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09614731993308746343064543583426077485e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48578173962833046113032690615443901556e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91098199913613774034789276073191721350e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.46788618410999858374206722394998550706e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.14296339768511312584670061679121003569e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.52631422678659858574974085885146420544e-15),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.48481735580594347909096198787726314434e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91598585888012869317473155570063821216e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12672162924784178863164220170459406872e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06981909640884405591730537337036849744e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.89767326897694369071250285702215471082e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05098647402530640576816174680275844283e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10454903166951593161839822697382452489e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08850649343579977859251275585834901546e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21168773136767495960695426112972188729e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21420361560900449851206650427538430926e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.84456961344035545134425261150891935402e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46462389440125559723382692664970874255e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.3397e-35
+        static const RealType P[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55242261334771588093967856464157010584e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48866040463435403672044647455806606078e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04241715667984551487882549843428953917e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.32030608366022483736940428739436921577e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17209924605508887793687609139940354371e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.16808856405217460367038406337257561698e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75466331296758720822164534334356742122e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35657250222166360635152712608912585973e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28870137478821561164537700376942753108e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07556331078347991810236646922418944687e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18067019247793233704208913546277631267e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96745094401496364651919224112160111958e-12),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07735872062601280828576861757316683396e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00667909426245388114411629440735066799e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18840123665979969294228925712434860653e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79233661359264185181083948452464063323e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38221013998193410441723488211346327478e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91365002115280149925615665651486504495e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50379182630668701710656913597366961277e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03946139315999749917224356955071595508e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95417998434227083224840824790387887539e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05109028829536837163462811783445124876e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.33125282515685091345480270760501403655e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.58127838888839012133236453180928291822e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64781659622256824499981528095809140284e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.0238e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83643820409470770350079809236512802618e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02996762669868036727057860510914079553e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88220267784864518806154823373656292346e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.12677705163934102871251710968247891123e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96642570169484318623869835991454809217e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04358807405587072010621764865118316919e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09461879230275452416933096674703383719e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06823998699058163165831211561331795518e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24129479811279469256914665585439417704e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01799222004929573125167949870797564244e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27744716755834439008073010185921331093e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.64210356143729930758657624381557123115e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11666384975358223644665199669986358056e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.30202644697506464624965700043476935471e-22),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44479208003384373099160875893986831861e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.54290037675901616362332580709754113529e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79815821498858750185823401350096868195e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01076480676864621093034009679744852375e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88607467767854661547920709472888000469e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51572461182263866462295745828009170865e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39843444671402317250813055670653845815e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60546478324160472036295355872288494327e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.25462551353792877506974677628167909695e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05915328498722701961972258866550409117e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20632869761578411246344533841556350518e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99438347491752820345051091574883391217e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.2541e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12656323880287532946687856443190592955e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31374972240605659239154788518240221417e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10776910971729651587578902049263096117e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.53872632372452909103332647334935138324e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81756147611150151751911596225474463602e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75302607308223110644722612796766590029e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33839913867469199941739467004997833889e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.32115127487193219555283158969582307620e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.90766547421015851413713511917307214275e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08939895797457378361211153362169024503e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88597187949354708113046662952288249250e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62829447082637808482463811005771133942e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.65525705592205245661726488519562256000e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60698835222044786453848932477732972928e-26),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88605948104664828377228254521124685930e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.58594705700945215121673591119784576258e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.67113091918430152113322758216774649130e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39583889554372147091140765508385042797e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57139043074134496391251233307552940106e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26451960029396455805403758307828624817e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.30400557427446929311350088728080667203e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99617890540456503276038942480115937467e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.50232186816498003232143065883536003942e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59310652872918546431499274822722004981e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82203579442241682923277858553949327687e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10345359368438386945407402887625511801e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55225829972215033873365516486524181445e-17),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.1276e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83847488747490686627461184914507143000e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61220392257287638364190361688188696363e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42217711448675893329072184826328300776e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20597728166467972373586650878478687059e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.46404433551447410467051774706080733051e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27909145305324391651548849043874549520e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.33564789388635859003082815215888382619e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.18456219811686603951886248687349029515e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.92730718471866912036453008101994816885e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.51773776414973336511129801645901922234e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32371094281803507447435352076735970857e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44775294242071078601023962869394690897e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.94920633206242554892676642458535141153e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18030442958390399095902441284074544279e-31),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65871972115253665568580046072625013145e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.74531522538358367003224536101724206626e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20716479628426451344205712137554469781e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.83247584368619500260722365812456197226e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.52931189426842216323461406426803698335e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19343566926626449933230814579037896037e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.16243058880148231471744235009435586353e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21344088555713979086041331387697053780e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63246599173435592817113618949498524238e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43426263963680589288791782556801934305e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.62386317351298917459659548443220451300e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13281535580097407374477446521496074453e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27187882784316306216858933778750811182e-21),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.8458e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85767880395157523314894776472286059373e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07684379950498990874449661385130414967e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.29181715091139597455177955800910928786e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78745116935613858188145093313446961899e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.61522707085521545633529621526418843836e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00989556810424018339768632204186394735e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94136605359672888838088037894401904574e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.15203266224687619299892471650072720579e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25349098945982074415471295859193558426e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31874620165906020409111024866737082384e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19330888204484008667352280840160186671e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.89951131249530265518610784629981482444e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35979606245171162602352579985003194602e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.50946115943875327149319867495704969908e-36),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21212467547297045538111676107434471585e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17663841151156626845609176694801024524e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25478800461954401173897968683982253458e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.69831763649657690166671862562231448718e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19712058726935472913461138967922524612e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11423395018514913507624349385447326009e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58664605420655866109404476637021322838e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15398721299264752103644541934654351463e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17567858878427250079920401604119982576e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92808825029184923713064129493385469531e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06007644624654848502783947087038305433e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.01246784499782934986619755015082182398e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(x) < 8) {
+        RealType t = log2(ldexp(x, -6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.6634e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78613480244945294594505480426643613242e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07362312709864018864207848733814857157e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47727521897653923649758175033206259109e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04183129813120998456717217121703605830e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09978729224187570508825456585418357590e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98739784100617344335742510102186570437e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08596635852958074572320481325030046975e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34947456497875218771996878497766058580e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31766866003171430205401377671093088134e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29444683984117745298484117924452498776e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34885173277203843795065094551227568738e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30306828175920576070486704404727265760e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.05908347665846652276910544097430115068e-13),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07218191317166728296013167220324207427e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38908532499742180532814291654329829544e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63676664387672566455490461784630320677e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31302647779056928216789214742790688980e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.69477260342662648574925942030720482689e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.82918424748192763052497731722563414651e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69244295675395948278971027618145225216e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08928780307959133484802547123672997757e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.11055350627948183551681634293425028439e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22066081452382450191191677443527136733e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78025987104169227624653323808131280009e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93164997733174955208299290433803918816e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 16) {
+        RealType t = log2(ldexp(x, -8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.1919e-36
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51438485661317103069553924870169052838e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.29652867028564588922931020456447362877e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90557738902930002845457640269863338815e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.47622170600415955276436226439948455362e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75198213226024095368607442455597948634e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73010116224706573149404022585502812698e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33440551266376466187512220300943206212e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27556365758364667507686872656121131255e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63395763346533783414747536236033733143e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75408632486279069728789506666930014630e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.74194099205847568739445023334735086627e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52462367172968216583968200390021647482e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75367408334713835736514158797013854282e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62633983586253025227038002631010874719e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46717630077826649018810277799043037738e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00642537643332236333695338824014611799e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47351714774371338348451112020520067028e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15896012319823666881998903857141624070e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62176014448801854863922778456328119208e-25),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.79042471052521112984740498925369905803e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.55058068535501327896327971200536085268e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33143443551335870264469963604049242325e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75325348141376361676246108294525717629e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28871858542582365161221803267369985933e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.23702867786056336210872367019916245663e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.14513776996445072162386201808986222616e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13763070277828149031445006534179375988e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75529866599039195417128499359378019030e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53029524184341515115464886126119582515e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.10598685541492162454676538516969294049e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75587930183994618721688808612207567233e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.83150895141383746641924725237948860959e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30675015193353451939138512698571954110e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.71774361582156518394662911172142577047e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.03397072601182597002547703682673198965e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.52666999314026491934445577764441483687e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 32) {
+        RealType t = log2(ldexp(x, -16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2411e-36
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36745544906925230101752563433306496000e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73688900814770369626527563956988302379e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81718746296195151971617726268038570065e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.13663059680440438907042970413471861121e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.40004645275531255402942177790836798523e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80059489775751412372432345156902685277e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47699576477278882708291693658669435536e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45226121992756638990044029871581321461e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13406331882918393195342615955627442395e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46682598893946975917562485374893408094e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50450743907497671918301557074470352707e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.33121239192492785826422815650499088833e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05998176182038788839361491871608950696e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17857918044922309623941523489531919822e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.67865547879145051715131144371287619666e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.89654931108624296326740455618289840327e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73017950634516660552375272495618707905e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68519137981001059472024985205381913202e-24),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.29948066505039082395951244410552705780e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.13730690908098361287472898564563217987e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27810872138103132689695155123062073221e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31948058845675193039732511839435290811e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06822729610151747708260147063757668707e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.03250522904270408071762059653475885811e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85197262150009124871794386644476067020e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78139536405831228129042087771755615472e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01642938314578533660138738069251610818e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36328724659833107203404258336776286146e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80342430290059616305921915291683180697e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66502051110007556897014898713746069491e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42209715361911856322028597714105225748e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.77842582605458905635718323117222788078e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.69147628396460384758492682185049535079e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.43015110519230289924122344324563890953e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21788819753161690674882271896091269356e-24),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 64) {
+        RealType t = log2(ldexp(x, -32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0348e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619776379492082323649724050601750141e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29818158612993476124594583743266388964e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07736315744724186061845512973085067283e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72566458808745644851080213349673559756e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.01243670706840752914099834172565920736e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65306557791300593593488790517297048902e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41751291649776832705247036453540452119e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26652535267657618112731521308564571490e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32742926765578976373764178875983383214e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.32948532312961882464151446137719196209e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96536595631611560703804402181953334762e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48463581600017734001916804890205661347e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.65588239861378749665334852913775575615e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39462290798829172203386678450961569536e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83049279786679854738508318703604392055e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87131679136229094080572090496960701828e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35977519905679446758726709186381481753e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.50639358104925465711435411537609380290e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.47593981758247424082096107205150226114e-40),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60997521267746350015610841742718472657e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.40470704349086277215167519790809981379e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.42305660178694704379572259575557934523e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30272082429322808188807034927827414359e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16742567294582284534194935923915261582e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22662407906450293978092195442686428843e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.84343501655116670387608730076359018869e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65591734166216912475609790035240582537e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15131286290573570519912674341226377625e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08718962387679715644203327604824250850e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.04444946843492647477476784817227903589e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35966282749098189010715902284098451987e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19066854132814661112207991393498039851e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87533136296192957063599695937632598999e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93945754223094281767677343057286164777e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13592988790740273103099465658198617078e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.64942281110142621080966631872844557766e-26),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else if (ilogb(x) < 128) {
+        RealType t = log2(ldexp(x, -64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.3963e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344984274685280416528592e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72417390936686577479751162141499390532e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74319117326966091295365258834959120634e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94269681742277805376258823511210253023e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09354876913180019634171748490068797632e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.46986612543101357465265079580805403382e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21726753043764920243710352514279216684e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29971756326232375757519588897328507962e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06770117983967828996891025614645348127e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27141668055392041978388268556174062945e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48383887723476619460217715361289178429e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49530301203157403427315504054500005836e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18668427867427341566476567665953082312e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73377083349017331494144334612902128610e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32380647653444581710582396517056104063e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.29865827039123699411352876626634361936e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07464506614287925844993490382319608619e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60173555862875972119871402681133785088e-23),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27912237038396638341492536677313983747e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02138359905285600768927677649467546192e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24763589856532154099789305018886222841e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27133166772875885088000073325642460162e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01628419446817660009223289575239926907e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62446834592284424116329218260348474201e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61238790103816844895453935630752859272e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67714109140674398508739253084218270557e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70952563202454851902810005226033501692e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33080865791583428494353408816388908148e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06120545912923145572220606396715398781e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86403930600680015325844027465766431761e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.29419718354538719350803683985104818654e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.36261565790718847159482447247645891176e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46062982552515416754702177333530968405e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68804852250549346018535616711418533423e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51600033199082754845231795160728350588e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
+    }
+    else {
+        result = 2 / (constants::pi<RealType>() * x * x);
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if(x >= -1){
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.3928e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(2.21762208692280384264e-1),
+            static_cast<RealType>(7.10041055270973473923e-1),
+            static_cast<RealType>(8.66556480457430718380e-1),
+            static_cast<RealType>(4.78718713740071686348e-1),
+            static_cast<RealType>(1.03670563650247405820e-1),
+            static_cast<RealType>(4.31699263023057628473e-3),
+            static_cast<RealType>(1.72029926636215817416e-3),
+            static_cast<RealType>(-2.76271972015177236271e-4),
+            static_cast<RealType>(1.89483904652983701680e-5),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.18155995697310361937e0),
+            static_cast<RealType>(2.53173077603836285217e0),
+            static_cast<RealType>(1.91802065831309251416e0),
+            static_cast<RealType>(9.94481663032480077373e-1),
+            static_cast<RealType>(3.72037148486473195054e-1),
+            static_cast<RealType>(8.85828240211801048938e-2),
+            static_cast<RealType>(1.41354784778520560313e-2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.4742e-18
+        static const RealType P[11] = {
+            static_cast<RealType>(6.50763682207511020789e-3),
+            static_cast<RealType>(5.73790055136022120436e-2),
+            static_cast<RealType>(2.22375662069496257066e-1),
+            static_cast<RealType>(4.92288611166073916396e-1),
+            static_cast<RealType>(6.74552077334695078716e-1),
+            static_cast<RealType>(5.75057550963763663751e-1),
+            static_cast<RealType>(2.85690710485234671432e-1),
+            static_cast<RealType>(6.73776735655426117231e-2),
+            static_cast<RealType>(3.80321995712675339999e-3),
+            static_cast<RealType>(1.09503400950148681072e-3),
+            static_cast<RealType>(-9.00045301380982997382e-5),
+        };
+        static const RealType Q[11] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.07919389927659014373e0),
+            static_cast<RealType>(2.56142472873207168042e0),
+            static_cast<RealType>(1.68357271228504881003e0),
+            static_cast<RealType>(2.23924151033591770613e0),
+            static_cast<RealType>(9.05629695159584880257e-1),
+            static_cast<RealType>(8.94372028246671579022e-1),
+            static_cast<RealType>(1.98616842716090037437e-1),
+            static_cast<RealType>(1.70142519339469434183e-1),
+            static_cast<RealType>(1.46288923980509020713e-2),
+            static_cast<RealType>(1.26171654901120724762e-2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        const static RealType lambda_bias = static_cast<RealType>(1.45158270528945486473); // (= log(pi/2)+1)
+
+        RealType sigma = exp(-x * constants::pi<RealType>() / 2 - lambda_bias);
+        RealType s = exp(-sigma) * sqrt(sigma);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 5.8685e-18
+            static const RealType P[8] = {
+                static_cast<RealType>(6.31126317567898819465e-1),
+                static_cast<RealType>(5.28493759149515726917e-1),
+                static_cast<RealType>(3.28301410420682938866e-1),
+                static_cast<RealType>(1.31682639578153092699e-1),
+                static_cast<RealType>(3.86573798047656547423e-2),
+                static_cast<RealType>(7.77797337463414935830e-3),
+                static_cast<RealType>(9.97883658430364658707e-4),
+                static_cast<RealType>(6.05131104440018116255e-5),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(8.47781139548258655981e-1),
+                static_cast<RealType>(5.21797290075642096762e-1),
+                static_cast<RealType>(2.10939174293308469446e-1),
+                static_cast<RealType>(6.14856955543769263502e-2),
+                static_cast<RealType>(1.24427885618560158811e-2),
+                static_cast<RealType>(1.58973907730896566627e-3),
+                static_cast<RealType>(9.66647686344466292608e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -5.1328125) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 3.2532e-17
+            static const RealType P[9] = {
+                static_cast<RealType>(6.26864481454444278646e-1),
+                static_cast<RealType>(5.10647753508714204745e-1),
+                static_cast<RealType>(1.98551443303285119497e-1),
+                static_cast<RealType>(4.71644854289800143386e-2),
+                static_cast<RealType>(7.71285919105951697285e-3),
+                static_cast<RealType>(8.93551020612017939395e-4),
+                static_cast<RealType>(6.97020145401946303751e-5),
+                static_cast<RealType>(4.17249760274638104772e-6),
+                static_cast<RealType>(7.73502439313710606153e-12),
+            };
+            static const RealType Q[8] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(8.15124079722976906223e-1),
+                static_cast<RealType>(3.16755852188961901369e-1),
+                static_cast<RealType>(7.52819418000330690962e-2),
+                static_cast<RealType>(1.23053506566779662890e-2),
+                static_cast<RealType>(1.42615273721494498141e-3),
+                static_cast<RealType>(1.11211928184477279204e-4),
+                static_cast<RealType>(6.65899898061789485757e-6),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2803e-36
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21762208692280384264052188465103527015e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07121154108880017947709737976750200391e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34036993772851526455115746887751392080e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06347688547967680654012636399459376006e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68662427153576049083876306225433068713e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67496398036468361727297056409545434117e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.69289909624425652939466055042210850769e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65649060232973461318206716040181929160e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.93006819232611588097575675157841312689e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34514211575975820725706925256381036061e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86184594939834946952489805173559003431e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66982890863184520310462776294335540260e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.28944885271022303878175622411438230193e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.47136245900831864668353768185407977846e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98034330388999615249606466662289782222e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.67931741921878993598048665757824165533e-12),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81019852414657529520034272090632311645e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.51602582973416348091361820936922274106e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.87246706500788771729605610442552651673e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55758863380051182011815572544985924963e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.16921634066377885762356020006515057786e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28590978860106110644638308039189352463e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07182688002603587927920766666962846169e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.14413931232875917473403467095618397172e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59534588679183116305361784906322155131e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62788361787003488572546802835677555151e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32291670834750583053201239125839728061e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97300476673137879475887158731166178829e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99801949382703479169010768105376163814e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09234481837537672361990844588166022791e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.8590e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.50763682207511020788551990942118742910e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35160148798611192350830963080055471564e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85567614778755464918744664468938413626e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24395902843792338723377508551415399267e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75803588325237557939443967923337822799e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44751743702858358960016891543930028989e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38771920793989989423514808134997891434e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99899457801652012757624005300136548027e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.59668432891116320233415536189782241116e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02521376213276025040458141317737977692e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.00511857068867825025582508627038721402e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19031970665203475373248353773765801546e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03203906044415590651592066934331209362e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01354553335348149914596284286907046333e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40077709279222086527834844446288408059e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07036291955272673946830858788691198641e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75229595324028909877518859428663744660e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.51522041748753421579496885726802106514e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28554063325397021905295499768922434904e-10),
+        };
+        static const RealType Q[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55889733194498836168215560931863059152e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45050534010127542130960211621894286688e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39437268390909980446225806216001154876e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85370557677145869100298813360909127310e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99358236671478050470186012149124879556e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82914467302553175692644992910876515874e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42426383410763382224410804289834740252e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69477085497572590673874940261777949808e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.69832833104494997844651343499526754631e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95708391432781281454592429473451742972e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32541987059874996779040445020449508142e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.24889827757289516008834701298899804535e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76326709965329347689033555841964826234e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.19652942193884551681987290472603208296e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22987197033955835618810845653379470109e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51893290463268547258382709202599507274e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43575882043846146581825453522967678538e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06683418138599962787868832158681391673e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        const static RealType lambda_bias = BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.451582705289454864726195229894882143572); // (= log(pi/2)+1)
+
+        RealType sigma = exp(-x * constants::pi<RealType>() / 2 - lambda_bias);
+        RealType s = exp(-sigma) * sqrt(sigma);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 7.0019e-35
+            static const RealType P[18] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31126317567898819464557840628449107915e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31008645911415314700225107327351636697e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.60743397071713227215207831174512626190e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69243936604887410595461520921270733657e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93778117053417749769040328795824088196e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04718815412035890861219665332918840537e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41914050146414549019258775115663029791e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17147074474397510167661838243237386450e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31006358624990533313832878493963971249e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.31424805670861981190416637260176493218e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71604447221961082506919140038819715820e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.01796816886825676412069047911936154422e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16975381608692872525287947181531051179e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47194712963929503930146780326366215579e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19469248860267489980690249379132289464e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22272545853285700254948346226514762534e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.05432616288832680241611577865488417904e-13),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08723511461992818779941378551362882730e-14),
+            };
+            static const RealType Q[16] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01021278581037282130358759075689669228e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.91783545335316986601746168681457332835e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90025337163174587593060864843160047245e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09029833197792884728968597136867674585e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44295160726145715084515736090313329125e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46416375246465800703437031839310870287e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86521610039165178072099210670199368231e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29830357713744587265637686549132688965e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32187562202835921333177458294507064946e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75034541113922116856456794810138543224e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79216314818261657918748858010817570215e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.69179323869133503169292092727333289999e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.09019623876540244217038375274802731869e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13900582194674129200395213522524183495e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92590979457175565666605415984496551246e-9),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -6.875) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 6.4095e-35
+            static const RealType P[18] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26864481454444278645937156746132802908e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35052316263030534355724898036735352905e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46701697626917441774916114124028252971e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03805679118924248671851611170709699862e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29457230118834515743802694404620370943e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04992992250026414994541561073467805333e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.21521951889983113700615967351903983850e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50611640491200231504944279876023072268e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96007721851412367657495076592244098807e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76876967456744990483799856564174838073e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34285198828980523126745002596084187049e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.98811180672843179022928339476420108494e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36933707823930146448761204037985193905e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.76515121042989743198432939393805252169e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87259915481622487665138935922067520210e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34703958446785695676542385299325713141e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53199672688507288037695102377982544434e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.97283413733676690377949556457649405210e-14),
+            };
+            static const RealType Q[18] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15492787140203223641846510939273526038e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34095796298757853634036909432345998054e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65650140652391522296109869665871008634e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.44894089102275258806976831589022821974e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27121975866547045393504246592187721233e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.91803733484503004520983723890062644122e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40341451263971324381655967408519161854e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72360046810103129487529493828280649599e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.60986435254173073868329335245110986549e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01216966786091058959421242465309838187e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11514619470960373138100691463949937779e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01639426441970732201346798259534312372e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.60411422906070056043690129326288757143e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58398956202137709744885774931524547894e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14956902064425256856583295469934064903e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23201118234279642321630988607491208515e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43185798646451225275728735761433082676e-13),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+    if (x >= 0) {
+        return landau_pdf_plus_imp_prec<RealType>(x, tag);
+    }
+    else if (x <= 0) {
+        return landau_pdf_minus_imp_prec<RealType>(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return landau_pdf_plus_imp_prec<RealType>(x, tag);
+    }
+    else if (x <= 0) {
+        return landau_pdf_minus_imp_prec<RealType>(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType landau_pdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x) {
+    //
+    // This calculates the pdf of the Landau distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::pdf(landau<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+    RealType bias = dist.bias();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    RealType u = (x - location) / scale + bias;
+
+    result = landau_pdf_imp_prec(u, tag_type()) / scale;
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 2.7348e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(6.34761298487625202628e-1),
+            static_cast<RealType>(7.86558857265845597915e-1),
+            static_cast<RealType>(4.30220871807399303399e-1),
+            static_cast<RealType>(1.26410946316538340541e-1),
+            static_cast<RealType>(2.09346669713191648490e-2),
+            static_cast<RealType>(1.48926177023501002834e-3),
+            static_cast<RealType>(-5.93750588554108593271e-7),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.65227304522196452589e0),
+            static_cast<RealType>(1.29276828719607419526e0),
+            static_cast<RealType>(5.93815051307098615300e-1),
+            static_cast<RealType>(1.69165968013666952456e-1),
+            static_cast<RealType>(2.84272940328510367574e-2),
+            static_cast<RealType>(2.28001970477820696422e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.1487e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(4.22133240358047652363e-1),
+            static_cast<RealType>(3.48421126689016131480e-1),
+            static_cast<RealType>(1.15402429637790321091e-1),
+            static_cast<RealType>(1.90374044978864005061e-2),
+            static_cast<RealType>(1.26628667888851698698e-3),
+            static_cast<RealType>(-5.75103242931559285281e-7),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.21277435324167238159e0),
+            static_cast<RealType>(6.38324046905267845243e-1),
+            static_cast<RealType>(1.81723381692749892660e-1),
+            static_cast<RealType>(2.80457012073363245106e-2),
+            static_cast<RealType>(1.93749385908189487538e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.2975e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(2.95892137955791216378e-1),
+            static_cast<RealType>(2.29083899043580095868e-1),
+            static_cast<RealType>(7.09374171394372356009e-2),
+            static_cast<RealType>(1.08774274442674552229e-2),
+            static_cast<RealType>(7.69674715320139398655e-4),
+            static_cast<RealType>(1.63486840000680408991e-5),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.09704883482087441931e0),
+            static_cast<RealType>(5.10139057077147935327e-1),
+            static_cast<RealType>(1.27055234007499238241e-1),
+            static_cast<RealType>(1.74542139987310825683e-2),
+            static_cast<RealType>(1.18944143641885993718e-3),
+            static_cast<RealType>(2.55296292914537992309e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.6740e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(1.73159318667565938776e-1),
+            static_cast<RealType>(6.95847424776057206679e-2),
+            static_cast<RealType>(1.04513924567165899506e-2),
+            static_cast<RealType>(6.35094718543965631442e-4),
+            static_cast<RealType>(1.04166111154771164657e-5),
+            static_cast<RealType>(1.43633490646363733467e-9),
+            static_cast<RealType>(-4.55493341295654514558e-11),
+            static_cast<RealType>(6.71119091495929467041e-13),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.23409270429130114247e-1),
+            static_cast<RealType>(1.54791925441839372663e-1),
+            static_cast<RealType>(1.85626981728559445893e-2),
+            static_cast<RealType>(1.01414235673220405086e-3),
+            static_cast<RealType>(1.63385654535791481980e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.6772e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(8.90469147411748292410e-2),
+            static_cast<RealType>(2.76033447621178662228e-2),
+            static_cast<RealType>(3.26577485081539607943e-3),
+            static_cast<RealType>(1.77755752909150255339e-4),
+            static_cast<RealType>(4.20716551767396206445e-6),
+            static_cast<RealType>(3.19415703637929092564e-8),
+            static_cast<RealType>(-1.79900915228302845362e-13),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.36499987260915480890e-1),
+            static_cast<RealType>(7.67544181756713372678e-2),
+            static_cast<RealType>(6.83535263652329633233e-3),
+            static_cast<RealType>(3.15983778969051850073e-4),
+            static_cast<RealType>(6.84144567273078698399e-6),
+            static_cast<RealType>(5.00300197147417963939e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.5678e-20
+        static const RealType P[8] = {
+            static_cast<RealType>(4.35157264931262089762e-2),
+            static_cast<RealType>(8.46833474333913742597e-3),
+            static_cast<RealType>(6.43769318301002170686e-4),
+            static_cast<RealType>(2.39440197089740502223e-5),
+            static_cast<RealType>(4.45572968892675484685e-7),
+            static_cast<RealType>(3.76071815793351687179e-9),
+            static_cast<RealType>(1.04851094362145160445e-11),
+            static_cast<RealType>(-8.50646541795105885254e-18),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.59832721225510968607e-1),
+            static_cast<RealType>(2.75929030381330309762e-2),
+            static_cast<RealType>(1.53115657043391090526e-3),
+            static_cast<RealType>(4.70173086825204710446e-5),
+            static_cast<RealType>(7.76185172490852556883e-7),
+            static_cast<RealType>(6.10512879655564540102e-9),
+            static_cast<RealType>(1.64522607881748812093e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.2534e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(2.11253031965493064317e-2),
+            static_cast<RealType>(1.36656844320536022509e-3),
+            static_cast<RealType>(2.99036224749763963099e-5),
+            static_cast<RealType>(2.54538665523638998222e-7),
+            static_cast<RealType>(6.79286608893558228264e-10),
+            static_cast<RealType>(-6.92803349600061706079e-16),
+            static_cast<RealType>(5.47233092767314029032e-19),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.71506209641408410168e-2),
+            static_cast<RealType>(3.52744690483830496158e-3),
+            static_cast<RealType>(5.85142319429623560735e-5),
+            static_cast<RealType>(4.29686638196055795330e-7),
+            static_cast<RealType>(1.06586221304077993137e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(x) < 8) {
+        RealType t = log2(ldexp(x, -6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.8057e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(6.60754766433212615409e-1),
+            static_cast<RealType>(2.47190065739055522599e-1),
+            static_cast<RealType>(4.17560046901040308267e-2),
+            static_cast<RealType>(3.71520821873148657971e-3),
+            static_cast<RealType>(2.03659383008528656781e-4),
+            static_cast<RealType>(2.52070598577347523483e-6),
+            static_cast<RealType>(-1.63741595848354479992e-8),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.92836792184266080580e-1),
+            static_cast<RealType>(6.64332913820571574875e-2),
+            static_cast<RealType>(5.59456053716889879620e-3),
+            static_cast<RealType>(3.44201583106671507027e-4),
+            static_cast<RealType>(2.74554105716911980435e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 16) {
+        RealType t = log2(ldexp(x, -8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.5585e-18
+        static const RealType P[9] = {
+            static_cast<RealType>(6.44802371584831601817e-1),
+            static_cast<RealType>(2.74177359656349204309e-1),
+            static_cast<RealType>(5.53659240731871433983e-2),
+            static_cast<RealType>(6.97653365560511851744e-3),
+            static_cast<RealType>(6.17058143529799037402e-4),
+            static_cast<RealType>(3.94979574476108021136e-5),
+            static_cast<RealType>(1.88315864113369221822e-6),
+            static_cast<RealType>(6.10941845734962836501e-8),
+            static_cast<RealType>(1.39403332890347813312e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.32345127287830884682e-1),
+            static_cast<RealType>(8.70500634789942065799e-2),
+            static_cast<RealType>(1.09253956356393590470e-2),
+            static_cast<RealType>(9.72576825490118007977e-4),
+            static_cast<RealType>(6.18656322285414147985e-5),
+            static_cast<RealType>(2.96375876501823390564e-6),
+            static_cast<RealType>(9.58622809886777038970e-8),
+            static_cast<RealType>(2.19059124630695181004e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 32) {
+        RealType t = log2(ldexp(x, -16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.4773e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.36685748306554972132e-1),
+            static_cast<RealType>(2.22217783148381285219e-1),
+            static_cast<RealType>(3.79173960692559280353e-2),
+            static_cast<RealType>(4.13394722917837684942e-3),
+            static_cast<RealType>(3.18141233442663766089e-4),
+            static_cast<RealType>(1.79745613243740552736e-5),
+            static_cast<RealType>(7.47632665728046334131e-7),
+            static_cast<RealType>(2.18258684729250152138e-8),
+            static_cast<RealType>(3.93038365129320422968e-10),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.49087806008685701060e-1),
+            static_cast<RealType>(5.95568283529034601477e-2),
+            static_cast<RealType>(6.49386742119035055908e-3),
+            static_cast<RealType>(4.99721374204563274865e-4),
+            static_cast<RealType>(2.82348248031305043777e-5),
+            static_cast<RealType>(1.17436903872210815656e-6),
+            static_cast<RealType>(3.42841159307801319359e-8),
+            static_cast<RealType>(6.17382517100568714012e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 64) {
+        RealType t = log2(ldexp(x, -32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.1441e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.36619774420718062663e-1),
+            static_cast<RealType>(2.68594096777677177874e-1),
+            static_cast<RealType>(5.50713044649497737064e-2),
+            static_cast<RealType>(7.26574134143434960446e-3),
+            static_cast<RealType>(6.89173530168387629057e-4),
+            static_cast<RealType>(4.87688310559244353811e-5),
+            static_cast<RealType>(2.84218580121660744969e-6),
+            static_cast<RealType>(9.65240367429172366675e-8),
+            static_cast<RealType>(5.21722720068664704240e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.21906621389193043384e-1),
+            static_cast<RealType>(8.65058026826346828750e-2),
+            static_cast<RealType>(1.14129998157398060009e-2),
+            static_cast<RealType>(1.08255124950652385121e-3),
+            static_cast<RealType>(7.66059006900869004871e-5),
+            static_cast<RealType>(4.46449501653114622960e-6),
+            static_cast<RealType>(1.51619602364037777665e-7),
+            static_cast<RealType>(8.19520132288940649002e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else {
+        result = 2 / (constants::pi<RealType>() * x);
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x < 1) {
+        // Rational Approximation
+        // Maximum Relative Error: 2.6472e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34761298487625202628055609797763667089e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67589195401255255724121983550745957195e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07502511824371206858547365520593277966e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58354381655514028012912292026393699991e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.26470588572701739953294573496059174764e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09494168186680012705692462031819276746e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.47385718073281027400744626077865581325e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69107567947502492044754464589464306928e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39641345689672620514703813504927833352e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27003930699448633502508661352994055898e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26124673422692247711088651516214728305e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92103390710025598612731036700549416611e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.49572523814120679048097861755172556652e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.50719933268462244255954307285373705456e-13),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05332427324361912631483249892199461926e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46280417679002004953145547112352398783e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10429833573651169023447466152999802738e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63535585818618617796313647799029559407e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24103322502244219003850826414302390557e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.38359438431541204276767900393091886363e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16687583686405832820912406970664239423e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31451667102532056871497958974899742424e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31646175307279119467894327494418625431e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22334681489114534492425036698050444462e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86326948577818727263376488455223120476e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53867591038308710930446815360572461884e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
+    }
+    else if (x < 2) {
+        RealType t = x - 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2387e-36
+        static const RealType P[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22133240358047652363270514524313049653e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35860518549481281929441026718420080571e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89900189271177970319691370395978805326e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84682995288088652145572170736339265315e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.10748045562955323875797887939420022326e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00246325517647746481631710824413702051e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02998394686245118431020407235000441722e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06095284318730009040434594746639110387e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.91754425158654496372516241124447726889e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.37288564874584819097890713305968351561e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77487285800889132325390488044487626942e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41654614425073025870130302460301244273e-13),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13058739144695658589427075788960660400e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11792528400843967390452475642793635419e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28794756779085737559146475126886069030e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29339015472607099189295465796550367819e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53434372685847620864540166752049026834e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17610372643685730837081191600424913542e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64455304425865128680681864919048610730e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62357689170951502920019033576939977973e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.89912258835489782923345357128779660633e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76323449710934127736624596886862488066e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21524231900555452527639738371019517044e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 4) {
+        RealType t = x - 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2281e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95892137955791216377776422765473500279e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65957634570689820998348206103212047458e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34657686985192350529330481818991619730e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43985500841002490334046057189458709493e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09876223028004323158413173719329449720e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.04194660038290410425299531094974709019e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09780604136364125990393172827373829860e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02676079027875648517286351062161581740e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30298199082321832830328345832636435982e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33633965123855006982811143987691483957e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46384114966020719170903077536685621119e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07058773850795175564735754911699285828e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.76765053309825506619419451346428518606e-16),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89758965744489334954041814073547951925e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65985298582650601001220682594742473012e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.81017086203232617734714711306180675445e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14481301672800918591822984940714490526e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.90605450026850685321372623938646722657e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42447999818015246265718131846902731574e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83426770079526980292392341278413549820e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65073357441521690641768959521412898756e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.90437453546925074707222505750595530773e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63458145595422196447107547750737429872e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.94457070577990681786301801930765271001e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80986568964737305842778359322566801845e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 8) {
+        RealType t = x - 4;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.3269e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73159318667565938775602634998889798568e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95149372103869634275319490207451722385e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.87504411659823400690797222216564651939e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94571385159717824767058200278511014560e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.71656210265434934399632978675652106638e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.51248899957476233641240573020681464290e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.74490600490886011190565727721143414249e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07537323853509621126318424069471060527e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59167561354023258538869598891502822922e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72608361427131857269675430568328018022e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.54143016370650707528704927655983490119e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07936446902207128577031566135957311260e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.73506415766100115673754920344659223382e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66918494546396383814682000746818494148e-21),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34854858486201481385140426291984169791e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.25379978655428608198799717171321453517e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.01905621587554903438286661709763596137e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31293339647901753103699339801273898688e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22793491714510746538048140924864505813e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45360205736839126407568005196865547577e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20918479556021574336548106785887700883e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.91450617548036413606169102407934734864e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59940586452863361281618661053014404930e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.93918243796178165623395356401173295690e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.14578198844767847381800490360878776998e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.25951924258762195043744665124187621023e-13),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 16) {
+        RealType t = x - 8;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8719e-36
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.90469147411748292410422813492550092930e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20196598836093298098360769875443462143e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92579652651763461802771336515384878994e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.50439147419887323351995227585244144060e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13214742069751393867851080954754449610e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29648648382394801501422003194522139519e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80420399625810952886117129805960917210e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.73059844436212109742132138573157222143e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66835461298243901306176013397428732836e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61808423521250921041207160217989047728e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39300098366988229510997966682317724011e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09447823064238788960158765421669935819e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76962456941948786610101052244821659252e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56004343709960620209823076030906442732e-25),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.22996422556023111037354479836605618488e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05244279198013248402385148537421114680e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72477335169177427114629223821992187549e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76404568980852320252614006021707040788e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.79959793426748071158513573279263946303e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.93524788220877416643145672816678561612e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.46692111397574773931528693806744007042e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20764040991846422990601664181377937629e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84452460717254884659858711994943474216e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30317379590981344496250492107505244036e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83736710938966780518785861828424593249e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72943283576264035508862984899450025895e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77791087299927741360821362607419036797e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 32) {
+        RealType t = x - 16;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.3269e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35157264931262089761621934621402648954e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51407493866635569361305338029611888082e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30886132894858313459359493329266696766e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02488735053241778868198537544867092626e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12676055870976203566712705442945186614e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.14136757304740001515364737551021389293e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01514327671186735593984375829685709678e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63783530594707477852365258482782354261e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67623013776194044717097141295482922572e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01397549144502050693284434189497148608e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.16720246008161901837639496002941412533e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70776057051329137176494230292143483874e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02838174509144355795908173352005717435e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07343581702278433243268463675468320030e-30),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13166129191902183515154099741529804400e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.58587877615076239769720197025023333190e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.14619910799508944167306046977187889556e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66671218029939293563302720748492945618e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67192565058098643223751044962155343554e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68397391192695060767615969382391508636e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94009678375859797198831431154760916459e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91901267471125881702216121486397689200e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83697721782125852878533856266722593909e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65409094893730117412328297801448869154e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.04202174160401885595563150562438901685e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82104711207466136473754349696286794448e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x < 64) {
+        RealType t = x - 32;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0937e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11253031965493064317003259449214452745e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66886306590939856622089350675801752704e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77786526684921036345823450504680078696e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20343424607276252128027697088363135591e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29196073776799916444272401212341853981e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.92132293422644089278551376756604946339e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07465707745270914645735055945940815947e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54424785613626844024154493717770471131e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74829439628215654062512023453584521531e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.03470347880592072854295353687395319489e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21113051919776165865529140783521696702e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.83719812218384126931626509884648891889e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.41009036423458926116066353864843586169e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04965807080681693416200699806159303323e-34),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06133417626680943824361625182288165823e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87991711814130682492211639336942588926e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98342969282034680444232201546039059255e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41940454945139684365514171982891170420e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.90481418770909949109210069475433304086e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25451856391453896652473393039014954572e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36349120987010174609224867075354225138e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94716367816033715208164909918572061643e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67466470065187852967064897686894407151e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31509787633232139845762764472649607555e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93147765040455324545205202900563337981e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07370974123835247210519262324524537634e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(x) < 8) {
+        RealType t = log2(ldexp(x, -6));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.1671e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60754766433212615408805486898847664740e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.76143516602438873568296501921670869526e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.25254763859315398784817302471631188095e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.58650277225655302085863010927524053686e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92227773746592457803942136197158658110e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77170481512334811333255898903061802339e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.97864282716826576471164657368231427231e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.44243747123065035356982629201975914275e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54592817957461998135980337838429682406e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.52110831321633404722419425039513444319e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75030698219998735693228347424295850790e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.08894662488905377548940479566994482806e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11472306961184868827300852021969296872e-12),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04202386226609593823214781180612848612e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07648212684952405730772649955008739292e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50646784687432427178774105515508540021e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02521400964223268224629095722841793118e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35374201758795213489427690294679848997e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67290684433876221744005507243460683585e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83834977086311601362115427826807705185e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43236252790815493406777552261402865674e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17693398496807851224497995174884274919e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34161978291568722756523120609497435933e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10819003833429876218381886615930538464e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75674945131892236663189757353419870796e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 16) {
+        RealType t = log2(ldexp(x, -8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.8517e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44802371584831601817146389426921705500e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.32962058761590152378007743852342151897e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93461601407042255925193793376118641680e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.55533612685775705468614711945893908392e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76358919439168503100357154639460097607e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74131615534562303144125602950691629908e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34470363614899824502654995633001232079e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29020592733459891982428815398092077306e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65794017754267756566941255128608603072e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78550878208007836345763926019855723350e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00524022519953193863682806155339574713e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75977976583947697667784048133959750133e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89287460618943500291479647438555099783e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27647727947590174240069836749437647626e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70582660582766959108625375415057711766e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.68499175244574169768386088971844067765e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84493774639724473576782806157757824413e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03526708437207438952843827018631758857e-20),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.88770963972332750838571146142568699263e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60273143287476497658795203149608758815e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34393017137025732376113353720493995469e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77086140458900002000076127880391602253e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30613589576665986239534705717153313682e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25355055770024448240128702278455001334e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.16820392686312531160900884133254461634e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.17518073757769640772428097588524967431e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80469112215756035261419102003591533407e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57898123952200478396366475124854317231e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47675840885248141425130440389244781221e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.97339213584115778189141444065113447170e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.85845602624148484344802432304264064957e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67971825826765902713812866354682255811e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.78795543918651402032912195982033010270e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18166403020940538730241286150437447698e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47995312365747437038996228794650773820e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 32) {
+        RealType t = log2(ldexp(x, -16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.5315e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36685748306554972131586673701426039950e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75892450098649456865500477195142009984e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.77167300709199375935767980419262418694e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76657987434662206916119089733639111866e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55003354250569146980730594644539195376e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.64102805555049236216024194001407792885e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36247488122195469059567496833809879653e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63710218182036673197103906176200862606e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60629446465979003842091012679929186607e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22712292003775206105713577811447961965e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.28539646473359376707298867613704501434e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47893806904387088760579412952474847897e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86809622035928392542821045232270554753e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47935154807866802001012566914901169147e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.40623855123515207599160827187101517978e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60738876249485914019826585865464103800e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29257874466803586327275841282905821499e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.06781616867813418930916928811492801723e-31),
+        };
+        static const RealType Q[17] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.33391038950576592915531240096703257292e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06598147816889621749840662500099582486e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21997213397347849640608088189055469954e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18596259982438670449688554459343971428e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86085649929528605647139297483281849158e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28178198640304770056854166079598253406e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.57155234493390297220982397633114062827e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03771216318243964850930846579433365529e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49837117625052865973189772546210716556e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.87302306206908338457432167186661027909e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32312467403555290915110093627622951484e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50516769529388616534895145258103120804e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.03618834064000582669276279973634033592e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.49205787058220657972891114812453768100e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23730041323226753771240724078738146658e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60115971929371066362271909482282503973e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 64) {
+        RealType t = log2(ldexp(x, -32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0538e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619774420718062663274858007687066488e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30268560944740805268408378762250557522e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09208091036436297425427953080968023835e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.74943166696408995577495065480328455423e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.03759498310898586326086395411203400316e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67261192787197720215143001944093963953e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42934578939412238889174695091726883834e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.32436794923711934610724023467723195718e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35077626369701051583611707128788137675e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40836846523442062397035620402082560833e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98783806012035285862106614557391807137e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53869567415427145730376778932236900838e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.76521311340629419738016523643187305675e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41298928566351198899106243930173421965e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85552706372195482059144049293491755419e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89780987301820615664133438159710338126e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37965575161090804572561349091024723962e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58944184323201470938493323680744408698e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35050162268451658064792430214910233545e-40),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61705010674524952791495931314010679992e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42782564900556152436041716057503104160e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.46038982970912591009739894441944631471e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34223936001873800295785537132905986678e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19812900355867749521882613003222797586e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24521111398180921205229795007228494287e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.93429394949368809594897465724934596442e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.69259071867341718986156650672535675726e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16370379759046264903196063336023488714e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.12248872253003553623419554868303473929e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12936649424676303532477421399492615666e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37683645610869385656713212194971883914e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21951837982136344238516771475869548147e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91465509588513270823718962232280739302e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98107277753797219142748868489983891831e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.16715818685246698314459625236675887448e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.77987471623502330881961633434056523159e-26),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else if (ilogb(x) < 128) {
+        RealType t = log2(ldexp(x, -64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.2309e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344040890134127619524371e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72522424358877592972375801826826390634e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74749058021341871895402838175268752603e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.95136532385982168410320513292144834602e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10500792867575154180588502397506694341e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48101840822895419487033057691746982216e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22577211783918426674527460572438843266e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30499751609793470641331626931224574780e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07043764292750472900578756659402327450e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28345765853059515246787820662932506931e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48838700086419232178247558529254516870e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.51015062047870581993810118835353083110e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19087584836023628483830612541904830502e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74405125338538967114280887107628943111e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.34493122865874905104884954420903910585e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.33794243240353561095702650271950891264e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07931799710240978706633227327649731325e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60935135769719557933955672887720342220e-23),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28077223152164982690351137450174450926e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02813709168750724641877726632095676090e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24899754437233214579860634420198464016e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27313166830073839667108783881090842820e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01803599095361490387188839658640162684e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63782732057408167492988043000134055952e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.62068163155799642595981598061154626504e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68143951757351157612001096085234448512e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72843955600132743549395255544732133507e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33795283380674591910584657171640729449e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.08452802793967494363851669977089389376e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87062340827301546650149031133192913586e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31034562935470222182311379138749593572e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39579834094849668082821388907704276985e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46680056726416759571957577951115309094e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69538874529209016624246362786229032706e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52796320119313458991885552944744518437e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
+    }
+    else {
+        result = 2 / (constants::pi<RealType>() * x);
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.8279e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(9.61609610406317335842e-2),
+            static_cast<RealType>(3.91836314722738553695e-1),
+            static_cast<RealType>(6.79862925205625107133e-1),
+            static_cast<RealType>(6.52516594941817706368e-1),
+            static_cast<RealType>(3.78594163612581127974e-1),
+            static_cast<RealType>(1.37741592243008345389e-1),
+            static_cast<RealType>(3.16100502353317199197e-2),
+            static_cast<RealType>(3.94935603975622336575e-3),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.76863983252615276767e0),
+            static_cast<RealType>(1.81486018095087241378e0),
+            static_cast<RealType>(1.17295504548962999723e0),
+            static_cast<RealType>(5.33998066342362562313e-1),
+            static_cast<RealType>(1.66508320794082632235e-1),
+            static_cast<RealType>(3.42192028846565504290e-2),
+            static_cast<RealType>(3.94691613177524994796e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.3675e-17
+        static const RealType P[11] = {
+            static_cast<RealType>(7.07114056489178077423e-4),
+            static_cast<RealType>(7.35277969197058909845e-3),
+            static_cast<RealType>(3.45402694579204809691e-2),
+            static_cast<RealType>(9.62849773112695332289e-2),
+            static_cast<RealType>(1.75738736725818007992e-1),
+            static_cast<RealType>(2.18309266582058485951e-1),
+            static_cast<RealType>(1.85680388782727289455e-1),
+            static_cast<RealType>(1.06177394398691169291e-1),
+            static_cast<RealType>(3.94880388335722224211e-2),
+            static_cast<RealType>(9.46543177731050647162e-3),
+            static_cast<RealType>(1.50949646857411896396e-3),
+        };
+        static const RealType Q[11] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.19520021153535414164e0),
+            static_cast<RealType>(2.24057032777744601624e0),
+            static_cast<RealType>(1.63635577968560162720e0),
+            static_cast<RealType>(1.58952087228427876880e0),
+            static_cast<RealType>(7.63062254749311648018e-1),
+            static_cast<RealType>(4.65805990343825931327e-1),
+            static_cast<RealType>(1.45821531714775598887e-1),
+            static_cast<RealType>(5.42393925507104531351e-2),
+            static_cast<RealType>(9.84276292481407168381e-3),
+            static_cast<RealType>(1.54787649925009672534e-3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        const static RealType lambda_bias = static_cast<RealType>(1.45158270528945486473); // (= log(pi/2)+1)
+
+        RealType sigma = exp(-x * constants::pi<RealType>() / 2 - lambda_bias);
+        RealType s = exp(-sigma) / sqrt(sigma);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 6.6532e-17
+            static const RealType P[9] = {
+                static_cast<RealType>(3.71658823632747235572e-1),
+                static_cast<RealType>(2.81493346318174084721e-1),
+                static_cast<RealType>(1.80052521696460721846e-1),
+                static_cast<RealType>(7.65907659636944822120e-2),
+                static_cast<RealType>(2.33352148213280934280e-2),
+                static_cast<RealType>(5.02308701022480574067e-3),
+                static_cast<RealType>(6.29239919421134075502e-4),
+                static_cast<RealType>(8.36993181707604609065e-6),
+                static_cast<RealType>(-8.38295154747385945293e-6),
+            };
+            static const RealType Q[9] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(6.62107509936390708604e-1),
+                static_cast<RealType>(4.72501892305147483696e-1),
+                static_cast<RealType>(1.84446743813050604353e-1),
+                static_cast<RealType>(5.99971792581573339487e-2),
+                static_cast<RealType>(1.24751029844082800143e-2),
+                static_cast<RealType>(1.56705297654475773870e-3),
+                static_cast<RealType>(2.36392472352050487445e-5),
+                static_cast<RealType>(-2.11667044716450080820e-5),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -5.1328125) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 2.6331e-17
+            static const RealType P[10] = {
+                static_cast<RealType>(3.97500903816385095134e-1),
+                static_cast<RealType>(5.08559630146730380854e-1),
+                static_cast<RealType>(2.99190443368166803486e-1),
+                static_cast<RealType>(1.07339363365158174786e-1),
+                static_cast<RealType>(2.61694301269384158162e-2),
+                static_cast<RealType>(4.58386867966451237870e-3),
+                static_cast<RealType>(5.80610284231484509069e-4),
+                static_cast<RealType>(5.07249042503156949021e-5),
+                static_cast<RealType>(2.91644292826084281875e-6),
+                static_cast<RealType>(9.75453868235609527534e-12),
+            };
+            static const RealType Q[9] = {
+                static_cast<RealType>(1),
+                static_cast<RealType>(1.27376091725485414303e0),
+                static_cast<RealType>(7.49829208702328578188e-1),
+                static_cast<RealType>(2.69157374996960976399e-1),
+                static_cast<RealType>(6.55795320040378662663e-2),
+                static_cast<RealType>(1.14912646428788757804e-2),
+                static_cast<RealType>(1.45541420582309879973e-3),
+                static_cast<RealType>(1.27135040794481871472e-4),
+                static_cast<RealType>(7.31138551538712031061e-6),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (x >= -1) {
+        RealType t = x + 1;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.2055e-36
+        static const RealType P[16] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61609610406317335842332400044553397267e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74152295981095898203847178356629061821e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58642905042588731020840168744866124345e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69370085525311304330141932309908104187e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14888713497930800611167630826754270499e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69123861559106636252620023643265102867e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74273532954853421626852458737661546439e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.73534665976007761924923962996725209700e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42543389723715037640714282663089570985e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05120903211852044362181935724880384488e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49586169587615171270941258051088627885e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46047939521303565932576405363107506886e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68248726161641913236972878212857788320e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60663638253775180681171554635861859625e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76463460016745893121574217030494989443e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.08380585744336744543979680558024295296e-12),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66458574743150749245922924142120646408e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87010262350733534202724862784081296105e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.51107149980251214963849267707173045433e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.71158207369578457239679595370389431171e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37188705505573668092513124472448362633e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95647530096628718695081507038921183627e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30278895428001081342301218278371140110e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61322060563420594659487640090297303892e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30529729106312748824241317854740876915e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90465740298431311519387111139787971960e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.92760416706194729215037805873466599319e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02070496615845146626690561655353212151e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72080705566714681586449384371609107346e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76433504120625478720883079263866245392e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (x >= -2) {
+        RealType t = x + 2;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.4133e-36
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07114056489178077422539043012078031613e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18006784954579394004360967455655021959e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.60309646092161147676756546417366564213e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13479499932401667065782086621368143322e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68587439643060549883916236839613331692e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12366494749830793876926914920462629077e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70739124754664545339208363069646589169e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04073482998938337661285862393345731336e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94833709787596305918524943438549684109e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50214412821697972546222929550410139790e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.43105005523280337071698704765973602884e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85396789833278250392015217207198739243e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05690359993570736607428746439280858381e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.17297815188944531843360083791153470475e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.03913601629627587800587620822216769010e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61963034255210565218722882961703473760e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.99502258440875586452963094474829571000e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.66563884565518965562535171848480872267e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23954896921292896539048530795544784261e-6),
+        };
+        static const RealType Q[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77934931846682015134812629288297137499e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.85052416252910403272283619201501701345e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45276747409453182009917448097687214033e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87717215449690275562288513806049961791e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96583424263422661540930513525639950307e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73001838976297286477856104855182595364e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29209801725936746054703603946844929105e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.31809396176316042818100839595926947461e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62125101720695030847208519302530333864e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22912823173107974750307098204717046200e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28404310708078592866397210871397836013e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33433860799478110495440617696667578486e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01779942752411055394079990371203135494e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60870827161929649807734240735205100749e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43275518144078080917466090587075581039e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.80287554756375373913082969626543154342e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00697535360590561244468004025972321465e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23883308105457761862174623664449205327e-6),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        const static RealType lambda_bias = BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.451582705289454864726195229894882143572); // (= log(pi/2)+1)
+
+        RealType sigma = exp(-x * constants::pi<RealType>() / 2 - lambda_bias);
+        RealType s = exp(-sigma) / sqrt(sigma);
+
+        if (x >= -4) {
+            RealType t = -x - 2;
+
+            // Rational Approximation
+            // Maximum Relative Error: 9.2619e-35
+            static const RealType P[19] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71658823632747235572391863987803415545e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20402452680758356732340074285765302037e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53870483364594487885882489517365212394e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.73525449564340671962525942038149851804e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.67339872142847248852186397385576389802e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60644488744851390946293970736919678433e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33042051950636491987775324999025538357e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13846819893538329440033115143593487041e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41648498082970622389678372669789346515e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74006867625631068946791714035394785978e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.12238896415831258936563475509362795783e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88070293465108791701905953972140154151e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.24813015654516014181209691083399092303e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64092873079064926551281731026589848877e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.09892207654972883190432072151353819511e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.86990125202059013860642688739159455800e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62986611607135348214220687891374676368e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07567013469555215514702758084138467446e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84619752008414239602732630339626773669e-14),
+            };
+            static const RealType Q[17] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28669950018285475182750690468224641923e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12421557061005325313661189943328446480e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68376064122323574208976258468929505299e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22010354939562426718305463635398985290e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13795955314742199207524303721722785075e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90452274425830801819532524004271355513e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.38324283887272345859359008873739301544e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15232844484261129757743512155821350773e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.79562237779621711674853020864686436450e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64370777996591099856555782918006739330e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02327782881305686529414731684464770990e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27181015755595543140221119020333695667e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01121287947061613072815935956604529157e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44038164966032378909755215752715620878e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39138685106442954199109662617641745618e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.83317957765031605023198891326325990178e-10),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else if (x >= -6.875) {
+            RealType t = -x - 4;
+
+            // Rational Approximation
+            // Maximum Relative Error: 4.9208e-35
+            static const RealType P[20] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97500903816385095134217223320239082420e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02058997410109156148729828665298333233e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30492992901887465108077581566548743407e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08695332228530157560495896731847709498e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54469321766529692240388930552986490213e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00543201281990041935310905273146022998e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08633547932070289660163851972658637916e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15432691192536747268886307936712580254e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.46179071338871656505293487217938889935e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45295210106393905833273975344579255175e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34638105523514101671944454719592801562e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15786069528793080046638424661219527619e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.54781306296697568446848038567723598851e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31977279631544580423883461084970429143e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.56616743805004179430469197497030496870e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60913959062328670735884196858280987356e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91123354712008822789348244888916948822e-11),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82453513391091361890763400931018529659e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.12671859603774617133607658779709622453e-14),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03211544596001317143519388487481133891e-20),
+            };
+            static const RealType Q[19] = {
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.56188463983858614833914386500628633184e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27273165410457713017446497319550252691e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72495122287308474449946195751088057230e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64049710819255633163836824600620426349e0),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53329810455612298967902432399110414761e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72302144446588066369304547920758875106e-1),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.90680157119357595265085115978578965640e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87039785683949322939618337154059874729e-2),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64199530594973983893552925652598080310e-3),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88147828823178863054226159776600116931e-4),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91569503818223078110818909039307983575e-5),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.89289385694964650198403071737653842880e-6),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.32154679053642509246603754078168127853e-7),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43239674842248090516375370051832849701e-8),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.03349866320207008385913232167927124115e-9),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98307302768178927108235662166752511325e-10),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07996042577029996321821937863373306901e-12),
+                BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53576500935979732855511826033727522138e-13),
+            };
+
+            result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+        }
+        else {
+            result = 0;
+        }
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+    if (x >= 0) {
+        return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - landau_cdf_minus_imp_prec(x, tag) : landau_cdf_minus_imp_prec(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType>
+inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+    if (x >= 0) {
+        return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
+    }
+    else if (x <= 0) {
+        return complement ? 1 - landau_cdf_minus_imp_prec(x, tag) : landau_cdf_minus_imp_prec(x, tag);
+    }
+    else {
+        return std::numeric_limits<RealType>::quiet_NaN();
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType landau_cdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+    //
+    // This calculates the cdf of the Landau distribution and/or its complement.
+    //
+
+    BOOST_MATH_STD_USING // for ADL of std functions
+    static const char* function = "boost::math::cdf(landau<%1%>&, %1%)";
+    RealType result = 0;
+    RealType location = dist.location();
+    RealType scale = dist.scale();
+    RealType bias = dist.bias();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_x(function, x, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    RealType u = (x - location) / scale + bias;
+
+    result = landau_cdf_imp_prec(u, complement, tag_type());
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.375) {
+        RealType t = p - static_cast < RealType>(0.375);
+
+        // Rational Approximation
+        // Maximum Absolute Error: 3.0596e-17
+        static const RealType P[6] = {
+            static_cast<RealType>(3.74557416577759554506e-2),
+            static_cast<RealType>(3.87808262376545756299e0),
+            static_cast<RealType>(4.03092288183382979104e0),
+            static_cast<RealType>(-1.65221829710249468257e1),
+            static_cast<RealType>(-6.99689838230114367276e0),
+            static_cast<RealType>(1.51123479911771488314e1),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.37863773851525662884e-1),
+            static_cast<RealType>(-6.35020262707816744534e0),
+            static_cast<RealType>(3.07646508389502660442e-1),
+            static_cast<RealType>(9.72566583784248877260e0),
+            static_cast<RealType>(-2.72338088170674280735e0),
+            static_cast<RealType>(-1.58608957980133006476e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - static_cast < RealType>(0.25);
+
+        // Rational Approximation
+        // Maximum Absolute Error: 5.2780e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(-4.17764764050720190117e-1),
+            static_cast<RealType>(1.27887601021900963655e0),
+            static_cast<RealType>(1.80329928265996817279e1),
+            static_cast<RealType>(2.35783605878556791719e1),
+            static_cast<RealType>(-2.67160590411398800149e1),
+            static_cast<RealType>(-2.36192101013335692266e1),
+            static_cast<RealType>(8.30396110938939237358e0),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.37459525158081633669e0),
+            static_cast<RealType>(2.35696607501498012129e0),
+            static_cast<RealType>(-1.71117034150268575909e1),
+            static_cast<RealType>(-6.72278235529877170403e0),
+            static_cast<RealType>(1.27763043804603299034e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - static_cast < RealType>(0.125);
+
+        // Rational Approximation
+        // Maximum Absolute Error: 6.3254e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-8.77109518013577785811e-1),
+            static_cast<RealType>(-1.03442936529923615496e1),
+            static_cast<RealType>(-1.03389868296950570121e1),
+            static_cast<RealType>(2.01575691867458616553e2),
+            static_cast<RealType>(4.59115079925618829199e2),
+            static_cast<RealType>(-3.38676271744958577802e2),
+            static_cast<RealType>(-5.38213647878547918506e2),
+            static_cast<RealType>(1.99214574934960143349e2),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.64177607733998839003e1),
+            static_cast<RealType>(8.10042194014991761178e1),
+            static_cast<RealType>(7.61952772645589839171e1),
+            static_cast<RealType>(-2.52698871224510918595e2),
+            static_cast<RealType>(-1.95365983250723202416e2),
+            static_cast<RealType>(2.61928845964255538379e2),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.5192e-18
+        static const RealType P[6] = {
+            static_cast<RealType>(-8.77109518013577852585e-1),
+            static_cast<RealType>(-1.08703720146608358678e0),
+            static_cast<RealType>(-4.34198537684719253325e-1),
+            static_cast<RealType>(-6.97264194535092564620e-2),
+            static_cast<RealType>(-4.20721933993302797971e-3),
+            static_cast<RealType>(-6.27420063107527426396e-5),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(8.38688797993971740640e-1),
+            static_cast<RealType>(2.47558526682310722526e-1),
+            static_cast<RealType>(3.03952783355954712472e-2),
+            static_cast<RealType>(1.39226078796010665644e-3),
+            static_cast<RealType>(1.43993679246435688244e-5),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.1196e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-1.16727296241754548410e0),
+            static_cast<RealType>(-1.12325365855062172009e0),
+            static_cast<RealType>(-3.96403456954867129566e-1),
+            static_cast<RealType>(-6.50024588048629862189e-2),
+            static_cast<RealType>(-5.08582387678609504048e-3),
+            static_cast<RealType>(-1.71657051345258316598e-4),
+            static_cast<RealType>(-1.81536405273085024830e-6),
+            static_cast<RealType>(-9.65262938333207656548e-10),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.55271574611337871389e-1),
+            static_cast<RealType>(2.16323131117540100488e-1),
+            static_cast<RealType>(2.92693206540519768049e-2),
+            static_cast<RealType>(1.89396907936678571916e-3),
+            static_cast<RealType>(5.20017914327360594265e-5),
+            static_cast<RealType>(4.18896774212993675707e-7),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0763e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(-1.78348038398799868409e0),
+            static_cast<RealType>(-7.74779087785346936524e-1),
+            static_cast<RealType>(-1.27121601027522656374e-1),
+            static_cast<RealType>(-9.86675785835385622362e-3),
+            static_cast<RealType>(-3.69510132425310943600e-4),
+            static_cast<RealType>(-6.00811940375633438805e-6),
+            static_cast<RealType>(-3.06397799506512676163e-8),
+            static_cast<RealType>(-7.34821360521886161256e-12),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.76606062137668223823e-1),
+            static_cast<RealType>(5.37821995022686641494e-2),
+            static_cast<RealType>(3.62736078766811383733e-3),
+            static_cast<RealType>(1.16954398984720362997e-4),
+            static_cast<RealType>(1.59917906784160311385e-6),
+            static_cast<RealType>(6.41144889614705503307e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.9936e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-2.32474749499506229415e0),
+            static_cast<RealType>(-4.81681429397597263092e-1),
+            static_cast<RealType>(-3.79696253130015182335e-2),
+            static_cast<RealType>(-1.42328672650093755545e-3),
+            static_cast<RealType>(-2.58335052925986849305e-5),
+            static_cast<RealType>(-2.03945574260603170161e-7),
+            static_cast<RealType>(-5.04229972664978604816e-10),
+            static_cast<RealType>(-5.49506755992282162712e-14),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.87186049570056737301e-1),
+            static_cast<RealType>(1.32852903862611979806e-2),
+            static_cast<RealType>(4.45262195863310928309e-4),
+            static_cast<RealType>(7.13306978839226580931e-6),
+            static_cast<RealType>(4.84555343060572391776e-8),
+            static_cast<RealType>(9.65086092007764297450e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 9.2449e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-2.82318656228158372998e0),
+            static_cast<RealType>(-2.84346379198027589453e-1),
+            static_cast<RealType>(-1.09194719815749710073e-2),
+            static_cast<RealType>(-1.99728160102967185378e-4),
+            static_cast<RealType>(-1.77069359938827653381e-6),
+            static_cast<RealType>(-6.82828539186572955883e-9),
+            static_cast<RealType>(-8.22634582905944543176e-12),
+            static_cast<RealType>(-4.10585514777842307175e-16),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.29910333991046040738e-2),
+            static_cast<RealType>(3.27860300729204691815e-3),
+            static_cast<RealType>(5.45852206475929614010e-5),
+            static_cast<RealType>(4.34395271645812189497e-7),
+            static_cast<RealType>(1.46600782366946777467e-9),
+            static_cast<RealType>(1.45083131237841500574e-12),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.6453e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-3.29700011190686231229e0),
+            static_cast<RealType>(-1.62920309130909343601e-1),
+            static_cast<RealType>(-3.07152472866757852259e-3),
+            static_cast<RealType>(-2.75922040607620211449e-5),
+            static_cast<RealType>(-1.20144242264703283024e-7),
+            static_cast<RealType>(-2.27410079849018964454e-10),
+            static_cast<RealType>(-1.34109445298156050256e-13),
+            static_cast<RealType>(-3.08843378675512185582e-18),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.62324092774919223927e-2),
+            static_cast<RealType>(8.10410923007867515072e-4),
+            static_cast<RealType>(6.70843016241177926470e-6),
+            static_cast<RealType>(2.65459014339231700938e-8),
+            static_cast<RealType>(4.45531791525831169724e-11),
+            static_cast<RealType>(2.19324401673412172456e-14),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -256) {
+        RealType t = -log2(ldexp(p, 128));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.2028e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-3.75666995985336008568e0),
+            static_cast<RealType>(-9.15751436135409108392e-2),
+            static_cast<RealType>(-8.51745858385908954959e-4),
+            static_cast<RealType>(-3.77453552696508401182e-6),
+            static_cast<RealType>(-8.10504146884381804474e-9),
+            static_cast<RealType>(-7.55871397276946580837e-12),
+            static_cast<RealType>(-2.19023097542770265117e-15),
+            static_cast<RealType>(-2.34270094396556916060e-20),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.30119177073875808729e-2),
+            static_cast<RealType>(2.00787377759037971795e-4),
+            static_cast<RealType>(8.27382543511838001513e-7),
+            static_cast<RealType>(1.62997898759733931959e-9),
+            static_cast<RealType>(1.36215810410261098317e-12),
+            static_cast<RealType>(3.33957268115953023683e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -512) {
+        RealType t = -log2(ldexp(p, 256));
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.8900e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-4.20826069989721597050e0),
+            static_cast<RealType>(-5.07864788729928381957e-2),
+            static_cast<RealType>(-2.33825872475869133650e-4),
+            static_cast<RealType>(-5.12795917403072758309e-7),
+            static_cast<RealType>(-5.44657955194364350768e-10),
+            static_cast<RealType>(-2.51001805474510910538e-13),
+            static_cast<RealType>(-3.58448226638949307172e-17),
+            static_cast<RealType>(-1.79092368272097571876e-22),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(1.14671758705641048135e-2),
+            static_cast<RealType>(4.98614103841229871806e-5),
+            static_cast<RealType>(1.02397186002860292625e-7),
+            static_cast<RealType>(1.00544286633906421384e-10),
+            static_cast<RealType>(4.18843275058038084849e-14),
+            static_cast<RealType>(5.11960642868907665857e-18),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -1024) {
+        RealType t = -log2(ldexp(p, 512));
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.6777e-18
+        static const RealType P[8] = {
+            static_cast<RealType>(-4.65527239540648658214e0),
+            static_cast<RealType>(-2.78834161568280967534e-2),
+            static_cast<RealType>(-6.37014695368461940922e-5),
+            static_cast<RealType>(-6.92971221299243529202e-8),
+            static_cast<RealType>(-3.64900562915285147191e-11),
+            static_cast<RealType>(-8.32868843440595945586e-15),
+            static_cast<RealType>(-5.87602374631705229119e-19),
+            static_cast<RealType>(-1.37812578498484605190e-24),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(5.72000087046224585566e-3),
+            static_cast<RealType>(1.24068329655043560901e-5),
+            static_cast<RealType>(1.27105410419102416943e-8),
+            static_cast<RealType>(6.22649556008196699310e-12),
+            static_cast<RealType>(1.29416254332222127404e-15),
+            static_cast<RealType>(7.89365027125866583275e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else{
+        result = -std::numeric_limits<RealType>::infinity();
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.375) {
+        RealType t = p - 0.375;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 2.5723e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74557416577759248536854968412794870581e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.04379368253541440583870397314012269006e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12622841210720956864564105821904588447e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.57744422491408570970393103737579322242e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.13509711945094517370264490591904074504e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.18322789179144512109337184576079775889e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21447613719864832622177316196592738866e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49076304733407444404640803736504398642e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.96654951892056950374719952752959986017e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73083458872938872583408218098970368331e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.22584946471889320670122404162385347867e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98534922151507267157370682137856253991e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.09159286510191893522643172277831735606e0),
+        };
+        static const RealType Q[12] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.86204686129323171601167115178777357431e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.43698274248278918649234376575855135232e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.75240332521434608696943994815649748669e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.31438891446345558658756610288653829009e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10716029191240549289948990305434475528e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10878330779477313404660683539265890549e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.52360069933886703736010179403700697679e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.15864312939821257811853678185928982258e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.10341116017481903631605786613604619909e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29121822170912306719250697890270750964e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56489746112937744052098794310386515793e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 6.1583e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.17764764050720242897742634974454113395e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.80044093802431965072543552425830082205e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23613318632011593171919848575560968064e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77438013844838858458786448973516177604e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.62569530523012138862025718052954558264e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02005706260864894793795986187582916504e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29383609355165614630538852833671831839e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.09367754001841471839736367284852087164e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45744413840415901080013900562654222567e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41920296534143581978760545125050148256e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.94857580745127596732818606388347624241e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02847586753967876900858299686189155164e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.29953583375818707785500963989580066735e1),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27455303165341271216882778791555788609e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41762124591820618604790027888328605963e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30845760165840203715852751405553821601e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.00827370048057599908445731563638383351e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.19621193929561206904250173267823637982e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10514757798726932158537558200005910184e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.79738493761540403010052092523396617472e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.94101664430520833603032182296078344870e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.31586575577250608890806988616823861649e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93650751613703379272667745729529916084e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.52472388998113562780767055981852228229e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.01428305018551686265238906201345171425e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Absolute Error: 1.3135e-35
+        static const RealType P[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160121458e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.05813204052660740589813216397258899528e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.19628607167020425528944673039894592264e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.67162644860799051148361885190022738759e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.05921446080443979618622123764941760355e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.26685085062411656483492973256809500654e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17117538916032273474332064444853786788e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.45059470468014721314631799845029715639e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28952226224720891553119529857430570919e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.98502296814963504284919407719496390478e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.10876326351879104392865586365509749012e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.70358021544406445036220918341411271912e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49724346845064961378591039928633169443e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23815021378788622035604969476085727123e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.17262073948257994617723369387261569086e4),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.94901665980514882602824575757494472790e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54328910175180674300123471690771017388e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84847502738788846487698327848593567941e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98451502799612368808473649408471338893e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.13744760159877712051088928513298431905e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.20745061658519699732567732006176366700e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68622317228909264645937229979147883985e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.96020751551679746882793283955926871655e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.88860541272346724142574740580038834720e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73454107207588310809238143625482857512e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.23165643368613191971938741926948857263e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94832163019509140191456686231012184524e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.26616234097287315007047356261933409072e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24686019847093806280148917466062407447e4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.0498e-35
+        static const RealType P[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160155093e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.77585398076895266354686007069850894777e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47522378123968853907102309276280187353e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.63343576432650242131602396758195296288e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.77801189859227220359806456829683498508e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93221663334563259732178473649683953515e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.95272757466323942599253855146019408376e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73624853556509653351605530630788087166e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.41317699770351712612969089634227647374e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.34187895701093934279414993393750297714e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.64090928155753225614302094820737249510e-10),
+        };
+        static const RealType Q[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62401464973350962823995096121206419019e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11979822811128264831341485706314465894e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27257342406829987209876262928379300361e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.85505879705365729768944032174855501091e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40983451000610516082352700421098499905e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23459897865681009685618192649929504121e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.28925214684463186484928824536992032740e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67647262682850294124662856194944728023e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88173142080572819772032615169461689904e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07756799117728455728056041053803769069e-11),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.7643e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16727296241754547290632950718657117630e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97822895738734630842909028778257589627e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45580723831325060656664869189975355503e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.13835678647158936819843386298690513648e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.64536831064884519168892017327822018961e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93786616484143556451247457584976578832e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.55770899078184683328915310751857391073e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.91778173446401005072425460365992356304e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.59064619930808759325013814591048817325e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.54786673836080683521554567617693797315e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.15917340396537949894051711038346411232e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29633344043292285568750868731529586549e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.27785620133198676852587951604694784533e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.89999814745618370028655821500875451178e-16),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48772690114094395052120751771215809418e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.72281013057830222881716429522080327421e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.67186370229687087768391373818683340542e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86988148601521223503040043124617333773e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43321724586909919175166704060749343677e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57428821868404424742036582321713763151e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17165774858274087452172407067668213010e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.78674439389954997342198692571336875222e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82045374895858670592647375231115294575e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40152058277291349447734231472872126483e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34789603687129472952627586273206671442e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38087376350052845654180435966624948994e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34945081364333330292720602508979680233e-16),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.4987e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78348038398799867332294266481364810762e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42913983922316889357725662957488617770e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.02077376277824482097703213549730657663e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.01799479940825547859103232846394236067e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.31954083060883245879038709103320778401e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.14437110578260816704498035546280169833e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.75434713435598124790021625988306358726e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.70722283097111675839403787383067403199e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.22792548204908895458622068271940298849e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23652632092726261134927067083229843867e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.26848751206698811476021875382152874517e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.96683933776920842966962054618493551480e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.65547426464916480144982028081303670013e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.01788104318587272115031165074724363239e-19),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.43507070588695242714872431565299762416e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42808541175677232789532731946043918868e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58154336417481327293949514291626832622e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.52883128062761272825364005132296437324e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46220303655089035098911370014929809787e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.44776253795594076489612438705019750179e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.09607872267766585503592561222987444825e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24270418154050297788150584301311027023e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52138350835458198482199500102799185922e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28330565098807415367837423320898722351e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61220858078610415609826514581165467762e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31680570822471881148008283775281806658e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61638868324981393463928986484698110415e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.4643e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.32474749499506228416012679106564727824e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.11125026189437033131539969177846635890e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56906722402983201196890012041528422765e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56242546565817333757522889497509484980e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.96189353402888611791301502740835972176e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.25518459970705638772495930203869523701e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23831474024265607073689937590604367113e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.44925744847701733694636991148083680863e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.22891322042392818013643347840386719351e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.72860750698838897533843164259437533533e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.38276123679972197567738586890856461530e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.75010927807240165715236750369730131837e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.39435252454410259267870094713230289131e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32672767938414655620839066142834241506e-23),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71913035066927544877255131988977106466e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07499674325721771035402891723823952963e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.73304002376509252638426379643927595435e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45986195188119302051678426047947808068e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39631771214004792103186529415117786213e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82972151546053891838685817022915476363e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.11484161875982352879422494936862579004e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.76886416872139526041488219568768973343e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88160764330501845206576873052377420740e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20653899535657202009579871085255085820e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.86752135706343102514753706859178940399e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08670633989984379551412930443791478495e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96869107941293302786688580824755244599e-24),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.2783e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.82318656228158372073367735499501003484e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.46261040951642110189344545942990712460e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.64741560190892266676648641695426188913e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.28753551974093682831398870653055328683e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.21312013770915263838500863217194379134e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.52436958859473873340733176333088176566e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.19550238139736009251193868269757013675e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.14964971787780037500173882363122301527e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.40304301938210548254468386306034204388e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.86982233973109416660769999752508002999e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47229710624085810190563630948355644978e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97511060097659395674010001155696382091e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.14321784268659603072523892366718901165e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.69804409248161357472540739283978368871e-27),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85763741109198600677877934140774914793e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51555423561034635648725665049090572375e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.14334282485948451530639961260946534734e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15303265564789411158928907568898290494e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.33945229806307308687045028827126348382e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.94373901322371782367428404051188999662e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.51420073260465851038482922686870398511e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.39366317896256472225488167609473929757e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32986474655329330922243678847674164814e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09408217872473269288530036223761068322e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.79051953285476930547217173280519421410e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94530899348454778842122895096072361105e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36452993460830805591166007621343447892e-28),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.0123e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.29700011190686230364493911161520668302e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.16175031776740080906111179721128106011e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33343982195432985864570319341790342784e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25414682801788504282484273374052405406e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.08812659343240279665150323243172015853e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.33251452861660571881208437468957953698e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.80894766863868081020089830941243893253e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84955155823472122347227298177346716657e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.98637322645260158088125181176106901234e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.24174383760514163336627039277792172744e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.54369979866464292009398761404242103210e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02572051048819721089874338860693952304e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93656169061287808919601714139458074543e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.14930159772574816086864316805656403181e-31),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27154900915819978649344191118112870943e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77527908332591966425460814882436207182e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88097249712649070373643439940164263005e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33593973311650359460519742789132084170e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34383186845963127931313004467487408932e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18631088001587612168708294926967112654e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25338215226314856456799568077385137286e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30644713290591280849926388043887647219e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55508263112797212356530850090635211577e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96694528841324480583957017533192805939e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.81411886190142822899424539396403206677e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64683991040772975824276994623053932566e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81924597500766743545654858597960153152e-32),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -256) {
+        RealType t = -log2(ldexp(p, 128));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.7624e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.75666995985336007747791649448887723610e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78960399079208663111712385988217075907e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.74942252057371678208959612011771010491e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.54567765510065203543937772001248399869e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.53093894540157655856029322335609764674e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.83833601054721321664219768559444646069e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.52281007055180941965172296953524749452e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.57322728543196345563534040700366511864e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.52881564741260266060082523971278782893e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.60440334652864372786302383583725866608e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.60691285483339296337794569661545125426e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.29567560587442907936295101146377006338e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.50976593324256906782731237116487284834e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.71308835356954147218854223581309967814e-35),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62732785401286024270119905692156750540e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.40382961238668912455720345718267045656e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10406445824749289380797744206585266357e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.28896702052362503156922190248503561966e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16141168910009886089186579048301366151e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41978644147717141591105056152782456952e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28101353275172857831967521183323237520e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02996252940600644617348281599332256544e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91006255647885778937252519693385130907e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84585864559619959844425689120130028450e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68573963627097356380969264657086640713e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11059307697054035905630311480256015939e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36363494270701950295678466437393953964e-36),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -512) {
+        RealType t = -log2(ldexp(p, 256));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.5621e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.20826069989721596260510558511263035942e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.97440158261228371765435988840257904642e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.03971528248920108158059927256206438162e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.27123766722395421727031536104546382045e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.42341191105097202061646583288627536471e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.27644514375284202188806395834379509517e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.10772944192965679212172315655880689287e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32875098791800400229370712119075696952e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.06204614360238210805757647764525929969e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.43745006810807466452260414216858795476e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.66712970893511330059273629445122037896e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.72840198778128683137250377883245540424e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.91906782399731224228792112460580813901e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.42769091263044979075875010403899574987e-39),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31008507886426704374911618340654350029e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34370110384866123378972324145883460422e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37370811166006065198348108499624387519e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.14880753458828334658200185014547794333e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29049942195929206183214601044522500821e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19814793427532184357255406261941946071e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53609759199568827596069048758012402352e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94113467521833827559558236675876398395e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.46066673213431758610437384053309779874e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73781952388557106045597803110890418919e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.17225106466605017267996611448679124342e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66384334839761400228111118435077786644e-35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02877806111195383689496741738320318348e-40),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -1024) {
+        RealType t = -log2(ldexp(p, 512));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.4128e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.65527239540648657446629479052874029563e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.49609214609793557370425343404734771058e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85355312961840000203681352424632999367e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.57243631623079865238801420669247289633e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.64978384343879316016184643597712973486e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.12776782513387823319217102727637716531e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.86985041780323969283076332449881856202e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.11665149267826038417038582618446201377e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.44259259232002496618805591961855219612e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.13186466395317710362065595347401054176e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72627240737786709568584848420972570566e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.40450635670659803069555960816203368299e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.90550919589933206991152832258558972394e-38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.33785768143117121220383154455316199086e-43),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15365252334339030944695314405853064901e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84519641047962864523571386561993045416e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71097850431873211384168229175171958023e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20268329795802836663630276028274915013e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.00891848515558877833795613956071967566e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41031229424613259381704686657785733606e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96506914235910190020798805190634423572e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.51190756655665636680121123277286815188e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82855686000721415124702578998188630945e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64298533757673219241102013167519737553e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01176104624443909516274664414542493718e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.41571947895162847564926590304679876888e-39),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.84682590163505511580949151048092123923e-44),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -2048) {
+        RealType t = -log2(ldexp(p, 1024));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.3064e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.09971143249822249471944441552701756051e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.00154235169065403254826962372636417554e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.76859552294270710004718457715250134998e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16331901379268792872208226779641113312e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.11590258438815173520561213981966313758e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.17278804462968109983985217400233347654e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.14112976645884560534267524918610371127e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.34652102658577790471066054415469309178e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.85242987373551062800089607781071064493e-24),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.35051904844102317261572436130886083833e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78478298776769981726834169566536801689e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.22532973433435489030532261530565473605e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25433604872532935232490414753194993235e-41),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.49792182967344082832448065912949074241e-47),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.76316274347013095030195725596822418859e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45872499993438633169552184478587544165e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13309566903496793786045158442686362533e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99468690853840997883815075627545315449e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24734617022827960185483615293575601906e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30099852343633243897084627428924039959e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52598626985708878790452436052924637029e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91432956461466900007096548587800675801e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.54421383015859327468201269268335476713e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55939743284103455997584863292829252782e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.73331214275752923691778067125447148395e-38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55089353084326800338273098565932598679e-42),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.85408276119483460035366338145310798737e-48),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4096) {
+        RealType t = -log2(ldexp(p, 2048));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.2337e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.54271778755494231572464179212263718102e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62737121212473668543011440432166267791e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.10099492629239750693134803100262740506e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56925359477960645026399648793960646858e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.50756287005636861300081510456668184335e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.40657453971177017986596834420774251809e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.25518001919157628924245515302669097090e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.79618511101781942757791021761865762100e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.70242241511341924787722778791482800736e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.87078860748428154402226644449936091766e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84256560347986567120140826597805016470e-35),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.71419536977123330712095123316879755172e-40),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20746149769511232987820552765701234564e-45),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.97544543671003989410397788518265345930e-51),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87980995989632171985079518382705421728e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64234691529227024725728122489224211774e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66149363392892604040036997518509803848e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24365427902918684575287447585802611012e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.88619663977804926166359181945671853793e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.25299846770395565237726328268659386749e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18720305257346902130922082357712771134e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13302092710568005396855019882472656722e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88571994886818976015465466797965950164e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.48486836614948668196092864992423643733e-36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72247229252387482782783442901266890088e-41),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76046592638280288324495546006105696670e-46),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.09378739037162732758860377477607829024e-52),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -8192) {
+        RealType t = -log2(ldexp(p, 4096));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.1864e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.98493298246627952401490656857159302716e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.76990949843357898517869703626917264559e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.65042794324685841303461715489845834903e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.10605446678026983843303253925148000808e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.02762962429283889606329831562937730874e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.04105882385534634676234513866095562877e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.76001901462155366759952792570076976049e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.48255362964603267691139956218580946011e-25),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.19422119466925125740484046268759113569e-29),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.00719439924828639148906078835399693640e-33),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.89921842231783558951433534621837291030e-38),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90738353848476619269054038082927243972e-43),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.19893980415902021846066305054394089887e-49),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.85434486590981105149494168639321627061e-55),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43932168599456260558411716919165161381e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.09851997458503734167541584552305867433e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.32285843258966417340522520711168738158e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76041266755635729156773747720864677283e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21202253509959946958614664659473305613e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28647335562574024550800155417747339700e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.24953333571478743858014647649207040423e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41206199962423704137133875822618501173e-30),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34018702380092542910629787632780530080e-34),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41732943566503750356718429150708698018e-39),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29626943299239081309470153019011607254e-44),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.13947437500822384369637881437951570653e-50),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.61766557173110449434575883392084129710e-56),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -16384) {
+        RealType t = -log2(ldexp(p, 8192));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.1568e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.42671464308364892089984144203590292562e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.70165333325375920690660683988390032004e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.51230594210711745541592189387307516997e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.81387249912672866168782835177116953008e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.35308063526816559199325906123032162155e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.67672500455361049516022171111707553191e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45533142942305626136621399056034449775e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.37422341389432268402917477004312957781e-27),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32123176403616347106899307416474970831e-31),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.07816837508332884935917946618577512264e-36),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.95418937882563343895280651308376855123e-41),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.78256110112636303941842779721479313701e-47),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.09423327107440352766843873264503717048e-52),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12386630925835960782702757402676887380e-58),
+        };
+        static const RealType Q[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19477412398085422408065302795208098500e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27347517804649548179786994390985841531e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15042399607786347684366638940822746311e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.84537882580411074097888848210083177973e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.78283331111405789359863743531858801963e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00711555012725961640684514298170252743e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.21370151454170604715234671414141850094e-28),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72008007024350635082914256163415892454e-32),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.61182095564217124712889821368695320635e-37),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35498047010165964231841033788823033461e-42),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11828030216193307885831734256233140264e-47),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22499308298315468568520585583666049073e-53),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04877018522402283597555167651619229959e-59),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else {
+        result = -std::numeric_limits<RealType>::infinity();
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.375) {
+        RealType t = p - static_cast < RealType>(0.375);
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.1286e-20
+        static const RealType P[7] = {
+            static_cast<RealType>(1.31348919222343858178e0),
+            static_cast<RealType>(-1.06646675961352786791e0),
+            static_cast<RealType>(-1.80946160022120488884e1),
+            static_cast<RealType>(-1.53457017598330440033e0),
+            static_cast<RealType>(4.71260102173048370028e1),
+            static_cast<RealType>(4.61048467818771410732e0),
+            static_cast<RealType>(-2.80957284947853532418e1),
+        };
+        static const RealType Q[8] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.71007453129016317772e0),
+            static_cast<RealType>(1.31946404969596908872e0),
+            static_cast<RealType>(-1.70321827414586880227e1),
+            static_cast<RealType>(-1.11253495615474018666e1),
+            static_cast<RealType>(1.62659086449959446986e1),
+            static_cast<RealType>(7.37109203295032098763e0),
+            static_cast<RealType>(-2.43898047338699777337e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - static_cast < RealType>(0.25);
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.4934e-18
+        static const RealType P[7] = {
+            static_cast<RealType>(2.55081568282045924981e0),
+            static_cast<RealType>(5.38750533719526696218e0),
+            static_cast<RealType>(-2.32797421725187349036e1),
+            static_cast<RealType>(-3.96043566411306749784e1),
+            static_cast<RealType>(3.80609941977115436545e1),
+            static_cast<RealType>(3.35014421131920266346e1),
+            static_cast<RealType>(-1.17490458743273503838e1),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(7.52439409918350484765e0),
+            static_cast<RealType>(1.34784954182866689668e1),
+            static_cast<RealType>(-9.21002543625052363446e0),
+            static_cast<RealType>(-2.67378141317474265949e1),
+            static_cast<RealType>(2.10158795079902783094e0),
+            static_cast<RealType>(5.90098096212203282798e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - static_cast < RealType>(0.125);
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.0795e-17
+        static const RealType P[8] = {
+            static_cast<RealType>(5.68160868054034111703e0),
+            static_cast<RealType>(1.06098927525586705381e2),
+            static_cast<RealType>(5.74509518025029027944e2),
+            static_cast<RealType>(4.91117375866809056969e2),
+            static_cast<RealType>(-2.92607000654635606895e3),
+            static_cast<RealType>(-3.82912009541683403499e3),
+            static_cast<RealType>(2.49195208452006100935e3),
+            static_cast<RealType>(1.29413301335116683836e3),
+        };
+        static const RealType Q[7] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(2.69603865809599480308e1),
+            static_cast<RealType>(2.63378422475372461819e2),
+            static_cast<RealType>(1.09903493506098212946e3),
+            static_cast<RealType>(1.60315072092792425370e3),
+            static_cast<RealType>(-5.44710468198458322870e2),
+            static_cast<RealType>(-1.76410218726878681387e3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 4.4618e-17
+        static const RealType P[7] = {
+            static_cast<RealType>(7.10201085067542566037e-1),
+            static_cast<RealType>(6.70042401812679849451e-1),
+            static_cast<RealType>(2.42799404088685074098e-1),
+            static_cast<RealType>(4.80613880364042262227e-2),
+            static_cast<RealType>(6.04473313360581797461e-3),
+            static_cast<RealType>(5.09172911021654842046e-4),
+            static_cast<RealType>(-6.63145317984529265677e-6),
+        };
+        static const RealType Q[6] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(9.18649629646213969612e-1),
+            static_cast<RealType>(3.66343989541898286306e-1),
+            static_cast<RealType>(8.01010534748206001446e-2),
+            static_cast<RealType>(1.00553335007168823115e-2),
+            static_cast<RealType>(6.30966763237332075752e-4),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.8994e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(7.06147398566773538296e-1),
+            static_cast<RealType>(4.26802162741800814387e-1),
+            static_cast<RealType>(1.32254436707168800420e-1),
+            static_cast<RealType>(2.86055054496737936396e-2),
+            static_cast<RealType>(3.63373131686703931514e-3),
+            static_cast<RealType>(3.84438945816411937013e-4),
+            static_cast<RealType>(1.67768561420296743529e-5),
+            static_cast<RealType>(8.76982374043363061978e-7),
+            static_cast<RealType>(-1.99744396595921347207e-8),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(6.28190787856605587324e-1),
+            static_cast<RealType>(2.10992746593815791546e-1),
+            static_cast<RealType>(4.44397672327578790713e-2),
+            static_cast<RealType>(6.02768341661155914525e-3),
+            static_cast<RealType>(5.46578619531721658923e-4),
+            static_cast<RealType>(3.11116573895074296750e-5),
+            static_cast<RealType>(1.17729007979018602786e-6),
+            static_cast<RealType>(-2.78441865351376040812e-8),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.8685e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.48209596014908359251e-1),
+            static_cast<RealType>(2.52611824671691390768e-1),
+            static_cast<RealType>(4.65114070477803399291e-2),
+            static_cast<RealType>(5.23373513313686849909e-3),
+            static_cast<RealType>(3.83113384161076881958e-4),
+            static_cast<RealType>(1.96230077517629530809e-5),
+            static_cast<RealType>(5.83117485120890819338e-7),
+            static_cast<RealType>(6.92614450423703079737e-9),
+            static_cast<RealType>(-3.89531123166658723619e-10),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.99413988076189200840e-1),
+            static_cast<RealType>(7.32068638518417765776e-2),
+            static_cast<RealType>(8.15517102642752348889e-3),
+            static_cast<RealType>(6.09126071418098074914e-4),
+            static_cast<RealType>(3.03794079468789962611e-5),
+            static_cast<RealType>(9.32109079205017197662e-7),
+            static_cast<RealType>(1.05435710482490499583e-8),
+            static_cast<RealType>(-6.08748435983193979360e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.0253e-17
+        static const RealType P[10] = {
+            static_cast<RealType>(6.36719010559816164896e-1),
+            static_cast<RealType>(2.06504115804034148753e-1),
+            static_cast<RealType>(3.28085429275407182582e-2),
+            static_cast<RealType>(3.31676417519020335859e-3),
+            static_cast<RealType>(2.35502578757551086372e-4),
+            static_cast<RealType>(1.21652240566662139418e-5),
+            static_cast<RealType>(4.57039495420392748658e-7),
+            static_cast<RealType>(1.18090959236399583940e-8),
+            static_cast<RealType>(1.77492646969597480221e-10),
+            static_cast<RealType>(-2.19331267300885448673e-17),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(3.24422807416528490276e-1),
+            static_cast<RealType>(5.15290129833049138552e-2),
+            static_cast<RealType>(5.21051235888272287209e-3),
+            static_cast<RealType>(3.69895399249472399625e-4),
+            static_cast<RealType>(1.91103139437893226482e-5),
+            static_cast<RealType>(7.17882574725373091636e-7),
+            static_cast<RealType>(1.85502934977316481559e-8),
+            static_cast<RealType>(2.78798057565507249164e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.1705e-17
+        static const RealType P[9] = {
+            static_cast<RealType>(6.36619775525705206992e-1),
+            static_cast<RealType>(2.68335698140634792041e-1),
+            static_cast<RealType>(5.49803347535070103650e-2),
+            static_cast<RealType>(7.25018344556356907109e-3),
+            static_cast<RealType>(6.87753481255849254220e-4),
+            static_cast<RealType>(4.86155006277788340253e-5),
+            static_cast<RealType>(2.84604768310787862450e-6),
+            static_cast<RealType>(9.56133960810049319917e-8),
+            static_cast<RealType>(5.26850116571886385248e-9),
+        };
+        static const RealType Q[9] = {
+            static_cast<RealType>(1),
+            static_cast<RealType>(4.21500730173440590900e-1),
+            static_cast<RealType>(8.63629077498258325752e-2),
+            static_cast<RealType>(1.13885615328098640032e-2),
+            static_cast<RealType>(1.08032064178130906887e-3),
+            static_cast<RealType>(7.63650498196064792408e-5),
+            static_cast<RealType>(4.47056124637379045275e-6),
+            static_cast<RealType>(1.50189171357721423127e-7),
+            static_cast<RealType>(8.27574227882033707932e-9),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else {
+        result = 2 / (constants::pi<RealType>() * p);
+    }
+
+    return result;
+}
+
+
+template <class RealType>
+inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+{
+    BOOST_MATH_STD_USING
+    RealType result;
+
+    if (p >= 0.4375) {
+        RealType t = p - 0.4375;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.4465e-35
+        static const RealType P[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.08338732735341567163440035550389989556e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27245731792290848390848202647311435023e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29317169036386848462079766136373749420e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36342136825575317326816540539659955416e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31108700679715257074164180252148868348e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.81863611749256385875333154189074054367e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.11618233433781722149749739225688743102e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45241854625686954669050322459035410227e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09780430233523239228350030812868983054e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42232005306623465126477816911649683789e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.24816048952817367950452675590290535540e0),
+        };
+        static const RealType Q[10] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80464069267458650284548842830642770344e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.28240205449280944407125436342013240876e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94145088402407692372903806765594642452e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30062294376971843436236253827463203953e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.47118047660686070998671803800237836970e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.00643263133479482753298910520340235765e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.79460803824650509439313928266686172255e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32647058691746306769699006355256099134e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.59208938705683333141038012302171324544e0),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.375) {
+        RealType t = p - 0.375;
+
+        // Rational Approximation
+        // Maximum Relative Error: 5.1929e-35
+        static const RealType P[11] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31348919222343858173602105619413801018e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02800226274700443079521563669609776285e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02091675505570786434803291987263553778e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50141943970885120432710080552941486001e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.93099903417013423125762526465625227789e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.56412922160141953385088141936082249641e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47026602535072645589119440784669747242e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.01068960815396205074336853052832780888e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.86591619131639705495877493344047777421e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.26390836417639942474165178280649450755e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.18212484486162942333407102351878915285e0),
+        };
+        static const RealType Q[10] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97802777458574322604171035748634755981e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.33277809211107726455308655998819166901e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.76555481647551088626503871996617234475e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33146828123660043197526014404644087069e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65159900182434446550785415837526228592e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.32391192521438191878041140980983374411e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.12112886240590711980064990996002999330e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.93964809733838306198746831833843897743e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53948309965401603055162465663290204205e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.25) {
+        RealType t = p - 0.25;
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.2765e-35
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55081568282045925871949387822806890848e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21080883686702131458668798583937913025e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15083151599213113740932148510289036342e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94190629930345397070104862391009053509e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.40768205403470729468297576291723141480e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00001008242667338579153437084294876585e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70900785394455368299616221471466320407e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48947677419760753410122194475234527150e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.01826174001050912355357867446431955195e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.55833657916143927452986099130671173511e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.32953617526068647169047596631564287934e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.32825234826729794599233825734928884074e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.47352171888649528242284500266830013906e1),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40793887011403443604922082103267036101e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.04348824299115035210088417095305744248e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19680004238557953382868629429538716069e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.31172263627566980203163658640597441741e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.07390429662527773449936608284938592773e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94877589960261706923147291496752293313e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.94903802003585398809229608695623474341e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80417437710146805538675929521229778181e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.23364098614130091185959973343748897970e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.12975537807357019330268041620753617442e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36592279898578127130605391750428961301e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18495624730372864715421146607185990918e1),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (p >= 0.125) {
+        RealType t = p - 0.125;
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.8007e-35
+        static const RealType P[14] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68160868054034088524891526884683014057e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85165791469635551063850795991424359350e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42938802867742165917839659578485422534e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59273512668331194186228996665355137458e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91680503091725091370507732042764517726e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85642348415580865994863513727308578556e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.90181935466760294413877600892013910183e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.89141276256233344773677083034724024215e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00250514074918631367419468760920281159e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28168216451109123143492880695546179794e6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14996399533648172721538646235459709807e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.58122093722347315498230864294015130011e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25168985723506298009849577846542992545e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01179759985059408785527092464505889999e5),
+        };
+        static const RealType Q[15] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08766677593618443545489115711858395831e1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.05163374816838964338807027995515659842e2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62582103160439981904537982068579322820e3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.62170991799612186300694554812291085206e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11013837158432827711075385018851760313e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45458895395245243570930804678601511371e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.08336489932795411216528182314354971403e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.11314692423102333551299419575616734987e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.43287683964711678082430107025218057096e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62052814931825182298493472041247278475e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91440920656902450957296030252809476245e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.54913345383745613446952578605023052270e5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.76034827722473399290702590414091767416e4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94027684838690965214346010602354223752e3),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
+    }
+    else if (ilogb(p) >= -4) {
+        RealType t = -log2(ldexp(p, 3));
+
+        // Rational Approximation
+        // Maximum Relative Error: 6.1905e-36
+        static const RealType P[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.10201085067542610656114408605853786551e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04725580445598482170291458376577106746e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35945839005443673797792325217359695272e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15894004364989372373490772246381545906e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54550169514753150042231386414687368032e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50389998399729913427837945242228928632e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75018554725308784191307050896936055909e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95901705695908219804887362154169268380e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34386856794684798098717884587473860604e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.89025399683852111061217430321882178699e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19044156703773954109232310846984749672e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11932910013840927659486142481532276176e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64064398716881126082770692219937093427e-10),
+        };
+        static const RealType Q[13] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24909572944428286558287313527068259394e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.70912720447370835699164559729287157119e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21998644852982625437008410769048682388e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.95906385698373052547496572397097325447e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35344144061390771459100718852878517200e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34168669072527413734185948498168454149e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.24488907049996230177518311480230131257e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92059624838630990024209986717533470508e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84464614954263838504154559314144088371e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.67874815200287308180777775077428545024e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65919857481420519138294080418011981524e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31466713452016682217190521435479677133e-10),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -8) {
+        RealType t = -log2(ldexp(p, 4));
+
+        // Rational Approximation
+        // Maximum Relative Error: 8.5157e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06147398566773479301585022897491054494e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06137881154706023038556659418303323027e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.00274868819366386235164897614448662308e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.03481313941011533876096564688041226638e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50172569438851062169493372974287427240e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.33370725278950299189434839636002761850e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.97566905908106543054773229070602272718e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85701973515993932384374087677862623215e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81956143385351702288398705969037130205e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49975572102999645354655667945479202048e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.54665400959860442558683245665801873530e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94292402413454232307556797758030774716e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98038791388715925556623187510676330309e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11242951548709169234296005470944661995e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.92636379295018831848234711132457626676e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77389296072621088586880199705598178518e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.57808410784300002747916947756919004207e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.93860773322862111592582321183379587624e-16),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52683694883265337797012770275040297516e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17837082293165509684677505408307814500e0),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06195236296471366891670923430225774487e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29459155224640682509948954218044556307e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.71350726081102446771887145938865551618e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55986063168260695680927535587363081713e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91996892322204645930710038043021675160e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43907073162091303683795779882887569537e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.50034830055055263363497137448887884379e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.56615898355501904078935686679056442496e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.61099855362387625880067378834775577974e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.12940315230564635808566630258463831421e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73572881409271303264226007333510301220e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77786420070246087920941454352749186288e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77914406265766625938477137082940482898e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19708585422668069396821478975324123588e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40406059898292960948942525697075698413e-15),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -16) {
+        RealType t = -log2(ldexp(p, 8));
+
+        // Rational Approximation
+        // Maximum Relative Error: 7.6812e-36
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48209596014908270566135466727658374314e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02026332003132864886056710532156370366e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68941634461905013212266453851941196774e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.61650792370551069313309111250434438540e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52611930219013953260661961529732777539e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29488123972430683478601278003510200360e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68806175827491046693183596144172426378e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51806782259569842628995584152985951836e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92353868262961486571527005289554589652e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21494769586031703137329731447673056499e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.39837421784601055804920937629607771973e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82216155524308827738242486229625170158e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04275785296896148301798836366902456306e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19999929939765873468528448012634122362e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.03583326787146398902262502660879425573e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59755092249701477917281379650537907903e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32583227076029470589713734885690555562e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18237323554153660947807202150429686004e-20),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.38459552164692902984228821988876295376e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21584899508575302641780901222203752951e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19656836695824518143414401720590693544e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39821085943818944882332778361549212756e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60484296824768079700823824408428524933e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22173385695010329771921985088956556771e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95541259523416810836752584764202086573e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.02184255281138028802991551275755427743e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90825805251143907045903671893185297007e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00501277755608081163250456177637280682e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43387099521800224735155351696799358451e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63751106922299101655071906417624415019e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02796982349519589339629488980132546290e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26197249278457937947269910907701176956e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50981935956236238709523457678017928506e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65309560070040982176772709693008187384e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42817828965851841104270899392956866435e-20),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -32) {
+        RealType t = -log2(ldexp(p, 16));
+
+        // Rational Approximation
+        // Maximum Relative Error: 2.8388e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36719010559816175149447242695581604280e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14714772485724956396126176973339095223e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47792450677638612907408723539943311437e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14084804538576805298420530820092167411e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.25784891219227004394312050838763762669e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06837168825575413225975778906503529455e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26908306638706189702624634771158355088e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06396335535135452379658152785541731746e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89854018431899039966628599727721422261e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.48974049316978526855972339306215972434e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50886538662952684349385729585856778829e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.14095970401472469264258565259303801322e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71915162586912203234023473966563445362e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.46099196574734038609354417874908346873e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.69944075002490023348175340827135133316e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.37340205792165863440617831987825515203e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87812199530402923085142356622707924805e-22),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76810877067601573471489978907720495511e-24),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.94373217074550329856398644558576545146e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17462725343185049507839058445338783693e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79202779096887355136298419604918306868e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97583473532621831662838256679872014292e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67819154370257505016693473230060726722e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14182379349642191946237975301363902175e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.38367234191828732305257162934647076311e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98221340505887984555143894024281550376e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17648765147609962405833802498013198305e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.94091261341172666220769613477202626517e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12169979717068598708585414568018667622e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70043694579268983742161305612636042906e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43651270200498902307944806310116446583e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.95266223996097470768947426604723764300e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15821111112681530432702452073811996961e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08041298058041360645934320138765284054e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91893114159827950553463154758337724676e-24),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -64) {
+        RealType t = -log2(ldexp(p, 32));
+
+        // Rational Approximation
+        // Maximum Relative Error: 1.8746e-35
+        static const RealType P[19] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619775525705288697351261475419832625e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29882145587771350744255724773409752285e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07952726597277085327360888304737411175e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72928496414816922167597110591366081416e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.01641163277458693633771532254570177776e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65627339211110756774878685166318417370e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41953343652571732907631074381749818724e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27682202874503433884090203197149318368e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33177176779158737868498722222027162030e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.34485618544363735547395633416797591537e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96996761199233617188435782568975757378e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.49631247632674130553464740647053162499e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68090516971007163491968659797593218680e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39910262557283449853923535586722968539e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83704888007521886644896435914745476741e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87884425419276681417666064027484555860e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36600092466902449189685791563990733005e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.53604301472332155307661986064796109517e-26),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65664588229982894587678197374867153136e-40),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61098031370834273919229478584740981117e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.40810642301361416278392589243623940154e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.42874346984605660407576451987840217534e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30896462654364903689199648803900475405e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.17246449391141576955714059812811712587e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22979790521806964047777145482613709395e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.85960899519336488582042102184331670230e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66273852553220863665584472398487539899e-9),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15372731217983084923067673501176233172e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.09441788794783860366430915309857085224e-12),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06279112323261126652767146380404236150e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36359339522621405197747209968637035618e-15),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19770526521305519813109395521868217810e-17),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.88562963284557433336083678206625018948e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95128165317597657325539450957778690578e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14570923483883184645242764315877865073e-23),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.69599603258626408321886443187629340033e-26),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else if (ilogb(p) >= -128) {
+        RealType t = -log2(ldexp(p, 64));
+
+        // Rational Approximation
+        // Maximum Relative Error: 3.9915e-35
+        static const RealType P[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344576326594951209529606e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72456363182667891167613558295097711432e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74486567435450138741058930951301644059e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94624522781897679952110594449134468564e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09848623985771449914778668831103210333e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.47493285141689711937343304940229517457e-5),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22134975575390048261922652492143139174e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30240148387764167235466713023950979069e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06917824188001432265980161955665997666e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27834220508404489112697949450988070802e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48663447630051388468872352628795428134e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50514504588736921389704370029090421684e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18965303814265217659151418619980209487e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74200654214326267651127117044008493519e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.34060054352573532839373386456991657111e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.34240516843783954067548886404044879120e-20),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07803703545135964499326712080667886449e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61500479431085205124031101160332446432e-23),
+        };
+        static const RealType Q[18] = {
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27973454499231032893774072677004977154e-1),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02401389920613749641292661572240166038e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24819328156695252221821935845914708591e-2),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27210724381675120281861717194783977895e-3),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01708007392492681238863778030115281961e-4),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63088069045476088736355784718397594807e-6),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61660379368211892821215228891806384883e-7),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67946125503415200067055797463173521598e-8),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72040422051759599096448422858046040086e-10),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33519997465950200122152159780364149268e-11),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07666528975810553712124845533861745455e-13),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86870262247486708096341722190198527508e-14),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30713380444621290817686989936029997572e-16),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.38899571664905345700275460272815357978e-18),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46750157220118157937510816924752429685e-19),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69337661543585547694652989893297703060e-21),
+            BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53684359865963395505791671817598669527e-23),
+        };
+
+        result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
+    }
+    else {
+        result = 2 / (constants::pi<RealType>() * p);
+    }
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+{
+    if (p > 0.5) {
+        return landau_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? landau_quantile_upper_imp_prec(p, tag) : landau_quantile_lower_imp_prec(p, tag);
+}
+
+template <class RealType>
+inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+{
+    if (p > 0.5) {
+        return landau_quantile_imp_prec(1 - p, !complement, tag);
+    }
+
+    return complement ? landau_quantile_upper_imp_prec(p, tag) : landau_quantile_lower_imp_prec(p, tag);
+}
+
+template <class RealType, class Policy>
+inline RealType landau_quantile_imp(const landau_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+{
+    // This routine implements the quantile for the Landau distribution,
+    // the value p may be the probability, or its complement if complement=true.
+
+    static const char* function = "boost::math::quantile(landau<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+    RealType bias = dist.bias();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_probability(function, p, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    result = location + scale * (landau_quantile_imp_prec(p, complement, tag_type()) - bias);
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_mode_imp_prec(const std::integral_constant<int, 53>&)
+{
+    return static_cast<RealType>(-0.42931452986133525017);
+}
+
+template <class RealType>
+inline RealType landau_mode_imp_prec(const std::integral_constant<int, 113>&)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.42931452986133525016556463510885028346);
+}
+
+template <class RealType, class Policy>
+inline RealType landau_mode_imp(const landau_distribution<RealType, Policy>& dist)
+{
+    // This implements the mode for the Landau distribution,
+
+    static const char* function = "boost::math::mode(landau<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+    RealType bias = dist.bias();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    result = location + scale * (landau_mode_imp_prec<RealType>(tag_type()) - bias);
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_median_imp_prec(const std::integral_constant<int, 53>&)
+{
+    return static_cast<RealType>(0.57563014394507821440);
+}
+
+template <class RealType>
+inline RealType landau_median_imp_prec(const std::integral_constant<int, 113>&)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, 0.57563014394507821439627930892257517269);
+}
+
+template <class RealType, class Policy>
+inline RealType landau_median_imp(const landau_distribution<RealType, Policy>& dist)
+{
+    // This implements the median for the Landau distribution,
+
+    static const char* function = "boost::math::median(landau<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+    RealType location = dist.location();
+    RealType bias = dist.bias();
+
+    if (false == detail::check_location(function, location, &result, Policy()))
+    {
+        return result;
+    }
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    result = location + scale * (landau_median_imp_prec<RealType>(tag_type()) - bias);
+
+    return result;
+}
+
+template <class RealType>
+inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 53>&)
+{
+    return static_cast<RealType>(2.37263644000448182448);
+}
+
+template <class RealType>
+inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 113>&)
+{
+    return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.3726364400044818244844049010588577710);
+}
+
+template <class RealType, class Policy>
+inline RealType landau_entropy_imp(const landau_distribution<RealType, Policy>& dist)
+{
+    // This implements the entropy for the Landau distribution,
+
+    static const char* function = "boost::math::entropy(landau<%1%>&, %1%)";
+    BOOST_MATH_STD_USING // for ADL of std functions
+
+    RealType result = 0;
+    RealType scale = dist.scale();
+
+    if (false == detail::check_scale(function, scale, &result, Policy()))
+    {
+        return result;
+    }
+
+    typedef typename tools::promote_args<RealType>::type result_type;
+    typedef typename policies::precision<result_type, Policy>::type precision_type;
+    typedef std::integral_constant<int,
+        precision_type::value <= 0 ? 0 :
+        precision_type::value <= 53 ? 53 :
+        precision_type::value <= 113 ? 113 : 0
+    > tag_type;
+
+    static_assert(tag_type::value, "The Landau distribution is only implemented for types with known precision, and 113 bits or fewer in the mantissa (ie 128 bit quad-floats");
+
+    result = landau_entropy_imp_prec<RealType>(tag_type()) + log(scale);
+
+    return result;
+}
+
+} // detail
+
+template <class RealType = double, class Policy = policies::policy<> >
+class landau_distribution
+{
+    public:
+    typedef RealType value_type;
+    typedef Policy policy_type;
+
+    landau_distribution(RealType l_location = 0, RealType l_scale = 1)
+        : mu(l_location), c(l_scale)
+    {
+        static const char* function = "boost::math::landau_distribution<%1%>::landau_distribution";
+        RealType result = 0;
+        detail::check_location(function, l_location, &result, Policy());
+        detail::check_scale(function, l_scale, &result, Policy());
+
+        using std::log;
+        location_bias = -2 / constants::pi<RealType>() * log(l_scale);
+    } // landau_distribution
+
+    RealType location()const
+    {
+        return mu;
+    }
+    RealType scale()const
+    {
+        return c;
+    }
+    RealType bias()const
+    {
+        return location_bias;
+    }
+
+    private:
+    RealType mu;    // The location parameter.
+    RealType c;     // The scale parameter.
+    RealType location_bias;  // = -2 / pi * log(c)
+};
+
+typedef landau_distribution<double> landau;
+
+#ifdef __cpp_deduction_guides
+template <class RealType>
+landau_distribution(RealType) -> landau_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+template <class RealType>
+landau_distribution(RealType, RealType) -> landau_distribution<typename boost::math::tools::promote_args<RealType>::type>;
+#endif
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> range(const landau_distribution<RealType, Policy>&)
+{ // Range of permissible values for random variable x.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline const std::pair<RealType, RealType> support(const landau_distribution<RealType, Policy>&)
+{ // Range of supported values for random variable x.
+   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
+    if (std::numeric_limits<RealType>::has_infinity)
+    {
+        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+    }
+    else
+    { // Can only use max_value.
+        using boost::math::tools::max_value;
+        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+    }
+}
+
+template <class RealType, class Policy>
+inline RealType pdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::landau_pdf_imp(dist, x);
+} // pdf
+
+template <class RealType, class Policy>
+inline RealType cdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
+{
+    return detail::landau_cdf_imp(dist, x, false);
+} // cdf
+
+template <class RealType, class Policy>
+inline RealType quantile(const landau_distribution<RealType, Policy>& dist, const RealType& p)
+{
+    return detail::landau_quantile_imp(dist, p, false);
+} // quantile
+
+template <class RealType, class Policy>
+inline RealType cdf(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::landau_cdf_imp(c.dist, c.param, true);
+} //  cdf complement
+
+template <class RealType, class Policy>
+inline RealType quantile(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
+{
+    return detail::landau_quantile_imp(c.dist, c.param, true);
+} // quantile complement
+
+template <class RealType, class Policy>
+inline RealType mean(const landau_distribution<RealType, Policy>&)
+{  // There is no mean:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "The Landau Distribution has no mean");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::mean(landau<%1%>&)",
+        "The Landau distribution does not have a mean: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType variance(const landau_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no variance:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "The Landau Distribution has no variance");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::variance(landau<%1%>&)",
+        "The Landau distribution does not have a variance: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType mode(const landau_distribution<RealType, Policy>& dist)
+{
+    return detail::landau_mode_imp(dist);
+}
+
+template <class RealType, class Policy>
+inline RealType median(const landau_distribution<RealType, Policy>& dist)
+{
+    return detail::landau_median_imp(dist);
+}
+
+template <class RealType, class Policy>
+inline RealType skewness(const landau_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no skewness:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "The Landau Distribution has no skewness");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::skewness(landau<%1%>&)",
+        "The Landau distribution does not have a skewness: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis(const landau_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "The Landau Distribution has no kurtosis");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis(landau<%1%>&)",
+        "The Landau distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType kurtosis_excess(const landau_distribution<RealType, Policy>& /*dist*/)
+{
+    // There is no kurtosis excess:
+    typedef typename Policy::assert_undefined_type assert_type;
+    static_assert(assert_type::value == 0, "The Landau Distribution has no kurtosis excess");
+
+    return policies::raise_domain_error<RealType>(
+        "boost::math::kurtosis_excess(landau<%1%>&)",
+        "The Landau distribution does not have a kurtosis: "
+        "the only possible return value is %1%.",
+        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+}
+
+template <class RealType, class Policy>
+inline RealType entropy(const landau_distribution<RealType, Policy>& dist)
+{
+    return detail::landau_entropy_imp(dist);
+}
+
+}} // namespaces
+
+
+#endif // BOOST_STATS_LANDAU_HPP
diff --git a/include/boost/math/distributions/non_central_beta.hpp b/include/boost/math/distributions/non_central_beta.hpp
index 66b12e870a..a8c8af868a 100644
--- a/include/boost/math/distributions/non_central_beta.hpp
+++ b/include/boost/math/distributions/non_central_beta.hpp
@@ -847,7 +847,7 @@ namespace boost
       { // skewness = sqrt(l).
          const char* function = "boost::math::non_central_beta_distribution<%1%>::skewness()";
          typedef typename Policy::assert_undefined_type assert_type;
-         static_assert(assert_type::value == 0, "Assert type is undefined.");
+         static_assert(assert_type::value == 0, "The Non Central Beta Distribution has no skewness.");
 
          return policies::raise_evaluation_error<RealType>(function, "This function is not yet implemented, the only sensible result is %1%.", // LCOV_EXCL_LINE
             std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
@@ -858,7 +858,7 @@ namespace boost
       {
          const char* function = "boost::math::non_central_beta_distribution<%1%>::kurtosis_excess()";
          typedef typename Policy::assert_undefined_type assert_type;
-         static_assert(assert_type::value == 0, "Assert type is undefined.");
+         static_assert(assert_type::value == 0, "The Non Central Beta Distribution has no kurtosis excess.");
 
          return policies::raise_evaluation_error<RealType>(function, "This function is not yet implemented, the only sensible result is %1%.", // LCOV_EXCL_LINE
             std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 6d962a08a6..e2d54a2d3e 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -522,7 +522,9 @@ struct non_type {};
    using std::ceil;\
    using std::floor;\
    using std::log10;\
-   using std::sqrt;
+   using std::sqrt;\
+   using std::log2;\
+   using std::ilogb;
 
 #define BOOST_MATH_STD_USING BOOST_MATH_STD_USING_CORE
 
diff --git a/test/Jamfile.v2 b/test/Jamfile.v2
index c7eaa3b1eb..67fb25163c 100644
--- a/test/Jamfile.v2
+++ b/test/Jamfile.v2
@@ -557,6 +557,7 @@ test-suite special_fun :
 
 test-suite distribution_tests :
    [ run test_arcsine.cpp pch ../../test/build//boost_unit_test_framework  ]
+   [ run test_landau.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
    [ run test_bernoulli.cpp ../../test/build//boost_unit_test_framework  ]
    [ run test_beta_dist.cpp ../../test/build//boost_unit_test_framework  ]
    [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
@@ -1380,6 +1381,7 @@ test-suite concepts :
    [ run  compile_test/dist_inv_chi_sq_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_hyperexponential_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_hypergeo_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
+   [ run  compile_test/dist_landau_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_laplace_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_logistic_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_lognormal_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
diff --git a/test/compile_test/dist_landau_incl_test.cpp b/test/compile_test/dist_landau_incl_test.cpp
new file mode 100644
index 0000000000..5b63a710ab
--- /dev/null
+++ b/test/compile_test/dist_landau_incl_test.cpp
@@ -0,0 +1,26 @@
+//  Copyright John Maddock 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// Basic sanity check that header <boost/math/distributions/landau.hpp>
+// #includes all the files that it needs to.
+//
+#define BOOST_MATH_ASSERT_UNDEFINED_POLICY false
+#include <boost/math/distributions/landau.hpp>
+//
+// Note this header includes no other headers, this is
+// important if this test is to be meaningful:
+//
+#include "test_compile_result.hpp"
+
+void compile_and_link_test()
+{
+   TEST_DIST_FUNC(landau)
+}
+
+template class boost::math::landau_distribution<float, boost::math::policies::policy<> >;
+template class boost::math::landau_distribution<double, boost::math::policies::policy<> >;
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+template class boost::math::landau_distribution<long double, boost::math::policies::policy<> >;
+#endif
diff --git a/test/compile_test/instantiate.hpp b/test/compile_test/instantiate.hpp
index bdb6d515cf..7b78e25be8 100644
--- a/test/compile_test/instantiate.hpp
+++ b/test/compile_test/instantiate.hpp
@@ -28,6 +28,7 @@ template <class RealType> bool instantiate_mixed_runner_result<RealType>::value;
 
 #include <boost/math/special_functions.hpp>
 #include <boost/concept_archetype.hpp>
+#include <boost/concept_check.hpp>
 #include <boost/math/distributions.hpp>
 
 #if !defined(BOOST_MATH_NO_DISTRIBUTION_CONCEPT_TESTS)
@@ -73,6 +74,24 @@ BOOST_MATH_DECLARE_DISTRIBUTIONS(double, test_policy)
 #  define TEST_GROUP_15
 #endif
 
+template <class RealType>
+void instantiate_for_fixed_precision_only(RealType, const std::true_type&)
+{
+   using namespace boost;
+   using namespace boost::math;
+   using namespace boost::math::concepts;
+
+#ifdef TEST_GROUP_1
+#if !defined(BOOST_MATH_NO_DISTRIBUTION_CONCEPT_TESTS)
+   function_requires<DistributionConcept<landau_distribution<RealType> > >();
+   function_requires<DistributionConcept<landau_distribution<RealType, test_policy> > >();
+   function_requires<DistributionConcept<dist_test::landau > >();
+#endif
+#endif
+}
+template <class RealType>
+void instantiate_for_fixed_precision_only(RealType, const std::false_type&){}
+
 template <class RealType>
 void instantiate(RealType)
 {
@@ -118,6 +137,9 @@ void instantiate(RealType)
    function_requires<DistributionConcept<triangular_distribution<RealType> > >();
    function_requires<DistributionConcept<uniform_distribution<RealType> > >();
    function_requires<DistributionConcept<weibull_distribution<RealType> > >();
+
+   instantiate_for_fixed_precision_only(RealType(), std::integral_constant<bool, std::numeric_limits<RealType>::is_specialized && (std::numeric_limits<RealType>::digits <= 113) && (std::numeric_limits<RealType>::radix == 2)>());
+
    #endif // !defined(BOOST_MATH_NO_DISTRIBUTION_CONCEPT_TESTS)
 #endif
 #ifndef BOOST_MATH_INSTANTIATE_MINIMUM
diff --git a/test/test_landau.cpp b/test/test_landau.cpp
new file mode 100644
index 0000000000..08d18ec8e6
--- /dev/null
+++ b/test/test_landau.cpp
@@ -0,0 +1,847 @@
+// Copyright Takuma Yoshimura 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_TEST_MAIN
+#define BOOST_TEST_MODULE StatsLandauTest
+#include <boost/test/included/unit_test.hpp>
+#include <boost/test/tools/floating_point_comparison.hpp>
+#include <boost/multiprecision/cpp_bin_float.hpp>
+
+#include <boost/math/distributions/landau.hpp>
+
+#if __has_include(<stdfloat>)
+# include <stdfloat>
+#endif
+
+using boost::math::landau_distribution;
+using boost::multiprecision::cpp_bin_float_quad;
+
+template<class RealType, int N>
+void do_test_landau_pdf(){
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    // Left tail of Landau distribution inherently limits accuracy due to the rapid decay of the function value.
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.23085262843901249987787600097675204323741277288698e-2763), tolerance * 10000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.43092685592935588160074717060232841559786193515624e-1259), tolerance * 10000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.07984079126853424748872672315932614660166330244758e-574), tolerance * 4000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51902330649665702862232056199116883579782363388698e-261), tolerance * 1000);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.61740160083645125413680224234682096739098348513281e-119), tolerance * 400);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.40268429420551752841762522647338593851384890728514e-54), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.64264014182893964260735316412669280242258553581563e-37), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.96628298286997713279446280099737948363623849272499e-25), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.65014695258589331535696024118503069088391324558285e-17), tolerance * 100);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52577680004870416264378840612037346351517011876564e-11), tolerance * 40);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.96564073685328676511751663666044321538322085645615e-8), tolerance * 40);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.49195679110887105000100573294850045215882388658736e-5), tolerance * 10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.83029281547111049679644135145824504175531296639784e-4), tolerance * 4);
+
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.50763682207511020788551990942118742909694977020766e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55239934591810979484111502955882518822410677336301e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.11811339800999276275816189148400161297598608940370e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.43803188361205250108898134179433045737003842752098e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44559645555354621908225839934967437642938589048641e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.19256762240252210606670736977933945194758525070962e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55747609478534232829752995639617852824070107389867e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.90787204474682320276094536207112207798402106183626e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.21762208692280384264052188465103527015057255360522e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.35142856681038695962612277740850797545496160091346e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46926317225475336949604234617889242016284403135263e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.57038182663311646092167022800387128596042855954974e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65453539644067140109079490907422208395106068408806e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72189928839617935958276513066615896148477769341984e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77299781354951097794140321722510611592577477809046e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.80862887196928314574763226767834515262714169253341e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.82979296472337068393182796635835781531645972141685e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83762914935252825962037404558307269544013453409236e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83335939453844198706047097920194738266342072083183e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.81824188244607845783889480215304948211453087161311e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79353314321623987234651193548815637401927993615201e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.76045845604337224786926223067521339118457783620200e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.72018967730828877761590993107231423707402335516208e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.67382951900254916684467526412940597211696659408252e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.62240126375351657025589608183516471314881294729647e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.56684293488331550048284390907274219670798777890274e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.50800501583089077855151395221936193088464543391697e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.44665091350810416315066697862911894015423062289459e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.38345947054726504652084392231776081590084152956389e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31902894209756674501863785530002142859374765415539e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25388195748200100617512573536171938322886836672500e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.18847108191054606649972320910802001046885937665349e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.12318467675064265241298421202132871385510191955048e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05835282809935995378486652717710487064456876565464e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.99425317296731752992133425091298094257535743484505e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.93111650117890312500196499480137441707124661561802e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86913205029713491869481191910148340512494429155677e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.80845244177744590342641324845464181512725512270901e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74919823041494123736512984399481253444800810061398e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.69146205716679200390505774997534008647397580964682e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.63531240868022603475813051802104652763421266792797e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52794577355035866144175272867439043108097332289280e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.42728268648990888425150769069939371653574963683898e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.33330183140387812967271143318337448709293578674499e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.24583903791438503777896988292725453902854934482082e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.16463504238864475787300731138600083506835647657585e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08937118376337417303260299595016407050621597377842e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01969562586719050610986409853288944869103385155807e-1), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.55242261334771588093967856464157010583515904813711e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40542106335080455284302185631726193959498759868958e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.42466467030240081155174776845818529710340047591917e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.58484837369864336802514847217316987349368653299870e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.86394883380361824062302169684513676586056038951383e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.24319810137134739489567689474925534356381531907667e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.70679858898932226345344507218372775665959269901845e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.24154519527191616123631238437619039275267092832219e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.83643820409470770350079809236512802617514831283958e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.17158939997042257734107084716347218188987519860810e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.65588931293442756274955123891841674957134577995432e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.24999943998132461512162382109845468953569057653206e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.92615450486233381461674333853015589016995103903169e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.66449631910567440889641030798080985765446733145615e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.45062281189987454243698017666196791149621836621069e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.27394302531621603387264220385271200998719076373774e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12656323880287532946687856443190592954884366662750e-2), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(9)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.97272209098442387115881795542777687494895710641442e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(10)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.29822142754406367527698808542596968321101482611499e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.04211802337476854086853204096220197132228559528499e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.07803739765703855539464392586871287241424478552475e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.32333875346680119671101261202737313738117089411627e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.72232982334134875374745579629692504175963269123550e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.23647379895109194018623503694593516089449736564227e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.83847488747490686627461184914507143000166295798209e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.23229209720541068914767304360845920096605060550204e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79947182256974676114073539538738666749318597550126e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48016777321149926163568000853843271440982208135806e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.23815521917416110142990010737370397993296057042020e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05051356188948975788809310742705170449199446295996e-3), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.02189494175551818802120780043908400302499693753383e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.82977743390109357722237932712596740553146168838163e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.85767880395157523314894776472286059373130513345678e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.38436988071020010518465973524617926941561115862543e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.33733686912592492663864652100824543220296291087705e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.56719760886187032655497099894304037738414747694058e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98455504950479524812911915761096343833926775180855e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.53330379508737569512814290970113441709685617438320e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.17681386666988585981678825113751906947724221061916e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89036019000414403525553377301848537121144402020797e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65677119200426097313111689557286038389044055520291e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.30262785101049126879812527584486523431435416855092e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05075497824543686508583330151701088746046662556142e-4), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.65309719784826735811404845249006631571011107397937e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.24862987881373408810690419771199915049078409763957e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.15969937273460908511004283053502890256890552857434e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.29851658065131948803621145305770537695198696080417e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.60580149897015438520712002341005415255634795262650e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.04036158768936643116910162586744782570492472991852e-5), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.94016243990046849166189460556288227597025594512208e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(512)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46086028677885635430916943188657821915692719236659e-6), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.11684517285572531637079275580373275248746393740505e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 11)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.52416040197318095218142515144159361915369773070323e-7), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 12)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.80328507092562833387828627033077037362079287147494e-8), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 13)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.49830894979328205589801770626380874036837651152185e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 14)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37321260457507890170942420030228551149027146711858e-9), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 15)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.93116689130330056188281287044879751157310863062584e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 16)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48253875064413349633513149673423379659751420343007e-10), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 17)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.70600576035028939688935887999924497768090063213495e-11), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 18)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.26455685393631638684357809746815117207931914505548e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 19)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31607812424720075650435345952742430841572532807506e-12), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 20)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.79011407780867471284567547634162699267979186606188e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 21)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44751775633854916204285667335984781835956253195982e-13), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 22)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.61878017561309094548695350627490496501579775589554e-14), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 23)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.04693171826032841875566733962302122545285900020005e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 24)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26173047049833308211942124367857471386868403241961e-15), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.65432295369693602811408648241147072923809751085578e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 26)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41358031701599971473805281134574751063094181933632e-16), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 27)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.53395024254254681824332124678431347548990493315457e-17), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 28)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.83487488981301080647710951024578189621167614209000e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 29)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20871862925450931967259224559170596670053211110073e-18), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 30)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.52179645209930996243372289840247886946662593536877e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 31)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38044909732789001695763980339161333087125784369381e-19), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 32)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.45112272298940668060590155421055597940788628104792e-20), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 34)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15695169189532579197171519055168026495351913764385e-21), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 36)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34809480577241011630081955001585893790541249979882e-22), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 38)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.42559253331811413189334788330851699569177453819777e-24), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 40)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.26599533286729634727335420905860617977183492898697e-25), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 42)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.29124708296676552183969416435576047604811850887072e-26), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 44)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05702942684184448841776719264034349959339461930208e-27), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 46)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28564339177412106630199552439532586497065103592483e-28), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 48)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.03527119858493090854162194048072858076706076597819e-30), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 50)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.02204449911503854915599875932648541933495423396290e-31), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 52)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13877781194681051697029360385733987849026091896815e-32), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 54)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96173613246674215642318845771797429014235991071697e-33), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 56)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22608508279171150505713607335390403334626262247470e-34), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 58)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.66303176744819310534466860343470655112837733629379e-36), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 60)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.78939485465512007489594618239133015330653514470962e-37), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 62)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.99337178415944994713157754959412500112801769504923e-38), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 64)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87085736509965620084544629248142254049400680133870e-39), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 68)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.30803658242053201409813080005840450554429514097447e-42), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 72)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85470179000802031747569733233640023770585023325816e-44), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 76)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.11511788672188293650018950543585978468059122696737e-46), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 80)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.35592924500735522070031636324180548468184125270321e-49), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 84)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70153486133099813308596977841944913997064236009234e-51), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 88)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.64662055207421145736704601944518511418678161667227e-54), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 92)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.59633615315398885053400175162079403845778513781261e-56), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 96)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01419380982577689473984441890730791873276374028644e-58), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 100)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.96169456963194099507751725745105477863201113021124e-61), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 104)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54753694126247695120215517859242605013890436588657e-63), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 108)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.04506617680655059063341866635141218965712131228669e-66), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 112)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36135397531505882446617916654287979923104956976029e-68), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 116)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.22403896607444853307101236930796194301091622511538e-71), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 120)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.60314022112283145823086420676091852871339922342198e-73), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 124)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40747664887610603837143133076598369654786648237564e-75), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.49795565967228921238840363580462378845964351238859e-78), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 128)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.49795565967228921238840363580462378845964351238859e-78), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 136)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.38921456859174989683289128998508268228293005240118e-83), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 144)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28009255502193449353529225005875895420403010118164e-87), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 152)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.95326622775563734975477943429376061127322830738396e-92), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 160)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.98044773522283531151547154891015718272892496044375e-97), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 168)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.54780233035710954515910575700402402149799340844629e-102), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 176)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.93939564568650748467881127472537845077208466864701e-107), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 184)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.05886774378761405711041431804281287395814280222275e-111), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 192)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.61570395475404976976076403509950694878867004733696e-116), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 200)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.46536858330390895044061895004197227293193061422265e-121), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 208)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.76185391739488060064791709906306804341420076633095e-126), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 216)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.74013354094677826026598678445902716585418818104698e-131), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 224)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.75874868918880960123594174874729486977262600867765e-136), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 232)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.33647898699780419940733974437672346035348907603114e-140), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 240)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.03930509490631744294332846737170938164289714970571e-145), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 248)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.11173262772570410605366282252763272345412773087419e-150), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist, ldexp(static_cast<RealType>(1), 256)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74812717853653580635629703144475208046589314403411e-155), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_cdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    // Left tail of Landau distribution inherently limits accuracy due to the rapid decay of the function value.
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.23104384186197610398535377648417544130503923472088e-2767), tolerance * 10000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13839831060468958638389597955042905895011279005609e-1263), tolerance * 10000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.44312475898376675389279659203392726913179988221856e-577), tolerance * 4000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60161744250590449897633679409320688863793657438650e-264), tolerance * 1000);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.35715172357835600843326068305277508896293574359993e-122), tolerance * 400);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21485044777822987831938208827397125595048645106450e-56), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20700596052912975894895710721207297741913643002012e-39), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.68977785355043338853968150291349097131276031028880e-27), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.08280503661515358192902976596786876511904900370188e-18), tolerance * 100);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.65792002575428625860974216754165889856915439054540e-13), tolerance * 40);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.10050102765608360408879765554028186586411956977646e-9), tolerance * 40);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.68815894016077213783105942021589578300879813020189e-7), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.37625644367407768681214121219960213300943983402353e-5), tolerance * 4);
+
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.07114056489178077422539043012078031612755414599729e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02378089289225642153717146519785629105551593533471e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.86628849116890981757518380028315283124563329691336e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01356086445894450901462536543096095003540865562528e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87500433294484935737405475465845379363381335629325e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.14477362642888337899595114315256777323730741351157e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.86347714259952478386139532766899266845283140865196e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.03233833485353985646171581359634291113172343250638e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.61609610406317335842332400044553397267403259400925e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10447280320452875363390566033897366825208362273976e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.25520504813750944299743577454809066282274647597463e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41278210604233003854999957016294448201095585229262e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.57614904197281705412681135912362432813551089393050e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.74424900339390561779123457277662541525802871208804e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.91604740159711318114657552509684829710278507526176e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.09055135109096066379824832581601920047332653592899e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26682451996131584587603100587452166035163093744954e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.44399775009966844789856291613140149240683895719411e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.62127593214618528740100724985588598153581542828585e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.79794168130771479096847395825066083537476191027208e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.97335637253762835584202042505471763077481208909960e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.14695907126043189562824247063432944143645211079990e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.31826385110143246791390839018674857130873325623297e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.48685593270949525320895832911820568633181874504622e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.65238701512374797371944390202236332910560491002867e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.81457010849525523978613828303353744448250289768502e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.97317411782647886281236276761522493696113175680302e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.12801837383425412356107316013533713934091886254748e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.27896726012877622151287254340779424837571495657384e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.42592504593813016256394437035333320729928769135529e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.56883100040026405468976154826963286030986607276898e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.70765483748602800807348700535078666283426208025338e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.84239251923251354944511010208659148773285992261636e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.97306242841106189982720542754596269997825882200963e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.09970190928358551894563742001208165448751595738393e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.22236416601074576846725329522076603667792610069772e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.34111550192882688466795267571966376590108144590146e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.45603287874932276581779533145259002587664864932810e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.56720177227709322443036736236667681466823855576748e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.67471430008752600464561254217339060305933972234066e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.77866759641952347636729485475686950346612605081233e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.97630190201768046886571833364686445094779890812683e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.16093363694296970300414411298982724729800950998126e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.33340119589825831941744118804669746898228023705595e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.49453081078357569536385447775302397639174227456126e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.64512181956668895495628599815612188484872430606076e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.78593712196194817010501161391740217697424135219932e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(1.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.91769748027973587988050487247823119315646010788285e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.04107862044208783622223577234526499721208130809085e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.26517695571963502030771662018373539384937999898516e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.46273425405663094259919090350425049446731674380517e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(2.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.63758376080325935199241149369372014196158210794207e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.79296673358868394263845167623854238605663977145579e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.93161494811251760796024569455411548871678150466575e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.05582884526567009703468807923041602465523081207835e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.16754715036218405381848078882559199991501527210887e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.26840681332434061224397365001110201431714574161004e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.44288421192372625436336887550283154670590764164969e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.58804227080862094903927728732613232538756639404536e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.71029700052871041881284261613115047981162112317573e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.81440531622793612780308998937907666985394243647458e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.90394591759649482553720310181182407678855125658003e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.98164927634689821536641290454567745500263396394663e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(7.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.04962661826577677675750333226666504803112871241155e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(8)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.10953085258825170758957718650744990707007748273190e-1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_ccdf() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.99292885943510821922577460956987921968387244585400e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.97976219107107743578462828534802143708944484064665e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.95133711508831090182424816199716847168754366703087e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.89864391355410554909853746345690390499645913443747e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.81249956670551506426259452453415462063661866437068e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.68552263735711166210040488568474322267626925864884e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.51365228574004752161386046723310073315471685913480e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.29676616651464601435382841864036570888682765674936e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.03839038959368266415766759995544660273259674059908e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.89552719679547124636609433966102633174791637726024e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.74479495186249055700256422545190933717725352402537e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.58721789395766996145000042983705551798904414770738e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.42385095802718294587318864087637567186448910606950e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.25575099660609438220876542722337458474197128791196e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.08395259840288681885342447490315170289721492473824e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.90944864890903933620175167418398079952667346407101e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.73317548003868415412396899412547833964836906255046e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.55600224990033155210143708386859850759316104280589e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37872406785381471259899275014411401846418457171415e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.20205831869228520903152604174933916462523808972792e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.02664362746237164415797957494528236922518791090040e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.85304092873956810437175752936567055856354788920010e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.68173614889856753208609160981325142869126674376703e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(-0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.51314406729050474679104167088179431366818125495378e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.34761298487625202628055609797763667089439508997133e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.0625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.18542989150474476021386171696646255551749710231498e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.02682588217352113718763723238477506303886824319698e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.87198162616574587643892683986466286065908113745252e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.72103273987122377848712745659220575162428504342616e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.57407495406186983743605562964666679270071230864471e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.43116899959973594531023845173036713969013392723102e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.29234516251397199192651299464921333716573791974662e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.15760748076748645055488989791340851226714007738364e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.5625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.02693757158893810017279457245403730002174117799037e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.90029809071641448105436257998791834551248404261607e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.6875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.77763583398925423153274670477923396332207389930228e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.65888449807117311533204732428033623409891855409854e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.8125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.54396712125067723418220466854740997412335135067190e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.43279822772290677556963263763332318533176144423252e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(0.9375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.32528569991247399535438745782660939694066027765934e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.22133240358047652363270514524313049653387394918767e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.02369809798231953113428166635313554905220109187317e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.83906636305703029699585588701017275270199049001874e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.66659880410174168058255881195330253101771976294405e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.50546918921642430463614552224697602360825772543874e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.35487818043331104504371400184387811515127569393924e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.21406287803805182989498838608259782302575864780068e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1.875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.08230251972026412011949512752176880684353989211715e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.95892137955791216377776422765473500278791869190915e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.73482304428036497969228337981626460615062000101484e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.53726574594336905740080909649574950553268325619483e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(2.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36241623919674064800758850630627985803841789205793e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20703326641131605736154832376145761394336022854421e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.06838505188748239203975430544588451128321849533425e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94417115473432990296531192076958397534476918792165e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(3.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.83245284963781594618151921117440800008498472789113e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.73159318667565938775602634998889798568285425838996e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(4.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55711578807627374563663112449716845329409235835031e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41195772919137905096072271267386767461243360595464e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(5.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28970299947128958118715738386884952018837887682427e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18559468377206387219691001062092333014605756352542e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(6.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.09605408240350517446279689818817592321144874341997e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01835072365310178463358709545432254499736603605337e-1), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(7.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.50373381734223223242496667733334951968871287588448e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.90469147411748292410422813492550092929922517268105e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(9))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.89904178519375419646729692713027452766956304810423e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.08967063825624536726393015854367927398248532043928e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.42552960269528172637745151674852945361026757129572e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.87155991603325430279966781361705985837149401924358e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.40297179699419503759356245733027728020687579530781e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.00178775061898975362196226343808042189550214610720e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.65467961100606469227978737829290437667112287748795e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.35157264931262089761621934621402648953813567255367e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.84807181681993477724365847791930879377149510380933e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.44719141256297825765636022076703604777398281522436e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.12076533048217442252783357779404422496811288961954e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.84999992100002427148546326508663805148388380497970e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.62189540632143171631461472152513248987041904718627e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42718378313424593748302632910098340183096121887744e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.25908549106503559691958010353777133320615316433912e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.11253031965493064317003259449214452744697000964364e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.86945568960396455137037115431688883900622129241921e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.67614509428664592918239573763993132586708338097148e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51880213758692367036733937634308433186738240289411e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38828350661980875444222979837389265249992909781147e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.27829420024685114258602774435891775801837844690349e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18436085060190590919501220038943005140750783789755e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.10321854418155548568175979136702978995567636390268e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03242932255189471157625857327944947615628400066886e-2), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.14901073563432515854150573798153430678589620957278e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.21304799594562916903235283213953478595851140543801e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.45021033455396813779806884621309261695988381836678e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.81662081970375351344432645398857600988792278643367e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.28205524656921301117582740567146809114392866561466e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.82502022536734166688286248837161828142031676980706e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.42981578145699797251974720633677573816663490439276e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.08470827750959570805565668839133674990776529552199e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.51875926400324844459822808369891291211052352126700e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(512))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.25243798184186193073508388843632555296804735961418e-3), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, static_cast<RealType>(1024))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.24222666597149382309278694960823422316591681354937e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 11))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.11546656864925721385400506911714668228522959074988e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55615661646764419866569094853675423840407090817980e-4), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 13))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.77642694561457848096607089076550607777923417509897e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.88702045347145575328162812652239839108265167027629e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 15))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.94318591305792177162247519775866592794374293269769e-5), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.71505353250968890581644704744607604904036466331858e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 17))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.85729142998688039060495209150963975787147384530557e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 18))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.42858279647060361837158514176420066606677711840386e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 19))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.21427464712490151175367196840586966659512986509712e-6), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.07132880360935675845351982773327267915998066915668e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 21))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03565265516245957916479321487698564090018898313690e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 22))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.51782323124974173858669998521646771346131838415381e-7), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 23))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.58910801622650317351735034158503382297981706223572e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.79455187330704471571840926063516392410676855026673e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.89727537800148613712401816975344760624742045931026e-8), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 26))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.48637543100068173667331269634864926724205314304352e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 27))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.74318733515442703770226252397963326193722512832281e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.37159356859216986241429458639296184020669300874754e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 29))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.18579675857518154364748998529259019922036982534955e-9), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 30))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.92898372613704146131858586390099325449659727514527e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 31))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.96449184577465200097456706940455493448424599625049e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.48224591841157074706460083370955443589105978681308e-10), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 34))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.70561478725616554450782995120929832467409189826579e-11), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 36))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.26403696230051280181276990208319690098486010067856e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 38))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.31600924018782655652761250713319794226217154394605e-12), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.79002310021356047142575775154740548981748412961642e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 42))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.44750577503651834833347404492486283164453776697661e-13), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 44))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.61876443758020639017543150875739203546579850550506e-14), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 46))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.04691109394324465958560412889011979187196424398413e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.26172777348533543325299108739056247374472601114618e-15), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 50))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.65431943371302795435372191153510741742082062236667e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 52))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.41357985842823674325840669958475387008031322630868e-16), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 54))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.53394964607057868542015717421467433254478008250729e-17), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.83487411517643815597510900540151314745726776276537e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 58))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.20871852879410898385647064972035961074675685323943e-18), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 60))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.52179632198527209999982790078399565586115610945978e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 62))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38044908049631800172983942388255378445601347506470e-19), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.45112270124079498928544180507695627740193986743475e-20), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 68))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15695168827549686524997208584894563633442321098092e-21), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 72))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.34809480517218554065439979557746061380338130338956e-22), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 76))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.42559253232615962903750225978472507493251963237152e-24), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.26599533270384976814627294052855716278192786930198e-25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 84))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.29124708293990610509133147452548575130220036516594e-26), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 88))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.05702942683744131568207851461222366485608388136168e-27), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 92))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.28564339177340082230129892190826718627845694793237e-28), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.03527119858375513938311820075537974687844953537787e-30), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 100))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.02204449911484696211444887297771791655738720297691e-31), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 104))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.13877781194677935132153054550953911471083914854259e-32), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 108))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.96173613246673709457595659093933570122399892106597e-33), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.22608508279171068410997286933691737981629848926873e-34), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 116))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.66303176744819177568733043335566577797931906017599e-36), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 120))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.78939485465511985980458152084728836560995745045025e-37), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 124))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.99337178415944991237786345052955511752869068868957e-38), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87085736509965619523616465658097194397480643905015e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.87085736509965619523616465658097194397480643905015e-39), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 136))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.30803658242053201264126818976942165494933536744296e-42), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 144))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.85470179000802031743799538662868033396263440343802e-44), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 152))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.11511788672188293649921694790182825545415091296783e-46), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.35592924500735522070006620274151662286777695301906e-49), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 168))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70153486133099813308596336044590493080772537219152e-51), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 176))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.64662055207421145736704437674181613596767723512183e-54), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 184))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.59633615315398885053400170966477192811237391996946e-56), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.01419380982577689473984441783780153441889606248807e-58), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 200))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.96169456963194099507751725717891224382381274409403e-61), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 208))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.54753694126247695120215517858551259524367685316173e-63), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 216))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.04506617680655059063341866634965857517061270766301e-66), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.36135397531505882446617916654283538092602058893086e-68), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 232))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.22403896607444853307101236930795070674226792551118e-71), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 240))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.60314022112283145823086420676091824482119840840280e-73), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 248))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.40747664887610603837143133076598368938328062828235e-75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(complement(dist, ldexp(static_cast<RealType>(1), 256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.49795565967228921238840363580462378665343995422791e-78), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_quantile_nearzero() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.03125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.37666142124664870427736212608782014348092232942703e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.0625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.16727296241754547290632950718657110865371011883488e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.09375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.01093317611810417245689707499918702758654056685650e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.77109518013577849065583862782160134594408514905936e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.15625)), BOOST_MATH_BIG_CONSTANT(RealType, N, -7.55147864363163697663604936395052484592948168261254e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.1875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.39830737061008092918841929339491480637487863539219e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.21875)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.28068260002115642528019835718799250663117082682413e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.25)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.17764764050720242897742634974454174978089714315837e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.28125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.07332710058680816601395586920882835843791948709923e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.3125)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.95448171270527198765810574858446724358448730774699e-1), tolerance);
+
+    // Relative error decreases near the root.
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.34375)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.09096582988749397639311472333288802663134525410086e-2), tolerance * 10);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.74557416577759248536854968412795127813716796439183e-2), tolerance * 10);
+
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.40625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.60865269786540938863996714417993425933643390360701e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.4375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.90647080532071673100911236876323489196027799942628e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.46875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.28310640852292004320545764804480585932279888826464e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.75630143945078214396279308922575172688187402052064e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.53125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.34751649957416497391423738312790099231331963193670e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.5625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.08338732735341567163440035550389980881822036530441e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.59375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.09977916217503813825408682237719484284367467701518e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31348919222343858173602105619413807214737739605647e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.65625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55537778016228176635489075791437025790508273018206e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.6875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.83358201486120130332744845371832465533289389791770e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.71875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15968268411007811908706240304578653239207877720217e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.55081568282045925871949387822806899205587760602861e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.78125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03356573722052416577951184486453626014326770622663e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.8125)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.65170109428623528831428068089551728119930570543517e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.84375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48307637103506875745328267812359172615004959210209e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68160868054034088524891526884683024288168516466432e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.90625)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.60235856635301171960591513042024596858455255485505e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.9375)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12983583770683756688253603663598582344177172936943e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, static_cast<RealType>(0.96875)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19714287107110229779819680655029619622254635434578e1), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_quantile_lower() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3)), BOOST_MATH_BIG_CONSTANT(RealType, N, -8.77109518013577849065583862782160134594408514905936e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.16727296241754547290632950718657110865371011883488e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.37666142124664870427736212608782014348092232942703e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.53937945687640569563878953898367418895418286968892e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.67193057806636817209385515556513905369159305215132e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.78348038398799867332294266481364804262899249535026e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10)), BOOST_MATH_BIG_CONSTANT(RealType, N, -1.96398712546539547900868300204740158406402253850740e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.10672834330580928387396530276881975373360375562766e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.22455234225296140347183338705883529117630663916504e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -16)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.32474749499506228416012679106564721359216355271060e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -20)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.48880222197195858123676152921728490355916489072920e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -24)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.62012266244208104039475013076613716084830146896364e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -28)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.72950770317262402197221324973838006547359087175177e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -32)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.82318656228158372073367735499500997206084370651970e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -40)), BOOST_MATH_BIG_CONSTANT(RealType, N, -2.97778747939490003780916437343292886429806927997697e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -48)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.10253941103391799610961378724535481625827036745191e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -56)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.20706965504048009454149883353144814083641366738928e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -64)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.29700011190686230364493911161520662289614047608888e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -80)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.44616534249558131319374859709618689440842790052762e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -96)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.56714397893479094507321490741760621098238204564655e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -112)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.66888826418737343076580628480419340009764391741662e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -128)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.75666995985336007747791649448887717847452667971341e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -160)), BOOST_MATH_BIG_CONSTANT(RealType, N, -3.90272386559500090814947503869007637264448398505091e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.02154690255519314578158695811138813197102888432118e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -224)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.12170243205222902851790251956181678240666087312573e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -256)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.20826069989721596260510558511263030379850705902299e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -320)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.35254674338923723387138280464388000015841039600555e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -384)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.47014796872616976009165833857464389146621180677518e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -448)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.56940486432189047495132801898571896454756873328884e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -512)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.65527239540648657446629479052874024150007745617425e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -640)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.79856256497052731627737920479094219620428520302497e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -768)), BOOST_MATH_BIG_CONSTANT(RealType, N, -4.91547732272180866354170476973276286391282782030491e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -896)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.01423042502756027207185677104980034013809957436307e0), tolerance);
+
+    // The test is terminated because p = 0 after this in fp64.
+    if(N <= 53){
+        return;
+    }
+
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1024)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.09971143249822249471944441552701750744803726485204e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1280)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.24244558247619917128857214117595378487244291900164e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1536)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.35897805692044314674029465486888992071638929853610e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -1792)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.45745119510512195777968048015384189694395480185084e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -2048)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.54271778755494231572464179212263712867955955556373e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -2560)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.68514415447058604503373799640504720298538164608415e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3072)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.80146552760710346457341432134646648154958472048223e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -3584)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.89978436824284434538360953970051552537044157804319e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -4096)), BOOST_MATH_BIG_CONSTANT(RealType, N, -5.98493298246627952401490656857159297529934857258768e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -5120)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.12719032649420608124001447392893816734788637468278e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -6144)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.24339602515596353391422898038238569270302761832424e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -7168)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.34163046670299704746360546090336718985578875063595e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -8192)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.42671464308364892089984144203590287404801291341155e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -10240)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.56887983067842563164669431493815471028291272019257e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -12288)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.68502258391108555173104319503169367212234002338911e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(dist, ldexp(static_cast<RealType>(1), -14336)), BOOST_MATH_BIG_CONSTANT(RealType, N, -6.78321117119788305968192558554365316820805283962570e0), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_quantile_upper() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist(static_cast<RealType>(0), static_cast<RealType>(1));
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.75630143945078214396279308922575172688187402052064e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.46875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.34751649957416497391423738312790099231331963193670e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.4375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.08338732735341567163440035550389980881822036530441e-1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.40625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.09977916217503813825408682237719484284367467701518e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.31348919222343858173602105619413807214737739605647e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.34375))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.55537778016228176635489075791437025790508273018206e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.3125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.83358201486120130332744845371832465533289389791770e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.28125))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.15968268411007811908706240304578653239207877720217e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.55081568282045925871949387822806899205587760602861e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.21875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.03356573722052416577951184486453626014326770622663e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.1875))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.65170109428623528831428068089551728119930570543517e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, static_cast<RealType>(0.15625))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.48307637103506875745328267812359172615004959210209e0), tolerance);
+
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -3))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.68160868054034088524891526884683024288168516466432e0), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -4))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.12983583770683756688253603663598582344177172936943e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -5))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.19714287107110229779819680655029619622254635434578e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -6))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.28089946846201448479186405990829330152038273940336e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -7))), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.40066013407733304728124190173163568113870838023174e1), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -8))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.65941656579816517264930679482280545790703168918131e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -10))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.55753077855274500558851746639632584040672341383365e2), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -12))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.61233279175261252785344820794971528959731572291875e3), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -14))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04359994051668217545134727183452999841836322543240e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -16))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.17280170760481128545941744972976378785527707571987e4), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -20))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.67552483213163052181906697701099131817014739251016e5), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -24))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06807174647511043368265795578221114430723661526053e7), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -28))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.70891330693062153503879914631960898643362032945242e8), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -32))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.73426111586976542228936210986127280848086481329720e9), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -40))), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.99970842207360156603062974124919047698394307869345e11), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -48))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.79192535600728707050158319385235151176991681631485e14), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -56))), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.58732891137812933185516807516215074813520642490265e16), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -64))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.17435620131280049336696928005840807489266101470318e19), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -80))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.69626080092356929518666088104130567689669972090860e23), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -96))), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.04382147849327037329330237397632338076523897478536e28), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -112))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.30551884414534967184149864106941373195910184715021e33), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -128))), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.16630482969909636093804454941121895928783047320959e38), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -160))), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.30420839672446839098151322191224148323438073311282e47), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -192))), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.99612707791001852622513406287046677525461975485236e57), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -224))), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.71632351102835736008910691332442626839731739200064e67), tolerance);
+    BOOST_CHECK_CLOSE(quantile(complement(dist, ldexp(static_cast<RealType>(1), -256))), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.37155334922269019018360983857591746072979653277477e76), tolerance);
+}
+
+template<class RealType, int N>
+void do_test_landau_locscale_param() {
+    //
+    // Basic sanity checks, tolerance is either 3 epsilon
+    // expressed as a percentage:
+    //
+
+    BOOST_MATH_STD_USING
+    RealType tolerance = boost::math::tools::epsilon<RealType>() * 100 * 3;
+
+    std::cout << "Testing acurracy[%]: " << tolerance << std::endl;
+
+    landau_distribution<RealType> dist_0_1(static_cast<RealType>(0), static_cast<RealType>(1));
+    landau_distribution<RealType> dist_1_3(static_cast<RealType>(1), static_cast<RealType>(3));
+    landau_distribution<RealType> dist_0_pihalf(static_cast<RealType>(0), boost::math::constants::pi<RealType>() / 2);
+
+    BOOST_CHECK_CLOSE(entropy(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.3726364400044818244844049010588577710), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_1_3), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.3726364400044818244844049010588577710) + log(static_cast<RealType>(3)), tolerance);
+    BOOST_CHECK_CLOSE(entropy(dist_0_pihalf), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.8242191452939366892106001309537399145), tolerance);
+
+    BOOST_CHECK_CLOSE(median(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.57563014394507821439627930892257517269), tolerance);
+    BOOST_CHECK_CLOSE(
+        median(dist_1_3),
+        (1 + 3 * (BOOST_MATH_BIG_CONSTANT(RealType, N, 0.57563014394507821439627930892257517269) + 2 / boost::math::constants::pi<RealType>() * log(static_cast<RealType>(3)))),
+        tolerance
+    );
+    BOOST_CHECK_CLOSE(median(dist_0_pihalf), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.3557804209908013250320928093906509105), tolerance);
+
+    BOOST_CHECK_CLOSE(mode(dist_0_1), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.42931452986133525016556463510885028346), tolerance);
+    BOOST_CHECK_CLOSE(
+        mode(dist_1_3),
+        (1 + 3 * (BOOST_MATH_BIG_CONSTANT(RealType, N, -0.42931452986133525016556463510885028346) + 2 / boost::math::constants::pi<RealType>() * log(static_cast<RealType>(3)))),
+        tolerance
+    );
+    BOOST_CHECK_CLOSE(mode(dist_0_pihalf), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.222782981256408504061824283124805665631673572953417648794046), tolerance);
+
+    BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.16353124086802260347581305180210465276342), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.09034495984298569669047391552324642172044), tolerance);
+    BOOST_CHECK_CLOSE(pdf(dist_0_pihalf, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.14520663709640194253543670745173917702186), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.57786675964195234763672948547568695034661), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.17119311431882309272302517476020685228892), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_pihalf, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.45101809281952585982591839302215356640746), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_pihalf, quantile(dist_0_pihalf, static_cast<RealType>(0.25))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.25), tolerance);
+
+    BOOST_CHECK_CLOSE(cdf(dist_0_1, quantile(dist_0_1, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_1_3, quantile(dist_1_3, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+    BOOST_CHECK_CLOSE(cdf(dist_0_pihalf, quantile(dist_0_pihalf, static_cast<RealType>(0.75))), BOOST_MATH_BIG_CONSTANT(RealType, N, 0.75), tolerance);
+}
+
+BOOST_AUTO_TEST_CASE(landau_pdf_fp64)
+{
+    do_test_landau_pdf<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_pdf_fp64_std)
+{
+    do_test_landau_pdf<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_pdf_fp128)
+{
+    do_test_landau_pdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_cdf_fp64)
+{
+    do_test_landau_cdf<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_cdf_fp64_std)
+{
+    do_test_landau_cdf<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_cdf_fp128)
+{
+    do_test_landau_cdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_ccdf_fp64)
+{
+    do_test_landau_ccdf<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_ccdf_fp64_std)
+{
+    do_test_landau_ccdf<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_ccdf_fp128)
+{
+    do_test_landau_ccdf<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp64)
+{
+    do_test_landau_quantile_nearzero<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp64_std)
+{
+    do_test_landau_quantile_nearzero<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp128)
+{
+    do_test_landau_quantile_nearzero<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp64)
+{
+    do_test_landau_quantile_lower<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp64_std)
+{
+    do_test_landau_quantile_lower<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp128)
+{
+    do_test_landau_quantile_lower<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp64)
+{
+    do_test_landau_quantile_upper<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp64_std)
+{
+    do_test_landau_quantile_upper<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp128)
+{
+    do_test_landau_quantile_upper<cpp_bin_float_quad, 113>();
+}
+
+BOOST_AUTO_TEST_CASE(landau_locscale_fp64)
+{
+    do_test_landau_locscale_param<double, 53>();
+}
+
+#ifdef __STDCPP_FLOAT64_T__
+BOOST_AUTO_TEST_CASE(landau_locscale_fp64_std)
+{
+    do_test_landau_locscale_param<std::float64_t, 53>();
+}
+#endif
+
+BOOST_AUTO_TEST_CASE(landau_locscale_fp128)
+{
+    do_test_landau_locscale_param<cpp_bin_float_quad, 113>();
+}
+

From d3f7123186e8c1365aa2a4a0db1c2bf2542f2889 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Mon, 22 Jul 2024 10:32:54 +0900
Subject: [PATCH 015/399] Fix: saspoint5 document about accuracy

---
 doc/distributions/saspoint5.qbk | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/doc/distributions/saspoint5.qbk b/doc/distributions/saspoint5.qbk
index ff977b378d..a5b818eb9a 100644
--- a/doc/distributions/saspoint5.qbk
+++ b/doc/distributions/saspoint5.qbk
@@ -85,7 +85,8 @@ The domain of the random variable is \[-[max_value], +[min_value]\].
 
 [h4 Accuracy]
 
-The error is within 4 epsilon.
+For float64, the error is within 4 epsilons.
+For float128, the error is within 4 epsilons except the peak.
 
 [h4 Implementation]
 

From b5ded3deb58128dc49c7fe28e748292bf292e894 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 09:17:17 -0400
Subject: [PATCH 016/399] Replace BOOST_MATH_CHECK_THROW with boost.test

---
 test/test_binomial.cpp     | 23 +++++-----
 test/test_out_of_range.hpp | 88 +++++++++++++++++++-------------------
 2 files changed, 55 insertions(+), 56 deletions(-)

diff --git a/test/test_binomial.cpp b/test/test_binomial.cpp
index 8aec49e4f8..ef7f171723 100644
--- a/test/test_binomial.cpp
+++ b/test/test_binomial.cpp
@@ -27,7 +27,6 @@
 // Enable C++ Exceptions Yes With SEH Exceptions (/EHa) prevents warning 4535.
 #endif
 
-#include <boost/math/tools/test.hpp>
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
 
@@ -522,57 +521,57 @@ void test_spots(RealType T)
           binomial_distribution<RealType>(static_cast<RealType>(0), static_cast<RealType>(0.25)),
           static_cast<RealType>(0)), static_cast<RealType>(1)
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        pdf(
           binomial_distribution<RealType>(static_cast<RealType>(-1), static_cast<RealType>(0.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        pdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(-0.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        pdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(1.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        pdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(0.25)),
           static_cast<RealType>(-1)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        pdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(0.25)),
           static_cast<RealType>(9)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        cdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(0.25)),
           static_cast<RealType>(-1)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        cdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(0.25)),
           static_cast<RealType>(9)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        cdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(-0.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        cdf(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(1.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        quantile(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(-0.25)),
           static_cast<RealType>(0)), std::domain_error
        );
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
        quantile(
           binomial_distribution<RealType>(static_cast<RealType>(8), static_cast<RealType>(1.25)),
           static_cast<RealType>(0)), std::domain_error
diff --git a/test/test_out_of_range.hpp b/test/test_out_of_range.hpp
index a8c93576f4..bed4e48a0f 100644
--- a/test/test_out_of_range.hpp
+++ b/test/test_out_of_range.hpp
@@ -9,7 +9,7 @@
 #define BOOST_MATH_TEST_OUT_OF_RANGE_HPP
 
 #include <boost/math/special_functions/next.hpp>
-#include <boost/test/test_tools.hpp>
+#include <boost/test/unit_test.hpp>
 
 /*` check_out_of_range functions check that bad parameters
 passed to constructors and functions throw domain_error exceptions.
@@ -48,60 +48,60 @@ void check_support(const Distro& d, bool Infinite = false)
        value_type m = (range(d).first == 0) ? -boost::math::tools::min_value<value_type>() : boost::math::float_prior(range(d).first);
        BOOST_MATH_ASSERT(m != range(d).first);
        BOOST_MATH_ASSERT(m < range(d).first);
-       BOOST_MATH_CHECK_THROW(pdf(d, m), std::domain_error);
-       BOOST_MATH_CHECK_THROW(cdf(d, m), std::domain_error);
-       BOOST_MATH_CHECK_THROW(cdf(complement(d, m)), std::domain_error);
+       BOOST_CHECK_THROW(pdf(d, m), std::domain_error);
+       BOOST_CHECK_THROW(cdf(d, m), std::domain_error);
+       BOOST_CHECK_THROW(cdf(complement(d, m)), std::domain_error);
      }
      if ((boost::math::isfinite)(range(d).second) && (range(d).second != boost::math::tools::max_value<value_type>()))
      { // If possible, check that a random variable value just more than the top of the supported range throws domain errors.
        value_type m = (range(d).second == 0) ? boost::math::tools::min_value<value_type>() : boost::math::float_next(range(d).second);
        BOOST_MATH_ASSERT(m != range(d).first);
        BOOST_MATH_ASSERT(m > range(d).first);
-       BOOST_MATH_CHECK_THROW(pdf(d, m), std::domain_error);
-       BOOST_MATH_CHECK_THROW(cdf(d, m), std::domain_error);
-       BOOST_MATH_CHECK_THROW(cdf(complement(d, m)), std::domain_error);
+       BOOST_CHECK_THROW(pdf(d, m), std::domain_error);
+       BOOST_CHECK_THROW(cdf(d, m), std::domain_error);
+       BOOST_CHECK_THROW(cdf(complement(d, m)), std::domain_error);
      }
      if (std::numeric_limits<value_type>::has_infinity)
      { // Infinity is available,
        if ((boost::math::isfinite)(range(d).second))
        {  // and top of range doesn't include infinity,
           // check that using infinity throws domain errors.
-         BOOST_MATH_CHECK_THROW(pdf(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
-         BOOST_MATH_CHECK_THROW(cdf(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
-         BOOST_MATH_CHECK_THROW(cdf(complement(d, std::numeric_limits<value_type>::infinity())), std::domain_error);
+         BOOST_CHECK_THROW(pdf(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
+         BOOST_CHECK_THROW(cdf(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
+         BOOST_CHECK_THROW(cdf(complement(d, std::numeric_limits<value_type>::infinity())), std::domain_error);
        }
        if ((boost::math::isfinite)(range(d).first))
        {  // and bottom of range doesn't include infinity,
           // check that using infinity throws domain_error exception.
-         BOOST_MATH_CHECK_THROW(pdf(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
-         BOOST_MATH_CHECK_THROW(cdf(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
-         BOOST_MATH_CHECK_THROW(cdf(complement(d, -std::numeric_limits<value_type>::infinity())), std::domain_error);
+         BOOST_CHECK_THROW(pdf(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
+         BOOST_CHECK_THROW(cdf(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
+         BOOST_CHECK_THROW(cdf(complement(d, -std::numeric_limits<value_type>::infinity())), std::domain_error);
        }
        // Check that using infinity with quantiles always throws domain_error exception.
-       BOOST_MATH_CHECK_THROW(quantile(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
-       BOOST_MATH_CHECK_THROW(quantile(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
-       BOOST_MATH_CHECK_THROW(quantile(complement(d, std::numeric_limits<value_type>::infinity())), std::domain_error);
-       BOOST_MATH_CHECK_THROW(quantile(complement(d, -std::numeric_limits<value_type>::infinity())), std::domain_error);
+       BOOST_CHECK_THROW(quantile(d, std::numeric_limits<value_type>::infinity()), std::domain_error);
+       BOOST_CHECK_THROW(quantile(d, -std::numeric_limits<value_type>::infinity()), std::domain_error);
+       BOOST_CHECK_THROW(quantile(complement(d, std::numeric_limits<value_type>::infinity())), std::domain_error);
+       BOOST_CHECK_THROW(quantile(complement(d, -std::numeric_limits<value_type>::infinity())), std::domain_error);
      }
    }
    if(std::numeric_limits<value_type>::has_quiet_NaN)
    { // NaN is available.
-      BOOST_MATH_CHECK_THROW(pdf(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(cdf(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(cdf(complement(d, std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(cdf(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(cdf(complement(d, -std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
-      BOOST_MATH_CHECK_THROW(quantile(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(quantile(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
-      BOOST_MATH_CHECK_THROW(quantile(complement(d, std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
-      BOOST_MATH_CHECK_THROW(quantile(complement(d, -std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
+      BOOST_CHECK_THROW(pdf(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(cdf(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(cdf(complement(d, std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
+      BOOST_CHECK_THROW(pdf(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(cdf(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(cdf(complement(d, -std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
+      BOOST_CHECK_THROW(quantile(d, std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(quantile(d, -std::numeric_limits<value_type>::quiet_NaN()), std::domain_error);
+      BOOST_CHECK_THROW(quantile(complement(d, std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
+      BOOST_CHECK_THROW(quantile(complement(d, -std::numeric_limits<value_type>::quiet_NaN())), std::domain_error);
    }
    // Check that using probability outside [0,1] with quantiles always throws domain_error exception.
-   BOOST_MATH_CHECK_THROW(quantile(d, -1), std::domain_error);
-   BOOST_MATH_CHECK_THROW(quantile(d, 2), std::domain_error);
-   BOOST_MATH_CHECK_THROW(quantile(complement(d, -1)), std::domain_error);
-   BOOST_MATH_CHECK_THROW(quantile(complement(d, 2)), std::domain_error);
+   BOOST_CHECK_THROW(quantile(d, -1), std::domain_error);
+   BOOST_CHECK_THROW(quantile(d, 2), std::domain_error);
+   BOOST_CHECK_THROW(quantile(complement(d, -1)), std::domain_error);
+   BOOST_CHECK_THROW(quantile(complement(d, 2)), std::domain_error);
 }
 
 // Four check_out_of_range versions for distributions with zero to 3 constructor parameters.
@@ -121,12 +121,12 @@ void check_out_of_range(typename Distro::value_type p1)
    check_support(d);
    if(std::numeric_limits<value_type>::has_infinity)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
- //     BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity()), range(d).second), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
+ //     BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity()), range(d).second), std::domain_error);
    }
    if(std::numeric_limits<value_type>::has_quiet_NaN)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
    }
 }
 
@@ -138,13 +138,13 @@ void check_out_of_range(typename Distro::value_type p1, typename Distro::value_t
    check_support(d);
    if(std::numeric_limits<value_type>::has_infinity)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity(), p2), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity(), p2), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
    }
    if(std::numeric_limits<value_type>::has_quiet_NaN)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN(), p2), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN(), p2), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
    }
 }
 
@@ -156,15 +156,15 @@ void check_out_of_range(typename Distro::value_type p1, typename Distro::value_t
    check_support(d);
    if(std::numeric_limits<value_type>::has_infinity)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity(), p2, p3), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::infinity(), p3), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, p2, std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::infinity(), p2, p3), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::infinity(), p3), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, p2, std::numeric_limits<value_type>::infinity()), range(d).first), std::domain_error);
    }
    if(std::numeric_limits<value_type>::has_quiet_NaN)
    {
-      BOOST_MATH_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN(), p2, p3), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::quiet_NaN(), p3), range(d).first), std::domain_error);
-      BOOST_MATH_CHECK_THROW(pdf(Distro(p1, p2, std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(std::numeric_limits<value_type>::quiet_NaN(), p2, p3), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, std::numeric_limits<value_type>::quiet_NaN(), p3), range(d).first), std::domain_error);
+      BOOST_CHECK_THROW(pdf(Distro(p1, p2, std::numeric_limits<value_type>::quiet_NaN()), range(d).first), std::domain_error);
    }
 }
 

From 2a16fe3557ef4f95e014c7019d9161be1fae247e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 10:07:39 -0400
Subject: [PATCH 017/399] Add additional configuration macros

---
 include/boost/math/tools/config.hpp | 25 +++++++++++++++++++++++++
 1 file changed, 25 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index e2d54a2d3e..b75a5fec54 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -662,6 +662,31 @@ namespace boost{ namespace math{
 #define BOOST_MATH_CONSTEXPR_TABLE_FUNCTION
 #endif
 
+//
+// CUDA support:
+//
+
+#ifdef __NVCC__
+#  define BOOST_MATH_HOST_DEVICE __host__ __device__
+#  ifndef BOOST_MATH_ENABLE_CUDA
+#    define BOOST_MATH_ENABLE_CUDA
+#  endif
+#else
+#  define BOOST_MATH_HOST_DEVICE
+#endif
+
+// Static variables are not allowed with CUDA or C++20 modules
+// See if we can inline them instead
+
+#if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
+#  define BOOST_MATH_STATIC_CONSTEXPR inline constexpr
+#else
+#  ifndef BOOST_MATH_ENABLE_CUDA
+#    define BOOST_MATH_STATIC_CONSTEXPR static constexpr
+#  else
+#    define BOOST_MATH_STATIC_CONSTEXPR constexpr
+#  endif
+#endif
 
 #endif // BOOST_MATH_TOOLS_CONFIG_HPP
 

From d04988c907d9fa85661dad86640f2e27ab8a6ea5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 10:18:46 -0400
Subject: [PATCH 018/399] Add additional macro for local static variables

---
 include/boost/math/tools/config.hpp | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index b75a5fec54..81593a69cb 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -680,11 +680,14 @@ namespace boost{ namespace math{
 
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_STATIC_CONSTEXPR inline constexpr
+#  define BOOST_MATH_STATIC static
 #else
 #  ifndef BOOST_MATH_ENABLE_CUDA
 #    define BOOST_MATH_STATIC_CONSTEXPR static constexpr
+#    define BOOST_MATH_STATIC static
 #  else
 #    define BOOST_MATH_STATIC_CONSTEXPR constexpr
+#    define BOOST_MATH_STATIC constexpr
 #  endif
 #endif
 

From 964d4943cd76eac87b24e4a79ea84dd610beb206 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 10:20:39 -0400
Subject: [PATCH 019/399] Add CUDA markers to binomial dist

---
 include/boost/math/distributions/binomial.hpp | 63 ++++++++++---------
 1 file changed, 32 insertions(+), 31 deletions(-)

diff --git a/include/boost/math/distributions/binomial.hpp b/include/boost/math/distributions/binomial.hpp
index cf7451104b..9a2bc73b1d 100644
--- a/include/boost/math/distributions/binomial.hpp
+++ b/include/boost/math/distributions/binomial.hpp
@@ -79,6 +79,7 @@
 #ifndef BOOST_MATH_SPECIAL_BINOMIAL_HPP
 #define BOOST_MATH_SPECIAL_BINOMIAL_HPP
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for incomplete beta.
 #include <boost/math/distributions/complement.hpp> // complements
@@ -100,7 +101,7 @@ namespace boost
      namespace binomial_detail{
         // common error checking routines for binomial distribution functions:
         template <class RealType, class Policy>
-        inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
+        BOOST_MATH_HOST_DEVICE inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
         {
            if((N < 0) || !(boost::math::isfinite)(N))
            {
@@ -112,7 +113,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_HOST_DEVICE inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
         {
            if((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
            {
@@ -124,7 +125,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_HOST_DEVICE inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
         {
            return check_success_fraction(
               function, p, result, pol)
@@ -132,7 +133,7 @@ namespace boost
                function, N, result, pol);
         }
         template <class RealType, class Policy>
-        inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
+        BOOST_MATH_HOST_DEVICE inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
         {
            if(check_dist(function, N, p, result, pol) == false)
               return false;
@@ -153,7 +154,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
+        BOOST_MATH_HOST_DEVICE inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
         {
            if((check_dist(function, N, p, result, pol) && detail::check_probability(function, prob, result, pol)) == false)
               return false;
@@ -161,7 +162,7 @@ namespace boost
         }
 
          template <class T, class Policy>
-         T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
+         BOOST_MATH_HOST_DEVICE T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
          {
             BOOST_MATH_STD_USING
             // mean:
@@ -196,7 +197,7 @@ namespace boost
          }
 
       template <class RealType, class Policy>
-      RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
+      BOOST_MATH_HOST_DEVICE RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
       { // Quantile or Percent Point Binomial function.
         // Return the number of expected successes k,
         // for a given probability p.
@@ -290,11 +291,11 @@ namespace boost
             &r, Policy());
       } // binomial_distribution constructor.
 
-      RealType success_fraction() const
+      BOOST_MATH_HOST_DEVICE RealType success_fraction() const
       { // Probability.
         return m_p;
       }
-      RealType trials() const
+      BOOST_MATH_HOST_DEVICE RealType trials() const
       { // Total number of trials.
         return m_n;
       }
@@ -310,13 +311,13 @@ namespace boost
       // these functions are used
       // to obtain confidence intervals for the success fraction.
       //
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_HOST_DEVICE static RealType find_lower_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
          interval_type t = clopper_pearson_exact_interval)
       {
-        static const char* function = "boost::math::binomial_distribution<%1%>::find_lower_bound_on_p";
+        BOOST_MATH_STATIC const char* function = "boost::math::binomial_distribution<%1%>::find_lower_bound_on_p";
         // Error checks:
         RealType result = 0;
         if(false == binomial_detail::check_dist_and_k(
@@ -335,13 +336,13 @@ namespace boost
         return (t == clopper_pearson_exact_interval) ? ibeta_inv(successes, trials - successes + 1, probability, static_cast<RealType*>(nullptr), Policy())
            : ibeta_inv(successes + 0.5f, trials - successes + 0.5f, probability, static_cast<RealType*>(nullptr), Policy());
       }
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_HOST_DEVICE static RealType find_upper_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
          interval_type t = clopper_pearson_exact_interval)
       {
-        static const char* function = "boost::math::binomial_distribution<%1%>::find_upper_bound_on_p";
+        BOOST_MATH_STATIC const char* function = "boost::math::binomial_distribution<%1%>::find_upper_bound_on_p";
         // Error checks:
         RealType result = 0;
         if(false == binomial_detail::check_dist_and_k(
@@ -363,12 +364,12 @@ namespace boost
       //    or
       // "How many trials can I have to be P% sure of seeing fewer than k events?"
       //
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_HOST_DEVICE static RealType find_minimum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
       {
-        static const char* function = "boost::math::binomial_distribution<%1%>::find_minimum_number_of_trials";
+        BOOST_MATH_STATIC const char* function = "boost::math::binomial_distribution<%1%>::find_minimum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == binomial_detail::check_dist_and_k(
@@ -382,12 +383,12 @@ namespace boost
         return result + k;
       }
 
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_HOST_DEVICE static RealType find_maximum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
       {
-        static const char* function = "boost::math::binomial_distribution<%1%>::find_maximum_number_of_trials";
+        BOOST_MATH_STATIC const char* function = "boost::math::binomial_distribution<%1%>::find_maximum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == binomial_detail::check_dist_and_k(
@@ -419,33 +420,33 @@ namespace boost
       #endif
 
       template <class RealType, class Policy>
-      const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
       { // Range of permissible values for random variable k.
         using boost::math::tools::max_value;
         return std::pair<RealType, RealType>(static_cast<RealType>(0), dist.trials());
       }
 
       template <class RealType, class Policy>
-      const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
       { // Range of supported values for random variable k.
         // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
         return std::pair<RealType, RealType>(static_cast<RealType>(0),  dist.trials());
       }
 
       template <class RealType, class Policy>
-      inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
       { // Mean of Binomial distribution = np.
         return  dist.trials() * dist.success_fraction();
       } // mean
 
       template <class RealType, class Policy>
-      inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
       { // Variance of Binomial distribution = np(1-p).
         return  dist.trials() * dist.success_fraction() * (1 - dist.success_fraction());
       } // variance
 
       template <class RealType, class Policy>
-      RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_HOST_DEVICE RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Probability Density/Mass Function.
         BOOST_FPU_EXCEPTION_GUARD
 
@@ -501,7 +502,7 @@ namespace boost
       } // pdf
 
       template <class RealType, class Policy>
-      inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_HOST_DEVICE inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -573,7 +574,7 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_HOST_DEVICE inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -650,19 +651,19 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_HOST_DEVICE inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
       {
          return binomial_detail::quantile_imp(dist, p, RealType(1-p), false);
       } // quantile
 
       template <class RealType, class Policy>
-      RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_HOST_DEVICE RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       {
          return binomial_detail::quantile_imp(c.dist, RealType(1-c.param), c.param, true);
       } // quantile
 
       template <class RealType, class Policy>
-      inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -671,7 +672,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType median(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType median(const binomial_distribution<RealType, Policy>& dist)
       { // Bounds for the median of the negative binomial distribution
         // VAN DE VEN R. ; WEBER N. C. ;
         // Univ. Sydney, school mathematics statistics, Sydney N.S.W. 2006, AUSTRALIE
@@ -689,7 +690,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -698,7 +699,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType n = dist.trials();
@@ -706,7 +707,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_HOST_DEVICE inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType q = 1 - p;

From b42048cf02ceb8a7ff795f132d14ded677a7e6b3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 10:38:52 -0400
Subject: [PATCH 020/399] Add CUDA markers to polynomial class

---
 include/boost/math/tools/polynomial.hpp | 182 ++++++++++++------------
 1 file changed, 91 insertions(+), 91 deletions(-)

diff --git a/include/boost/math/tools/polynomial.hpp b/include/boost/math/tools/polynomial.hpp
index 6f9b9039fd..8d87fbf68c 100644
--- a/include/boost/math/tools/polynomial.hpp
+++ b/include/boost/math/tools/polynomial.hpp
@@ -32,7 +32,7 @@
 namespace boost{ namespace math{ namespace tools{
 
 template <class T>
-T chebyshev_coefficient(unsigned n, unsigned m)
+BOOST_MATH_HOST_DEVICE T chebyshev_coefficient(unsigned n, unsigned m)
 {
    BOOST_MATH_STD_USING
    if(m > n)
@@ -56,7 +56,7 @@ T chebyshev_coefficient(unsigned n, unsigned m)
 }
 
 template <class Seq>
-Seq polynomial_to_chebyshev(const Seq& s)
+BOOST_MATH_HOST_DEVICE Seq polynomial_to_chebyshev(const Seq& s)
 {
    // Converts a Polynomial into Chebyshev form:
    typedef typename Seq::value_type value_type;
@@ -92,7 +92,7 @@ Seq polynomial_to_chebyshev(const Seq& s)
 }
 
 template <class Seq, class T>
-T evaluate_chebyshev(const Seq& a, const T& x)
+BOOST_MATH_HOST_DEVICE T evaluate_chebyshev(const Seq& a, const T& x)
 {
    // Clenshaw's formula:
    typedef typename Seq::difference_type difference_type;
@@ -124,7 +124,7 @@ namespace detail {
 * subtlety of distinction.
 */
 template <typename T, typename N>
-typename std::enable_if<!std::numeric_limits<T>::is_integer, void >::type
+BOOST_MATH_HOST_DEVICE typename std::enable_if<!std::numeric_limits<T>::is_integer, void >::type
 division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N k)
 {
     q[k] = u[n + k] / v[n];
@@ -136,7 +136,7 @@ division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N
 }
 
 template <class T, class N>
-T integer_power(T t, N n)
+BOOST_MATH_HOST_DEVICE T integer_power(T t, N n)
 {
    switch(n)
    {
@@ -167,7 +167,7 @@ T integer_power(T t, N n)
 * don't currently have that subtlety of distinction.
 */
 template <typename T, typename N>
-typename std::enable_if<std::numeric_limits<T>::is_integer, void >::type
+BOOST_MATH_HOST_DEVICE typename std::enable_if<std::numeric_limits<T>::is_integer, void >::type
 division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N k)
 {
     q[k] = u[n + k] * integer_power(v[n], k);
@@ -187,7 +187,7 @@ division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N
  * @param   v   Divisor.
  */
 template <typename T>
-std::pair< polynomial<T>, polynomial<T> >
+BOOST_MATH_HOST_DEVICE std::pair< polynomial<T>, polynomial<T> >
 division(polynomial<T> u, const polynomial<T>& v)
 {
     BOOST_MATH_ASSERT(v.size() <= u.size());
@@ -218,7 +218,7 @@ division(polynomial<T> u, const polynomial<T>& v)
 struct negate
 {
    template <class T>
-   T operator()(T const &x) const
+   BOOST_MATH_HOST_DEVICE T operator()(T const &x) const
    {
       return -x;
    }
@@ -227,7 +227,7 @@ struct negate
 struct plus
 {
    template <class T, class U>
-   T operator()(T const &x, U const& y) const
+   BOOST_MATH_HOST_DEVICE T operator()(T const &x, U const& y) const
    {
       return x + y;
    }
@@ -236,7 +236,7 @@ struct plus
 struct minus
 {
    template <class T, class U>
-   T operator()(T const &x, U const& y) const
+   BOOST_MATH_HOST_DEVICE T operator()(T const &x, U const& y) const
    {
       return x - y;
    }
@@ -248,13 +248,13 @@ struct minus
  * Returns the zero element for multiplication of polynomials.
  */
 template <class T>
-polynomial<T> zero_element(std::multiplies< polynomial<T> >)
+BOOST_MATH_HOST_DEVICE polynomial<T> zero_element(std::multiplies< polynomial<T> >)
 {
     return polynomial<T>();
 }
 
 template <class T>
-polynomial<T> identity_element(std::multiplies< polynomial<T> >)
+BOOST_MATH_HOST_DEVICE polynomial<T> identity_element(std::multiplies< polynomial<T> >)
 {
     return polynomial<T>(T(1));
 }
@@ -264,7 +264,7 @@ polynomial<T> identity_element(std::multiplies< polynomial<T> >)
  * This function is not defined for division by zero: user beware.
  */
 template <typename T>
-std::pair< polynomial<T>, polynomial<T> >
+BOOST_MATH_HOST_DEVICE std::pair< polynomial<T>, polynomial<T> >
 quotient_remainder(const polynomial<T>& dividend, const polynomial<T>& divisor)
 {
     BOOST_MATH_ASSERT(divisor);
@@ -283,51 +283,51 @@ class polynomial
    typedef typename std::vector<T>::size_type size_type;
 
    // construct:
-   polynomial()= default;
+   BOOST_MATH_HOST_DEVICE polynomial()= default;
 
    template <class U>
-   polynomial(const U* data, unsigned order)
+   BOOST_MATH_HOST_DEVICE polynomial(const U* data, unsigned order)
       : m_data(data, data + order + 1)
    {
        normalize();
    }
 
    template <class Iterator>
-   polynomial(Iterator first, Iterator last)
+   BOOST_MATH_HOST_DEVICE polynomial(Iterator first, Iterator last)
       : m_data(first, last)
    {
        normalize();
    }
 
    template <class Iterator>
-   polynomial(Iterator first, unsigned length)
+   BOOST_MATH_HOST_DEVICE polynomial(Iterator first, unsigned length)
       : m_data(first, std::next(first, length + 1))
    {
        normalize();
    }
 
-   polynomial(std::vector<T>&& p) : m_data(std::move(p))
+   BOOST_MATH_HOST_DEVICE polynomial(std::vector<T>&& p) : m_data(std::move(p))
    {
       normalize();
    }
 
    template <class U, typename std::enable_if<std::is_convertible<U, T>::value, bool>::type = true>
-   explicit polynomial(const U& point)
+   BOOST_MATH_HOST_DEVICE explicit polynomial(const U& point)
    {
        if (point != U(0))
           m_data.push_back(point);
    }
 
    // move:
-   polynomial(polynomial&& p) noexcept
+   BOOST_MATH_HOST_DEVICE polynomial(polynomial&& p) noexcept
       : m_data(std::move(p.m_data)) { }
 
    // copy:
-   polynomial(const polynomial& p)
+   BOOST_MATH_HOST_DEVICE polynomial(const polynomial& p)
       : m_data(p.m_data) { }
 
    template <class U>
-   polynomial(const polynomial<U>& p)
+   BOOST_MATH_HOST_DEVICE polynomial(const polynomial<U>& p)
    {
       m_data.resize(p.size());
       for(unsigned i = 0; i < p.size(); ++i)
@@ -337,17 +337,17 @@ class polynomial
    }
 #ifdef BOOST_MATH_HAS_IS_CONST_ITERABLE
     template <class Range, typename std::enable_if<boost::math::tools::detail::is_const_iterable<Range>::value, bool>::type = true>
-    explicit polynomial(const Range& r) 
+    BOOST_MATH_HOST_DEVICE explicit polynomial(const Range& r)
        : polynomial(r.begin(), r.end()) 
     {
     }
 #endif
-    polynomial(std::initializer_list<T> l) : polynomial(std::begin(l), std::end(l))
+    BOOST_MATH_HOST_DEVICE polynomial(std::initializer_list<T> l) : polynomial(std::begin(l), std::end(l))
     {
     }
 
     polynomial&
-    operator=(std::initializer_list<T> l)
+    BOOST_MATH_HOST_DEVICE operator=(std::initializer_list<T> l)
     {
         m_data.assign(std::begin(l), std::end(l));
         normalize();
@@ -356,47 +356,47 @@ class polynomial
 
 
    // access:
-   size_type size() const { return m_data.size(); }
-   size_type degree() const
+   BOOST_MATH_HOST_DEVICE size_type size() const { return m_data.size(); }
+   BOOST_MATH_HOST_DEVICE size_type degree() const
    {
        if (size() == 0)
           BOOST_MATH_THROW_EXCEPTION(std::logic_error("degree() is undefined for the zero polynomial."));
        return m_data.size() - 1;
    }
-   value_type& operator[](size_type i)
+   BOOST_MATH_HOST_DEVICE value_type& operator[](size_type i)
    {
       return m_data[i];
    }
-   const value_type& operator[](size_type i) const
+   BOOST_MATH_HOST_DEVICE const value_type& operator[](size_type i) const
    {
       return m_data[i];
    }
 
-   T evaluate(T z) const
+   BOOST_MATH_HOST_DEVICE T evaluate(T z) const
    {
       return this->operator()(z);
    }
 
-   T operator()(T z) const
+   BOOST_MATH_HOST_DEVICE T operator()(T z) const
    {
       return m_data.size() > 0 ? boost::math::tools::evaluate_polynomial((m_data).data(), z, m_data.size()) : T(0);
    }
-   std::vector<T> chebyshev() const
+   BOOST_MATH_HOST_DEVICE std::vector<T> chebyshev() const
    {
       return polynomial_to_chebyshev(m_data);
    }
 
-   std::vector<T> const& data() const
+   BOOST_MATH_HOST_DEVICE std::vector<T> const& data() const
    {
        return m_data;
    }
 
-   std::vector<T> & data()
+   BOOST_MATH_HOST_DEVICE std::vector<T> & data()
    {
        return m_data;
    }
 
-   polynomial<T> prime() const
+   BOOST_MATH_HOST_DEVICE polynomial<T> prime() const
    {
 #ifdef _MSC_VER
       // Disable int->float conversion warning:
@@ -418,7 +418,7 @@ class polynomial
 #endif
    }
 
-   polynomial<T> integrate() const
+   BOOST_MATH_HOST_DEVICE polynomial<T> integrate() const
    {
       std::vector<T> i_data(m_data.size() + 1);
       // Choose integration constant such that P(0) = 0.
@@ -431,20 +431,20 @@ class polynomial
    }
 
    // operators:
-   polynomial& operator =(polynomial&& p) noexcept
+   BOOST_MATH_HOST_DEVICE polynomial& operator =(polynomial&& p) noexcept
    {
        m_data = std::move(p.m_data);
        return *this;
    }
 
-   polynomial& operator =(const polynomial& p)
+   BOOST_MATH_HOST_DEVICE polynomial& operator =(const polynomial& p)
    {
        m_data = p.m_data;
        return *this;
    }
 
    template <class U>
-   typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator +=(const U& value)
+   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator +=(const U& value)
    {
        addition(value);
        normalize();
@@ -452,7 +452,7 @@ class polynomial
    }
 
    template <class U>
-   typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator -=(const U& value)
+   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator -=(const U& value)
    {
        subtraction(value);
        normalize();
@@ -460,7 +460,7 @@ class polynomial
    }
 
    template <class U>
-   typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator *=(const U& value)
+   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator *=(const U& value)
    {
       multiplication(value);
       normalize();
@@ -468,7 +468,7 @@ class polynomial
    }
 
    template <class U>
-   typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator /=(const U& value)
+   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator /=(const U& value)
    {
        division(value);
        normalize();
@@ -476,7 +476,7 @@ class polynomial
    }
 
    template <class U>
-   typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator %=(const U& /*value*/)
+   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator %=(const U& /*value*/)
    {
        // We can always divide by a scalar, so there is no remainder:
        this->set_zero();
@@ -484,7 +484,7 @@ class polynomial
    }
 
    template <class U>
-   polynomial& operator +=(const polynomial<U>& value)
+   BOOST_MATH_HOST_DEVICE polynomial& operator +=(const polynomial<U>& value)
    {
       addition(value);
       normalize();
@@ -492,7 +492,7 @@ class polynomial
    }
 
    template <class U>
-   polynomial& operator -=(const polynomial<U>& value)
+   BOOST_MATH_HOST_DEVICE polynomial& operator -=(const polynomial<U>& value)
    {
        subtraction(value);
        normalize();
@@ -500,7 +500,7 @@ class polynomial
    }
 
    template <typename U, typename V>
-   void multiply(const polynomial<U>& a, const polynomial<V>& b) {
+   BOOST_MATH_HOST_DEVICE void multiply(const polynomial<U>& a, const polynomial<V>& b) {
        if (!a || !b)
        {
            this->set_zero();
@@ -514,28 +514,28 @@ class polynomial
    }
 
    template <class U>
-   polynomial& operator *=(const polynomial<U>& value)
+   BOOST_MATH_HOST_DEVICE polynomial& operator *=(const polynomial<U>& value)
    {
       this->multiply(*this, value);
       return *this;
    }
 
    template <typename U>
-   polynomial& operator /=(const polynomial<U>& value)
+   BOOST_MATH_HOST_DEVICE polynomial& operator /=(const polynomial<U>& value)
    {
        *this = quotient_remainder(*this, value).first;
        return *this;
    }
 
    template <typename U>
-   polynomial& operator %=(const polynomial<U>& value)
+   BOOST_MATH_HOST_DEVICE polynomial& operator %=(const polynomial<U>& value)
    {
        *this = quotient_remainder(*this, value).second;
        return *this;
    }
 
    template <typename U>
-   polynomial& operator >>=(U const &n)
+   BOOST_MATH_HOST_DEVICE polynomial& operator >>=(U const &n)
    {
        BOOST_MATH_ASSERT(n <= m_data.size());
        m_data.erase(m_data.begin(), m_data.begin() + n);
@@ -543,7 +543,7 @@ class polynomial
    }
 
    template <typename U>
-   polynomial& operator <<=(U const &n)
+   BOOST_MATH_HOST_DEVICE polynomial& operator <<=(U const &n)
    {
        m_data.insert(m_data.begin(), n, static_cast<T>(0));
        normalize();
@@ -551,33 +551,33 @@ class polynomial
    }
 
    // Convenient and efficient query for zero.
-   bool is_zero() const
+   BOOST_MATH_HOST_DEVICE bool is_zero() const
    {
        return m_data.empty();
    }
 
    // Conversion to bool.
-   inline explicit operator bool() const
+   BOOST_MATH_HOST_DEVICE inline explicit operator bool() const
    {
        return !m_data.empty();
    }
 
    // Fast way to set a polynomial to zero.
-   void set_zero()
+   BOOST_MATH_HOST_DEVICE void set_zero()
    {
        m_data.clear();
    }
 
     /** Remove zero coefficients 'from the top', that is for which there are no
     *        non-zero coefficients of higher degree. */
-   void normalize()
+   BOOST_MATH_HOST_DEVICE void normalize()
    {
       m_data.erase(std::find_if(m_data.rbegin(), m_data.rend(), [](const T& x)->bool { return x != T(0); }).base(), m_data.end());
    }
 
 private:
     template <class U, class R>
-    polynomial& addition(const U& value, R op)
+    BOOST_MATH_HOST_DEVICE polynomial& addition(const U& value, R op)
     {
         if(m_data.size() == 0)
             m_data.resize(1, 0);
@@ -586,19 +586,19 @@ class polynomial
     }
 
     template <class U>
-    polynomial& addition(const U& value)
+    BOOST_MATH_HOST_DEVICE polynomial& addition(const U& value)
     {
         return addition(value, detail::plus());
     }
 
     template <class U>
-    polynomial& subtraction(const U& value)
+    BOOST_MATH_HOST_DEVICE polynomial& subtraction(const U& value)
     {
         return addition(value, detail::minus());
     }
 
     template <class U, class R>
-    polynomial& addition(const polynomial<U>& value, R op)
+    BOOST_MATH_HOST_DEVICE polynomial& addition(const polynomial<U>& value, R op)
     {
         if (m_data.size() < value.size())
             m_data.resize(value.size(), 0);
@@ -608,26 +608,26 @@ class polynomial
     }
 
     template <class U>
-    polynomial& addition(const polynomial<U>& value)
+    BOOST_MATH_HOST_DEVICE polynomial& addition(const polynomial<U>& value)
     {
         return addition(value, detail::plus());
     }
 
     template <class U>
-    polynomial& subtraction(const polynomial<U>& value)
+    BOOST_MATH_HOST_DEVICE polynomial& subtraction(const polynomial<U>& value)
     {
         return addition(value, detail::minus());
     }
 
     template <class U>
-    polynomial& multiplication(const U& value)
+    BOOST_MATH_HOST_DEVICE polynomial& multiplication(const U& value)
     {
        std::transform(m_data.begin(), m_data.end(), m_data.begin(), [&](const T& x)->T { return x * value; });
        return *this;
     }
 
     template <class U>
-    polynomial& division(const U& value)
+    BOOST_MATH_HOST_DEVICE polynomial& division(const U& value)
     {
        std::transform(m_data.begin(), m_data.end(), m_data.begin(), [&](const T& x)->T { return x / value; });
        return *this;
@@ -638,7 +638,7 @@ class polynomial
 
 
 template <class T>
-inline polynomial<T> operator + (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result(a);
    result += b;
@@ -646,26 +646,26 @@ inline polynomial<T> operator + (const polynomial<T>& a, const polynomial<T>& b)
 }
 
 template <class T>
-inline polynomial<T> operator + (polynomial<T>&& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (polynomial<T>&& a, const polynomial<T>& b)
 {
    a += b;
    return std::move(a);
 }
 template <class T>
-inline polynomial<T> operator + (const polynomial<T>& a, polynomial<T>&& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (const polynomial<T>& a, polynomial<T>&& b)
 {
    b += a;
    return b;
 }
 template <class T>
-inline polynomial<T> operator + (polynomial<T>&& a, polynomial<T>&& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (polynomial<T>&& a, polynomial<T>&& b)
 {
    a += b;
    return a;
 }
 
 template <class T>
-inline polynomial<T> operator - (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result(a);
    result -= b;
@@ -673,26 +673,26 @@ inline polynomial<T> operator - (const polynomial<T>& a, const polynomial<T>& b)
 }
 
 template <class T>
-inline polynomial<T> operator - (polynomial<T>&& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (polynomial<T>&& a, const polynomial<T>& b)
 {
    a -= b;
    return a;
 }
 template <class T>
-inline polynomial<T> operator - (const polynomial<T>& a, polynomial<T>&& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (const polynomial<T>& a, polynomial<T>&& b)
 {
    b -= a;
    return -b;
 }
 template <class T>
-inline polynomial<T> operator - (polynomial<T>&& a, polynomial<T>&& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (polynomial<T>&& a, polynomial<T>&& b)
 {
    a -= b;
    return a;
 }
 
 template <class T>
-inline polynomial<T> operator * (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator * (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result;
    result.multiply(a, b);
@@ -700,94 +700,94 @@ inline polynomial<T> operator * (const polynomial<T>& a, const polynomial<T>& b)
 }
 
 template <class T>
-inline polynomial<T> operator / (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator / (const polynomial<T>& a, const polynomial<T>& b)
 {
    return quotient_remainder(a, b).first;
 }
 
 template <class T>
-inline polynomial<T> operator % (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_HOST_DEVICE inline polynomial<T> operator % (const polynomial<T>& a, const polynomial<T>& b)
 {
    return quotient_remainder(a, b).second;
 }
 
 template <class T, class U>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (polynomial<T> a, const U& b)
 {
    a += b;
    return a;
 }
 
 template <class T, class U>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (polynomial<T> a, const U& b)
 {
    a -= b;
    return a;
 }
 
 template <class T, class U>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (polynomial<T> a, const U& b)
 {
    a *= b;
    return a;
 }
 
 template <class T, class U>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator / (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator / (polynomial<T> a, const U& b)
 {
    a /= b;
    return a;
 }
 
 template <class T, class U>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator % (const polynomial<T>&, const U&)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator % (const polynomial<T>&, const U&)
 {
    // Since we can always divide by a scalar, result is always an empty polynomial:
    return polynomial<T>();
 }
 
 template <class U, class T>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (const U& a, polynomial<T> b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (const U& a, polynomial<T> b)
 {
    b += a;
    return b;
 }
 
 template <class U, class T>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (const U& a, polynomial<T> b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (const U& a, polynomial<T> b)
 {
    b -= a;
    return -b;
 }
 
 template <class U, class T>
-inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (const U& a, polynomial<T> b)
+BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (const U& a, polynomial<T> b)
 {
    b *= a;
    return b;
 }
 
 template <class T>
-bool operator == (const polynomial<T> &a, const polynomial<T> &b)
+BOOST_MATH_HOST_DEVICE bool operator == (const polynomial<T> &a, const polynomial<T> &b)
 {
     return a.data() == b.data();
 }
 
 template <class T>
-bool operator != (const polynomial<T> &a, const polynomial<T> &b)
+BOOST_MATH_HOST_DEVICE bool operator != (const polynomial<T> &a, const polynomial<T> &b)
 {
     return a.data() != b.data();
 }
 
 template <typename T, typename U>
-polynomial<T> operator >> (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE polynomial<T> operator >> (polynomial<T> a, const U& b)
 {
     a >>= b;
     return a;
 }
 
 template <typename T, typename U>
-polynomial<T> operator << (polynomial<T> a, const U& b)
+BOOST_MATH_HOST_DEVICE polynomial<T> operator << (polynomial<T> a, const U& b)
 {
     a <<= b;
     return a;
@@ -795,26 +795,26 @@ polynomial<T> operator << (polynomial<T> a, const U& b)
 
 // Unary minus (negate).
 template <class T>
-polynomial<T> operator - (polynomial<T> a)
+BOOST_MATH_HOST_DEVICE polynomial<T> operator - (polynomial<T> a)
 {
     std::transform(a.data().begin(), a.data().end(), a.data().begin(), detail::negate());
     return a;
 }
 
 template <class T>
-bool odd(polynomial<T> const &a)
+BOOST_MATH_HOST_DEVICE bool odd(polynomial<T> const &a)
 {
     return a.size() > 0 && a[0] != static_cast<T>(0);
 }
 
 template <class T>
-bool even(polynomial<T> const &a)
+BOOST_MATH_HOST_DEVICE bool even(polynomial<T> const &a)
 {
     return !odd(a);
 }
 
 template <class T>
-polynomial<T> pow(polynomial<T> base, int exp)
+BOOST_MATH_HOST_DEVICE polynomial<T> pow(polynomial<T> base, int exp)
 {
     if (exp < 0)
         return policies::raise_domain_error(
@@ -838,7 +838,7 @@ polynomial<T> pow(polynomial<T> base, int exp)
 }
 
 template <class charT, class traits, class T>
-inline std::basic_ostream<charT, traits>& operator << (std::basic_ostream<charT, traits>& os, const polynomial<T>& poly)
+BOOST_MATH_HOST_DEVICE inline std::basic_ostream<charT, traits>& operator << (std::basic_ostream<charT, traits>& os, const polynomial<T>& poly)
 {
    os << "{ ";
    for(unsigned i = 0; i < poly.size(); ++i)

From f62b73a55660365d29ed878d624dce6d179835c4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 13:44:23 -0400
Subject: [PATCH 021/399] Add cuda markers to arcsine distribution

---
 include/boost/math/distributions/arcsine.hpp | 51 ++++++++++----------
 1 file changed, 26 insertions(+), 25 deletions(-)

diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index a8fcbbc05f..fd160da6e6 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -30,6 +30,7 @@
 #define BOOST_MATH_DIST_ARCSINE_HPP
 
 #include <cmath>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/complement.hpp> // complements.
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks.
@@ -55,7 +56,7 @@ namespace boost
       // Common error checking routines for arcsine distribution functions:
       // Duplicating for x_min and x_max provides specific error messages.
       template <class RealType, class Policy>
-      inline bool check_x_min(const char* function, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_x_min(const char* function, const RealType& x, RealType* result, const Policy& pol)
       {
         if (!(boost::math::isfinite)(x))
         {
@@ -68,7 +69,7 @@ namespace boost
       } // bool check_x_min
 
       template <class RealType, class Policy>
-      inline bool check_x_max(const char* function, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_x_max(const char* function, const RealType& x, RealType* result, const Policy& pol)
       {
         if (!(boost::math::isfinite)(x))
         {
@@ -82,7 +83,7 @@ namespace boost
 
 
       template <class RealType, class Policy>
-      inline bool check_x_minmax(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_x_minmax(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
       { // Check x_min < x_max
         if (x_min >= x_max)
         {
@@ -100,7 +101,7 @@ namespace boost
       } // bool check_x_minmax
 
       template <class RealType, class Policy>
-      inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         if ((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
         {
@@ -113,7 +114,7 @@ namespace boost
       } // bool check_prob
 
       template <class RealType, class Policy>
-      inline bool check_x(const char* function, const RealType& x_min, const RealType& x_max, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_x(const char* function, const RealType& x_min, const RealType& x_max, const RealType& x, RealType* result, const Policy& pol)
       { // Check x finite and x_min < x < x_max.
         if (!(boost::math::isfinite)(x))
         {
@@ -137,7 +138,7 @@ namespace boost
       } // bool check_x
 
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_dist(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
       { // Check both x_min and x_max finite, and x_min  < x_max.
         return check_x_min(function, x_min, result, pol)
             && check_x_max(function, x_max, result, pol)
@@ -145,14 +146,14 @@ namespace boost
       } // bool check_dist
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_x(const char* function, const RealType& x_min, const RealType& x_max, RealType x, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_dist_and_x(const char* function, const RealType& x_min, const RealType& x_max, RealType x, RealType* result, const Policy& pol)
       {
         return check_dist(function, x_min, x_max, result, pol)
           && arcsine_detail::check_x(function, x_min, x_max, x, result, pol);
       } // bool check_dist_and_x
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, const RealType& x_min, const RealType& x_max, RealType p, RealType* result, const Policy& pol)
+      BOOST_MATH_HOST_DEVICE inline bool check_dist_and_prob(const char* function, const RealType& x_min, const RealType& x_max, RealType p, RealType* result, const Policy& pol)
       {
         return check_dist(function, x_min, x_max, result, pol)
           && check_prob(function, p, result, pol);
@@ -167,7 +168,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      arcsine_distribution(RealType x_min = 0, RealType x_max = 1) : m_x_min(x_min), m_x_max(x_max)
+      BOOST_MATH_HOST_DEVICE arcsine_distribution(RealType x_min = 0, RealType x_max = 1) : m_x_min(x_min), m_x_max(x_max)
       { // Default beta (alpha = beta = 0.5) is standard arcsine with x_min = 0, x_max = 1.
         // Generalized to allow x_min and x_max to be specified.
         RealType result;
@@ -178,11 +179,11 @@ namespace boost
           &result, Policy());
       } // arcsine_distribution constructor.
       // Accessor functions:
-      RealType x_min() const
+      BOOST_MATH_HOST_DEVICE RealType x_min() const
       {
         return m_x_min;
       }
-      RealType x_max() const
+      BOOST_MATH_HOST_DEVICE RealType x_max() const
       {
         return m_x_max;
       }
@@ -203,21 +204,21 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_HOST_DEVICE inline const std::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
       return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_HOST_DEVICE inline const std::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
       return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType mean(const arcsine_distribution<RealType, Policy>& dist)
     { // Mean of arcsine distribution .
       RealType result;
       RealType x_min = dist.x_min();
@@ -236,7 +237,7 @@ namespace boost
     } // mean
 
     template <class RealType, class Policy>
-    inline RealType variance(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType variance(const arcsine_distribution<RealType, Policy>& dist)
     { // Variance of standard arcsine distribution = (1-0)/8 = 0.125.
       RealType result;
       RealType x_min = dist.x_min();
@@ -254,7 +255,7 @@ namespace boost
     } // variance
 
     template <class RealType, class Policy>
-    inline RealType mode(const arcsine_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_HOST_DEVICE inline RealType mode(const arcsine_distribution<RealType, Policy>& /* dist */)
     { //There are always [*two] values for the mode, at ['x_min] and at ['x_max], default 0 and 1,
       // so instead we raise the exception domain_error.
       return policies::raise_domain_error<RealType>(
@@ -265,7 +266,7 @@ namespace boost
     } // mode
 
     template <class RealType, class Policy>
-    inline RealType median(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType median(const arcsine_distribution<RealType, Policy>& dist)
     { // Median of arcsine distribution (a + b) / 2 == mean.
       RealType x_min = dist.x_min();
       RealType x_max = dist.x_max();
@@ -283,7 +284,7 @@ namespace boost
     }
 
     template <class RealType, class Policy>
-    inline RealType skewness(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType skewness(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -302,7 +303,7 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType kurtosis_excess(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -322,7 +323,7 @@ namespace boost
     } // kurtosis_excess
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_HOST_DEVICE inline RealType kurtosis(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -342,7 +343,7 @@ namespace boost
     } // kurtosis
 
     template <class RealType, class Policy>
-    inline RealType pdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& xx)
+    BOOST_MATH_HOST_DEVICE inline RealType pdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& xx)
     { // Probability Density/Mass Function arcsine.
       BOOST_FPU_EXCEPTION_GUARD
       BOOST_MATH_STD_USING // For ADL of std functions.
@@ -368,7 +369,7 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_HOST_DEVICE inline RealType cdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& x)
     { // Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
 
@@ -401,7 +402,7 @@ namespace boost
     } // arcsine cdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_HOST_DEVICE inline RealType cdf(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
       static const char* function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
@@ -437,7 +438,7 @@ namespace boost
     } // arcsine ccdf
 
     template <class RealType, class Policy>
-    inline RealType quantile(const arcsine_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_HOST_DEVICE inline RealType quantile(const arcsine_distribution<RealType, Policy>& dist, const RealType& p)
     { 
       // Quantile or Percent Point arcsine function or
       // Inverse Cumulative probability distribution function CDF.
@@ -481,7 +482,7 @@ namespace boost
     } // quantile
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_HOST_DEVICE inline RealType quantile(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
     { 
       // Complement Quantile or Percent Point arcsine function.
       // Return the number of expected x for a given

From 977ccbf7b0d88ae30ed25796891a45a80d1a1578 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 15:45:46 -0400
Subject: [PATCH 022/399] Add CUDA definition of force inline ignoring that of
 the host compiler

---
 include/boost/math/tools/config.hpp | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 81593a69cb..0c41a86502 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -666,11 +666,15 @@ namespace boost{ namespace math{
 // CUDA support:
 //
 
-#ifdef __NVCC__
+#ifdef __CUDACC__
 #  define BOOST_MATH_HOST_DEVICE __host__ __device__
 #  ifndef BOOST_MATH_ENABLE_CUDA
 #    define BOOST_MATH_ENABLE_CUDA
 #  endif
+
+// We want to use force inline from CUDA instead of the host compiler
+#  undef BOOST_MATH_FORCEINLINE
+#  define BOOST_MATH_FORCEINLINE __forceinline__
 #else
 #  define BOOST_MATH_HOST_DEVICE
 #endif

From 980a10cc8b573340b0adf008aad0601c0332e46f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 16:21:18 -0400
Subject: [PATCH 023/399] Add config option to return NANs

---
 include/boost/math/tools/config.hpp | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 0c41a86502..8c7e2ddcf7 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -675,8 +675,13 @@ namespace boost{ namespace math{
 // We want to use force inline from CUDA instead of the host compiler
 #  undef BOOST_MATH_FORCEINLINE
 #  define BOOST_MATH_FORCEINLINE __forceinline__
+
+// We can't use return std::numeric_limits<T>::quiet_NaN()
+#  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
+
 #else
 #  define BOOST_MATH_HOST_DEVICE
+#  define BOOST_MATH_QUIET_NAN(T) std::numeric_limits<T>::quiet_NaN();
 #endif
 
 // Static variables are not allowed with CUDA or C++20 modules

From ec3d237aca538b9ca67b3076fedf199faac6a34e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 18 Jul 2024 16:21:41 -0400
Subject: [PATCH 024/399] First cut at CUDA allowed policies

---
 .../boost/math/policies/error_handling.hpp    | 128 +++++++++---------
 include/boost/math/policies/policy.hpp        |  54 ++++----
 2 files changed, 91 insertions(+), 91 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 070266c7fe..cd604aad39 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -199,7 +199,7 @@ void raise_error(const char* pfunction, const char* pmessage, const T& val)
 #endif
 
 template <class T>
-inline T raise_domain_error(
+BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
            const char* function,
            const char* message,
            const T& val,
@@ -210,12 +210,12 @@ inline T raise_domain_error(
 #else
    raise_error<std::domain_error, T>(function, message, val);
    // we never get here:
-   return std::numeric_limits<T>::quiet_NaN();
+   return BOOST_MATH_QUIET_NAN(T);
 #endif
 }
 
 template <class T>
-inline constexpr T raise_domain_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(
            const char* ,
            const char* ,
            const T& ,
@@ -223,11 +223,11 @@ inline constexpr T raise_domain_error(
 {
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
-   return std::numeric_limits<T>::quiet_NaN();
+   return BOOST_MATH_QUIET_NAN(T);
 }
 
 template <class T>
-inline T raise_domain_error(
+BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
            const char* ,
            const char* ,
            const T& ,
@@ -236,11 +236,11 @@ inline T raise_domain_error(
    errno = EDOM;
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
-   return std::numeric_limits<T>::quiet_NaN();
+   return BOOST_MATH_QUIET_NAN(T);
 }
 
 template <class T>
-inline T raise_domain_error(
+BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
            const char* function,
            const char* message,
            const T& val,
@@ -250,7 +250,7 @@ inline T raise_domain_error(
 }
 
 template <class T>
-inline T raise_pole_error(
+BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -264,7 +264,7 @@ inline T raise_pole_error(
 }
 
 template <class T>
-inline constexpr T raise_pole_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -274,7 +274,7 @@ inline constexpr T raise_pole_error(
 }
 
 template <class T>
-inline constexpr T raise_pole_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -284,7 +284,7 @@ inline constexpr T raise_pole_error(
 }
 
 template <class T>
-inline T raise_pole_error(
+BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -294,7 +294,7 @@ inline T raise_pole_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::throw_on_error>&)
@@ -309,7 +309,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* function,
            const char* message,
            const T& val,
@@ -325,7 +325,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline constexpr T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -336,7 +336,7 @@ inline constexpr T raise_overflow_error(
 }
 
 template <class T>
-inline constexpr T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
            const char* ,
            const char* ,
            const T&,
@@ -348,7 +348,7 @@ inline constexpr T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -360,7 +360,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* ,
            const char* ,
            const T&,
@@ -373,7 +373,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::user_error>&)
@@ -382,7 +382,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_overflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
            const char* function,
            const char* message,
            const T& val,
@@ -396,7 +396,7 @@ inline T raise_overflow_error(
 }
 
 template <class T>
-inline T raise_underflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::throw_on_error>&)
@@ -411,7 +411,7 @@ inline T raise_underflow_error(
 }
 
 template <class T>
-inline constexpr T raise_underflow_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -422,7 +422,7 @@ inline constexpr T raise_underflow_error(
 }
 
 template <class T>
-inline T raise_underflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
            const char* /* function */,
            const char* /* message */,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -434,7 +434,7 @@ inline T raise_underflow_error(
 }
 
 template <class T>
-inline T raise_underflow_error(
+BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::user_error>&)
@@ -443,7 +443,7 @@ inline T raise_underflow_error(
 }
 
 template <class T>
-inline T raise_denorm_error(
+BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
            const char* function,
            const char* message,
            const T& /* val */,
@@ -459,7 +459,7 @@ inline T raise_denorm_error(
 }
 
 template <class T>
-inline constexpr T raise_denorm_error(
+BOOST_MATH_HOST_DEVICE inline constexpr T raise_denorm_error(
            const char* ,
            const char* ,
            const T&  val,
@@ -471,7 +471,7 @@ inline constexpr T raise_denorm_error(
 }
 
 template <class T>
-inline T raise_denorm_error(
+BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
            const char* ,
            const char* ,
            const T& val,
@@ -484,7 +484,7 @@ inline T raise_denorm_error(
 }
 
 template <class T>
-inline T raise_denorm_error(
+BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
            const char* function,
            const char* message,
            const T& val,
@@ -494,7 +494,7 @@ inline T raise_denorm_error(
 }
 
 template <class T>
-inline T raise_evaluation_error(
+BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
            const char* function,
            const char* message,
            const T& val,
@@ -510,7 +510,7 @@ inline T raise_evaluation_error(
 }
 
 template <class T>
-inline constexpr T raise_evaluation_error(
+BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(
            const char* ,
            const char* ,
            const T& val,
@@ -522,7 +522,7 @@ inline constexpr T raise_evaluation_error(
 }
 
 template <class T>
-inline T raise_evaluation_error(
+BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
            const char* ,
            const char* ,
            const T& val,
@@ -535,7 +535,7 @@ inline T raise_evaluation_error(
 }
 
 template <class T>
-inline T raise_evaluation_error(
+BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
            const char* function,
            const char* message,
            const T& val,
@@ -545,7 +545,7 @@ inline T raise_evaluation_error(
 }
 
 template <class T, class TargetType>
-inline TargetType raise_rounding_error(
+BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
            const char* function,
            const char* message,
            const T& val,
@@ -562,7 +562,7 @@ inline TargetType raise_rounding_error(
 }
 
 template <class T, class TargetType>
-inline constexpr TargetType raise_rounding_error(
+BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(
            const char* ,
            const char* ,
            const T& val,
@@ -576,7 +576,7 @@ inline constexpr TargetType raise_rounding_error(
 }
 
 template <class T, class TargetType>
-inline TargetType raise_rounding_error(
+BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
            const char* ,
            const char* ,
            const T& val,
@@ -590,7 +590,7 @@ inline TargetType raise_rounding_error(
    return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
 }
 template <class T, class TargetType>
-inline TargetType raise_rounding_error(
+BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
            const char* function,
            const char* message,
            const T& val,
@@ -601,7 +601,7 @@ inline TargetType raise_rounding_error(
 }
 
 template <class T, class R>
-inline T raise_indeterminate_result_error(
+BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
            const char* function,
            const char* message,
            const T& val,
@@ -618,7 +618,7 @@ inline T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-inline constexpr T raise_indeterminate_result_error(
+BOOST_MATH_HOST_DEVICE inline constexpr T raise_indeterminate_result_error(
            const char* ,
            const char* ,
            const T& ,
@@ -631,7 +631,7 @@ inline constexpr T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-inline T raise_indeterminate_result_error(
+BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
            const char* ,
            const char* ,
            const T& ,
@@ -645,7 +645,7 @@ inline T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-inline T raise_indeterminate_result_error(
+BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
            const char* function,
            const char* message,
            const T& val,
@@ -658,7 +658,7 @@ inline T raise_indeterminate_result_error(
 }  // namespace detail
 
 template <class T, class Policy>
-inline constexpr T raise_domain_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::domain_error_type policy_type;
    return detail::raise_domain_error(
@@ -667,7 +667,7 @@ inline constexpr T raise_domain_error(const char* function, const char* message,
 }
 
 template <class T, class Policy>
-inline constexpr T raise_pole_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::pole_error_type policy_type;
    return detail::raise_pole_error(
@@ -676,7 +676,7 @@ inline constexpr T raise_pole_error(const char* function, const char* message, c
 }
 
 template <class T, class Policy>
-inline constexpr T raise_overflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::overflow_error_type policy_type;
    return detail::raise_overflow_error<T>(
@@ -685,7 +685,7 @@ inline constexpr T raise_overflow_error(const char* function, const char* messag
 }
 
 template <class T, class Policy>
-inline constexpr T raise_overflow_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::overflow_error_type policy_type;
    return detail::raise_overflow_error(
@@ -694,7 +694,7 @@ inline constexpr T raise_overflow_error(const char* function, const char* messag
 }
 
 template <class T, class Policy>
-inline constexpr T raise_underflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::underflow_error_type policy_type;
    return detail::raise_underflow_error<T>(
@@ -703,7 +703,7 @@ inline constexpr T raise_underflow_error(const char* function, const char* messa
 }
 
 template <class T, class Policy>
-inline constexpr T raise_denorm_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_denorm_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::denorm_error_type policy_type;
    return detail::raise_denorm_error<T>(
@@ -713,7 +713,7 @@ inline constexpr T raise_denorm_error(const char* function, const char* message,
 }
 
 template <class T, class Policy>
-inline constexpr T raise_evaluation_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::evaluation_error_type policy_type;
    return detail::raise_evaluation_error(
@@ -722,7 +722,7 @@ inline constexpr T raise_evaluation_error(const char* function, const char* mess
 }
 
 template <class T, class TargetType, class Policy>
-inline constexpr TargetType raise_rounding_error(const char* function, const char* message, const T& val, const TargetType& t, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(const char* function, const char* message, const T& val, const TargetType& t, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::rounding_error_type policy_type;
    return detail::raise_rounding_error(
@@ -731,7 +731,7 @@ inline constexpr TargetType raise_rounding_error(const char* function, const cha
 }
 
 template <class T, class R, class Policy>
-inline constexpr T raise_indeterminate_result_error(const char* function, const char* message, const T& val, const R& result, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE constexpr T raise_indeterminate_result_error(const char* function, const char* message, const T& val, const R& result, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::indeterminate_result_error_type policy_type;
    return detail::raise_indeterminate_result_error(
@@ -746,7 +746,7 @@ namespace detail
 {
 
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    BOOST_MATH_STD_USING
    if(fabs(val) > tools::max_value<R>())
@@ -758,7 +758,7 @@ BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* result, const char* functio
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -768,7 +768,7 @@ BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T> val, R* result, const
    return r;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    if((val != 0) && (static_cast<R>(val) == 0))
    {
@@ -778,7 +778,7 @@ BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* result, const char* functi
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -788,7 +788,7 @@ BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<T> val, R* result, cons
    return r;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    BOOST_MATH_STD_USING
    if((fabs(val) < static_cast<T>(tools::min_value<R>())) && (static_cast<R>(val) != 0))
@@ -799,7 +799,7 @@ BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result, const char* function,
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -811,28 +811,28 @@ BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T> val, R* result, const c
 
 // Default instantiations with ignore_error policy.
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_overflow(T /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_overflow(T /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_overflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_overflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_underflow(T /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_underflow(T /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_underflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_underflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_denorm(T /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_denorm(T /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_FORCEINLINE constexpr bool check_denorm(std::complex<T> /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_denorm(std::complex<T> /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 
 } // namespace detail
 
 template <class R, class Policy, class T>
-BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    typedef typename Policy::overflow_error_type overflow_type;
    typedef typename Policy::underflow_error_type underflow_type;
@@ -852,7 +852,7 @@ BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noe
 }
 
 template <class T, class Policy>
-inline void check_series_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_HOST_DEVICE inline void check_series_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    if(max_iter >= policies::get_max_series_iterations<Policy>())
       raise_evaluation_error<T>(
@@ -861,7 +861,7 @@ inline void check_series_iterations(const char* function, std::uintmax_t max_ite
 }
 
 template <class T, class Policy>
-inline void check_root_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_HOST_DEVICE inline void check_root_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    if(max_iter >= policies::get_max_root_iterations<Policy>())
       raise_evaluation_error<T>(
@@ -878,7 +878,7 @@ namespace detail{
 // that value usually comes from one of the error handlers above:
 //
 template <class T>
-std::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_HOST_DEVICE std::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
 {
    return std::make_pair(val, val);
 }
diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index eb09682e32..25a43f41e6 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -22,9 +22,9 @@ namespace mp = tools::meta_programming;
 namespace tools{
 
 template <class T>
-constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept;
+BOOST_MATH_HOST_DEVICE constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept;
 template <class T>
-constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value);
+BOOST_MATH_HOST_DEVICE constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value);
 
 }
 
@@ -640,81 +640,81 @@ struct normalise<policy<detail::forwarding_arg1, detail::forwarding_arg2>,
    using type = policy<detail::forwarding_arg1, detail::forwarding_arg2>;
 };
 
-inline constexpr policy<> make_policy() noexcept
+BOOST_MATH_HOST_DEVICE constexpr policy<> make_policy() noexcept
 { return {}; }
 
 template <class A1>
-inline constexpr typename normalise<policy<>, A1>::type make_policy(const A1&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1>::type make_policy(const A1&) noexcept
 {
    typedef typename normalise<policy<>, A1>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2>
-inline constexpr typename normalise<policy<>, A1, A2>::type make_policy(const A1&, const A2&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2>::type make_policy(const A1&, const A2&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3>
-inline constexpr typename normalise<policy<>, A1, A2, A3>::type make_policy(const A1&, const A2&, const A3&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3>::type make_policy(const A1&, const A2&, const A3&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4>::type make_policy(const A1&, const A2&, const A3&, const A4&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4>::type make_policy(const A1&, const A2&, const A3&, const A4&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9, class A10>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9, class A10, class A11>
-inline constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&, const A11&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&, const A11&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type result_type;
    return result_type();
@@ -793,7 +793,7 @@ struct precision<BOOST_MATH_FLOAT128_TYPE, Policy>
 namespace detail{
 
 template <class T, class Policy>
-inline constexpr int digits_imp(std::true_type const&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::true_type const&) noexcept
 {
    static_assert( std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
    typedef typename boost::math::policies::precision<T, Policy>::type p_t;
@@ -801,7 +801,7 @@ inline constexpr int digits_imp(std::true_type const&) noexcept
 }
 
 template <class T, class Policy>
-inline constexpr int digits_imp(std::false_type const&) noexcept
+BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::false_type const&) noexcept
 {
    return tools::digits<T>();
 }
@@ -809,26 +809,26 @@ inline constexpr int digits_imp(std::false_type const&) noexcept
 } // namespace detail
 
 template <class T, class Policy>
-inline constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
+BOOST_MATH_HOST_DEVICE constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
 {
    typedef std::integral_constant<bool, std::numeric_limits<T>::is_specialized > tag_type;
    return detail::digits_imp<T, Policy>(tag_type());
 }
 template <class T, class Policy>
-inline constexpr int digits_base10(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
+BOOST_MATH_HOST_DEVICE constexpr int digits_base10(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
 {
    return boost::math::policies::digits<T, Policy>() * 301 / 1000L;
 }
 
 template <class Policy>
-inline constexpr unsigned long get_max_series_iterations() noexcept
+BOOST_MATH_HOST_DEVICE constexpr unsigned long get_max_series_iterations() noexcept
 {
    typedef typename Policy::max_series_iterations_type iter_type;
    return iter_type::value;
 }
 
 template <class Policy>
-inline constexpr unsigned long get_max_root_iterations() noexcept
+BOOST_MATH_HOST_DEVICE constexpr unsigned long get_max_root_iterations() noexcept
 {
    typedef typename Policy::max_root_iterations_type iter_type;
    return iter_type::value;
@@ -839,7 +839,7 @@ namespace detail{
 template <class T, class Digits, class Small, class Default>
 struct series_factor_calc
 {
-   static T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_HOST_DEVICE static T get() noexcept(std::is_floating_point<T>::value)
    {
       return ldexp(T(1.0), 1 - Digits::value);
    }
@@ -848,7 +848,7 @@ struct series_factor_calc
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::true_type, std::true_type>
 {
-   static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
@@ -856,7 +856,7 @@ struct series_factor_calc<T, Digits, std::true_type, std::true_type>
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::true_type, std::false_type>
 {
-   static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return 1 / static_cast<T>(static_cast<std::uintmax_t>(1u) << (Digits::value - 1));
    }
@@ -864,14 +864,14 @@ struct series_factor_calc<T, Digits, std::true_type, std::false_type>
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::false_type, std::true_type>
 {
-   static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
 };
 
 template <class T, class Policy>
-inline constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_floating_point<T>::value)
 {
    static_assert(std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
    static_assert(std::numeric_limits<T>::radix == 2, "std::numeric_limits<T>::radix == 2");
@@ -883,7 +883,7 @@ inline constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_float
 }
 
 template <class T, class Policy>
-inline constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floating_point<T>::value)
 {
    return tools::epsilon<T>();
 }
@@ -891,7 +891,7 @@ inline constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floa
 } // namespace detail
 
 template <class T, class Policy>
-inline constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_HOST_DEVICE constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    typedef std::integral_constant<bool, (std::numeric_limits<T>::is_specialized && (std::numeric_limits<T>::radix == 2)) > tag_type;
    return detail::get_epsilon_imp<T, Policy>(tag_type());

From 96921dae22a8225a87f08ff08260422bbe354d22 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 09:21:12 -0400
Subject: [PATCH 025/399] Add new definitions of classification functions

---
 .../math/special_functions/fpclassify.hpp     | 77 +++++++++++++++++++
 1 file changed, 77 insertions(+)

diff --git a/include/boost/math/special_functions/fpclassify.hpp b/include/boost/math/special_functions/fpclassify.hpp
index 2c504d7ac8..617d818488 100644
--- a/include/boost/math/special_functions/fpclassify.hpp
+++ b/include/boost/math/special_functions/fpclassify.hpp
@@ -14,6 +14,7 @@
 #include <limits>
 #include <type_traits>
 #include <cmath>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/real_cast.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/detail/fp_traits.hpp>
@@ -76,6 +77,80 @@ is used.
 
 */
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+namespace boost { namespace math {
+
+template<> inline BOOST_MATH_HOST_DEVICE bool (isnan)(float x) { return x != x; }
+template<> inline BOOST_MATH_HOST_DEVICE bool (isnan)(double x) { return x != x; }
+
+template<> inline BOOST_MATH_HOST_DEVICE bool (isinf)(float x) { return x > FLT_MAX || x < -FLT_MAX; }
+template<> inline BOOST_MATH_HOST_DEVICE bool (isinf)(double x) { return x > DBL_MAX || x < -DBL_MAX; }
+
+template<> inline BOOST_MATH_HOST_DEVICE bool (isfinite)(float x) {  return !isnan(x) && !isinf(x);  }
+template<> inline BOOST_MATH_HOST_DEVICE bool (isfinite)(double x) {  return !isnan(x) && !isinf(x); }
+
+template<> inline BOOST_MATH_HOST_DEVICE bool (isnormal)(float x)
+{
+   if(x < 0) x = -x;
+   return (x >= FLT_MIN) && (x <= FLT_MAX);
+}
+template<> inline BOOST_MATH_HOST_DEVICE bool (isnormal)(double x)
+{
+   if(x < 0) x = -x;
+   return (x >= DBL_MIN) && (x <= DBL_MAX);
+}
+
+template<> inline BOOST_MATH_HOST_DEVICE int (fpclassify)(float t)
+{
+   if((boost::math::isnan)(t))
+      return FP_NAN;
+   // std::fabs broken on a few systems especially for long long!!!!
+   float at = (t < 0.0f) ? -t : t;
+
+   // Use a process of exclusion to figure out
+   // what kind of type we have, this relies on
+   // IEEE conforming reals that will treat
+   // Nan's as unordered.  Some compilers
+   // don't do this once optimisations are
+   // turned on, hence the check for nan's above.
+   if(at <= FLT_MAX)
+   {
+      if(at >= FLT_MIN)
+         return FP_NORMAL;
+      return (at != 0) ? FP_SUBNORMAL : FP_ZERO;
+   }
+   else if(at > FLT_MAX)
+      return FP_INFINITE;
+   return FP_NAN;
+}
+
+template<> inline BOOST_MATH_HOST_DEVICE int (fpclassify)(double t)
+{
+   if((boost::math::isnan)(t))
+      return FP_NAN;
+   // std::fabs broken on a few systems especially for long long!!!!
+   double at = (t < 0.0) ? -t : t;
+
+   // Use a process of exclusion to figure out
+   // what kind of type we have, this relies on
+   // IEEE conforming reals that will treat
+   // Nan's as unordered.  Some compilers
+   // don't do this once optimisations are
+   // turned on, hence the check for nan's above.
+   if(at <= DBL_MAX)
+   {
+      if(at >= DBL_MIN)
+         return FP_NORMAL;
+      return (at != 0) ? FP_SUBNORMAL : FP_ZERO;
+   }
+   else if(at > DBL_MAX)
+      return FP_INFINITE;
+   return FP_NAN;
+}
+
+#else
+
 #if defined(_MSC_VER) || defined(BOOST_BORLANDC)
 #include <cfloat>
 #endif
@@ -632,6 +707,8 @@ inline bool (isnan)(__float128 x)
 }
 #endif
 
+#endif
+
 } // namespace math
 } // namespace boost
 #endif // BOOST_MATH_FPCLASSIFY_HPP

From fbf5a7f15e73fc08373310988784827ab7ca4ce6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 09:22:53 -0400
Subject: [PATCH 026/399] Replace use of std::string with char*

---
 include/boost/math/distributions/arcsine.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index fd160da6e6..aa824e5076 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -87,10 +87,10 @@ namespace boost
       { // Check x_min < x_max
         if (x_min >= x_max)
         {
-          std::string msg = "x_max argument is %1%, but must be > x_min";
+          constexpr auto msg = "x_max argument is %1%, but must be > x_min";
           *result = policies::raise_domain_error<RealType>(
             function,
-            msg.c_str(), x_max, pol);
+            msg, x_max, pol);
             // "x_max argument is %1%, but must be > x_min !", x_max, pol);
             // "x_max argument is %1%, but must be > x_min %2!", x_max, x_min, pol); would be better. 
             // But would require replication of all helpers functions in /policies/error_handling.hpp for two values,

From bb0716d3afcfda64ebfc59a12b10f1447799636c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 09:38:24 -0400
Subject: [PATCH 027/399] Mark constants as CUDA

---
 include/boost/math/constants/constants.hpp | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/constants/constants.hpp b/include/boost/math/constants/constants.hpp
index 4bf81c61d1..2ebd816888 100644
--- a/include/boost/math/constants/constants.hpp
+++ b/include/boost/math/constants/constants.hpp
@@ -209,11 +209,11 @@ namespace boost{ namespace math
       constant_initializer<T, & BOOST_MATH_JOIN(constant_, name)<T>::get_from_string >::force_instantiate();\
       return get_from_string();\
    }\
-   static inline constexpr T get(const std::integral_constant<int, construct_from_float>) noexcept\
+   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_float>) noexcept\
    { return BOOST_MATH_JOIN(x, F); }\
-   static inline constexpr T get(const std::integral_constant<int, construct_from_double>&) noexcept\
+   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_double>&) noexcept\
    { return x; }\
-   static inline constexpr T get(const std::integral_constant<int, construct_from_long_double>&) noexcept\
+   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_long_double>&) noexcept\
    { return BOOST_MATH_JOIN(x, L); }\
    BOOST_MATH_FLOAT128_CONSTANT_OVERLOAD(x) \
    template <int N> static inline const T& get(const std::integral_constant<int, N>&)\
@@ -231,9 +231,9 @@ namespace boost{ namespace math
    \
    \
    /* The actual forwarding function: */ \
-   template <typename T, typename Policy> inline constexpr typename detail::constant_return<T, Policy>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(Policy)) BOOST_MATH_NOEXCEPT(T)\
+   template <typename T, typename Policy> BOOST_MATH_HOST_DEVICE inline constexpr typename detail::constant_return<T, Policy>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(Policy)) BOOST_MATH_NOEXCEPT(T)\
    { return detail:: BOOST_MATH_JOIN(constant_, name)<T>::get(typename construction_traits<T, Policy>::type()); }\
-   template <typename T> inline constexpr typename detail::constant_return<T>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) BOOST_MATH_NOEXCEPT(T)\
+   template <typename T> BOOST_MATH_HOST_DEVICE inline constexpr typename detail::constant_return<T>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) BOOST_MATH_NOEXCEPT(T)\
    { return name<T, boost::math::policies::policy<> >(); }\
    \
    \
@@ -328,7 +328,7 @@ namespace boost{ namespace math
 #endif
 
 template <typename T>
-inline constexpr T tau() {  return two_pi<T>(); }
+BOOST_MATH_HOST_DEVICE inline constexpr T tau() {  return two_pi<T>(); }
 
 } // namespace constants
 } // namespace math

From 2481c0dd450650cd42afa4a351c1bb7d8c2f84e5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 09:50:16 -0400
Subject: [PATCH 028/399] Disable exceptions for device code

---
 include/boost/math/tools/config.hpp | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 8c7e2ddcf7..c0b6b13317 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -672,6 +672,11 @@ namespace boost{ namespace math{
 #    define BOOST_MATH_ENABLE_CUDA
 #  endif
 
+// Device code can not handle exceptions
+#  ifndef BOOST_MATH_NO_EXCEPTIONS
+#    define BOOST_MATH_NO_EXCEPTIONS
+#  endif
+
 // We want to use force inline from CUDA instead of the host compiler
 #  undef BOOST_MATH_FORCEINLINE
 #  define BOOST_MATH_FORCEINLINE __forceinline__

From 301637c0970e5a5cbd460afe70c48edc3ba5b97f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 11:03:12 -0400
Subject: [PATCH 029/399] Specialize epsilon functions

---
 include/boost/math/tools/precision.hpp | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index a7a807ea28..8a2c2367a3 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -138,11 +138,27 @@ inline T log_min_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_E
 }
 
 template <class T>
-inline constexpr T epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+constexpr T epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return std::numeric_limits<T>::epsilon();
 }
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+template <>
+BOOST_MATH_HOST_DEVICE constexpr float epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
+{
+   return FLT_EPSILON;
+}
+
+template <>
+BOOST_MATH_HOST_DEVICE constexpr double epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
+{
+   return DBL_EPSILON;
+}
+
+#endif
+
 #if defined(__GNUC__) && ((LDBL_MANT_DIG == 106) || (__LDBL_MANT_DIG__ == 106))
 template <>
 inline constexpr long double epsilon<long double>(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(long double)) noexcept
@@ -230,7 +246,7 @@ inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(
 #endif
 
 template <class T>
-inline constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_HOST_DEVICE constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(std::is_floating_point<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::epsilon<T>(std::integral_constant<bool, ::std::numeric_limits<T>::is_specialized>());

From d3e93ad4ed7f1a5143a4ab23d961eba058b607e0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 13:54:27 -0400
Subject: [PATCH 030/399] Add sycl configuration options

---
 include/boost/math/tools/config.hpp | 21 +++++++++++++++++++--
 1 file changed, 19 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index c0b6b13317..ae3716716d 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -667,7 +667,8 @@ namespace boost{ namespace math{
 //
 
 #ifdef __CUDACC__
-#  define BOOST_MATH_HOST_DEVICE __host__ __device__
+#  define BOOST_MATH_GPU_ENABLED __host__ __device__
+#  define BOOST_MATH_HAS_GPU_SUPPORT
 #  ifndef BOOST_MATH_ENABLE_CUDA
 #    define BOOST_MATH_ENABLE_CUDA
 #  endif
@@ -684,9 +685,25 @@ namespace boost{ namespace math{
 // We can't use return std::numeric_limits<T>::quiet_NaN()
 #  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
 
+#elif defined(SYCL_LANGUAGE_VERSION)
+
+#  define BOOST_MATH_GPU_ENABLED SYCL_EXTERNAL
+#  define BOOST_MATH_HAS_GPU_SUPPORT
+
+#  ifndef BOOST_MATH_NO_EXCEPTIONS
+#    define BOOST_MATH_NO_EXCEPTIONS
+#  endif
+
+#  undef BOOST_MATH_FORCEINLINE
+#  define BOOST_MATH_FORCEINLINE inline 
+
+#  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
+
 #else
-#  define BOOST_MATH_HOST_DEVICE
+
+#  define BOOST_MATH_GPU_ENABLED
 #  define BOOST_MATH_QUIET_NAN(T) std::numeric_limits<T>::quiet_NaN();
+
 #endif
 
 // Static variables are not allowed with CUDA or C++20 modules

From dee1c40420fc8b1efadd760c9fa849d0526a9a1b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 13:54:39 -0400
Subject: [PATCH 031/399] Rename GPU macros

---
 include/boost/math/constants/constants.hpp    |  12 +-
 include/boost/math/distributions/arcsine.hpp  |  50 ++---
 include/boost/math/distributions/binomial.hpp |  54 +++---
 .../boost/math/policies/error_handling.hpp    | 122 ++++++------
 include/boost/math/policies/policy.hpp        |  54 +++---
 .../math/special_functions/fpclassify.hpp     |  22 +--
 include/boost/math/tools/polynomial.hpp       | 182 +++++++++---------
 include/boost/math/tools/precision.hpp        |   8 +-
 8 files changed, 252 insertions(+), 252 deletions(-)

diff --git a/include/boost/math/constants/constants.hpp b/include/boost/math/constants/constants.hpp
index 2ebd816888..bd2afd714a 100644
--- a/include/boost/math/constants/constants.hpp
+++ b/include/boost/math/constants/constants.hpp
@@ -209,11 +209,11 @@ namespace boost{ namespace math
       constant_initializer<T, & BOOST_MATH_JOIN(constant_, name)<T>::get_from_string >::force_instantiate();\
       return get_from_string();\
    }\
-   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_float>) noexcept\
+   BOOST_MATH_GPU_ENABLED static inline constexpr T get(const std::integral_constant<int, construct_from_float>) noexcept\
    { return BOOST_MATH_JOIN(x, F); }\
-   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_double>&) noexcept\
+   BOOST_MATH_GPU_ENABLED static inline constexpr T get(const std::integral_constant<int, construct_from_double>&) noexcept\
    { return x; }\
-   BOOST_MATH_HOST_DEVICE static inline constexpr T get(const std::integral_constant<int, construct_from_long_double>&) noexcept\
+   BOOST_MATH_GPU_ENABLED static inline constexpr T get(const std::integral_constant<int, construct_from_long_double>&) noexcept\
    { return BOOST_MATH_JOIN(x, L); }\
    BOOST_MATH_FLOAT128_CONSTANT_OVERLOAD(x) \
    template <int N> static inline const T& get(const std::integral_constant<int, N>&)\
@@ -231,9 +231,9 @@ namespace boost{ namespace math
    \
    \
    /* The actual forwarding function: */ \
-   template <typename T, typename Policy> BOOST_MATH_HOST_DEVICE inline constexpr typename detail::constant_return<T, Policy>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(Policy)) BOOST_MATH_NOEXCEPT(T)\
+   template <typename T, typename Policy> BOOST_MATH_GPU_ENABLED inline constexpr typename detail::constant_return<T, Policy>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(Policy)) BOOST_MATH_NOEXCEPT(T)\
    { return detail:: BOOST_MATH_JOIN(constant_, name)<T>::get(typename construction_traits<T, Policy>::type()); }\
-   template <typename T> BOOST_MATH_HOST_DEVICE inline constexpr typename detail::constant_return<T>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) BOOST_MATH_NOEXCEPT(T)\
+   template <typename T> BOOST_MATH_GPU_ENABLED inline constexpr typename detail::constant_return<T>::type name(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) BOOST_MATH_NOEXCEPT(T)\
    { return name<T, boost::math::policies::policy<> >(); }\
    \
    \
@@ -328,7 +328,7 @@ namespace boost{ namespace math
 #endif
 
 template <typename T>
-BOOST_MATH_HOST_DEVICE inline constexpr T tau() {  return two_pi<T>(); }
+BOOST_MATH_GPU_ENABLED inline constexpr T tau() {  return two_pi<T>(); }
 
 } // namespace constants
 } // namespace math
diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index aa824e5076..a1d06b7db0 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -56,7 +56,7 @@ namespace boost
       // Common error checking routines for arcsine distribution functions:
       // Duplicating for x_min and x_max provides specific error messages.
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_x_min(const char* function, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_x_min(const char* function, const RealType& x, RealType* result, const Policy& pol)
       {
         if (!(boost::math::isfinite)(x))
         {
@@ -69,7 +69,7 @@ namespace boost
       } // bool check_x_min
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_x_max(const char* function, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_x_max(const char* function, const RealType& x, RealType* result, const Policy& pol)
       {
         if (!(boost::math::isfinite)(x))
         {
@@ -83,7 +83,7 @@ namespace boost
 
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_x_minmax(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_x_minmax(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
       { // Check x_min < x_max
         if (x_min >= x_max)
         {
@@ -101,7 +101,7 @@ namespace boost
       } // bool check_x_minmax
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         if ((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
         {
@@ -114,7 +114,7 @@ namespace boost
       } // bool check_prob
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_x(const char* function, const RealType& x_min, const RealType& x_max, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_x(const char* function, const RealType& x_min, const RealType& x_max, const RealType& x, RealType* result, const Policy& pol)
       { // Check x finite and x_min < x < x_max.
         if (!(boost::math::isfinite)(x))
         {
@@ -138,7 +138,7 @@ namespace boost
       } // bool check_x
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_dist(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& x_min, const RealType& x_max, RealType* result, const Policy& pol)
       { // Check both x_min and x_max finite, and x_min  < x_max.
         return check_x_min(function, x_min, result, pol)
             && check_x_max(function, x_max, result, pol)
@@ -146,14 +146,14 @@ namespace boost
       } // bool check_dist
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_dist_and_x(const char* function, const RealType& x_min, const RealType& x_max, RealType x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_x(const char* function, const RealType& x_min, const RealType& x_max, RealType x, RealType* result, const Policy& pol)
       {
         return check_dist(function, x_min, x_max, result, pol)
           && arcsine_detail::check_x(function, x_min, x_max, x, result, pol);
       } // bool check_dist_and_x
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline bool check_dist_and_prob(const char* function, const RealType& x_min, const RealType& x_max, RealType p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& x_min, const RealType& x_max, RealType p, RealType* result, const Policy& pol)
       {
         return check_dist(function, x_min, x_max, result, pol)
           && check_prob(function, p, result, pol);
@@ -168,7 +168,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      BOOST_MATH_HOST_DEVICE arcsine_distribution(RealType x_min = 0, RealType x_max = 1) : m_x_min(x_min), m_x_max(x_max)
+      BOOST_MATH_GPU_ENABLED arcsine_distribution(RealType x_min = 0, RealType x_max = 1) : m_x_min(x_min), m_x_max(x_max)
       { // Default beta (alpha = beta = 0.5) is standard arcsine with x_min = 0, x_max = 1.
         // Generalized to allow x_min and x_max to be specified.
         RealType result;
@@ -179,11 +179,11 @@ namespace boost
           &result, Policy());
       } // arcsine_distribution constructor.
       // Accessor functions:
-      BOOST_MATH_HOST_DEVICE RealType x_min() const
+      BOOST_MATH_GPU_ENABLED RealType x_min() const
       {
         return m_x_min;
       }
-      BOOST_MATH_HOST_DEVICE RealType x_max() const
+      BOOST_MATH_GPU_ENABLED RealType x_max() const
       {
         return m_x_max;
       }
@@ -204,21 +204,21 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline const std::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
       return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline const std::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
       return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType mean(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const arcsine_distribution<RealType, Policy>& dist)
     { // Mean of arcsine distribution .
       RealType result;
       RealType x_min = dist.x_min();
@@ -237,7 +237,7 @@ namespace boost
     } // mean
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType variance(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const arcsine_distribution<RealType, Policy>& dist)
     { // Variance of standard arcsine distribution = (1-0)/8 = 0.125.
       RealType result;
       RealType x_min = dist.x_min();
@@ -255,7 +255,7 @@ namespace boost
     } // variance
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType mode(const arcsine_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const arcsine_distribution<RealType, Policy>& /* dist */)
     { //There are always [*two] values for the mode, at ['x_min] and at ['x_max], default 0 and 1,
       // so instead we raise the exception domain_error.
       return policies::raise_domain_error<RealType>(
@@ -266,7 +266,7 @@ namespace boost
     } // mode
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType median(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType median(const arcsine_distribution<RealType, Policy>& dist)
     { // Median of arcsine distribution (a + b) / 2 == mean.
       RealType x_min = dist.x_min();
       RealType x_max = dist.x_max();
@@ -284,7 +284,7 @@ namespace boost
     }
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType skewness(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -303,7 +303,7 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType kurtosis_excess(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -323,7 +323,7 @@ namespace boost
     } // kurtosis_excess
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType kurtosis(const arcsine_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const arcsine_distribution<RealType, Policy>& dist)
     {
       RealType result;
       RealType x_min = dist.x_min();
@@ -343,7 +343,7 @@ namespace boost
     } // kurtosis
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType pdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& xx)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& xx)
     { // Probability Density/Mass Function arcsine.
       BOOST_FPU_EXCEPTION_GUARD
       BOOST_MATH_STD_USING // For ADL of std functions.
@@ -369,7 +369,7 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType cdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const arcsine_distribution<RealType, Policy>& dist, const RealType& x)
     { // Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
 
@@ -402,7 +402,7 @@ namespace boost
     } // arcsine cdf
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType cdf(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
       static const char* function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
@@ -438,7 +438,7 @@ namespace boost
     } // arcsine ccdf
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType quantile(const arcsine_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const arcsine_distribution<RealType, Policy>& dist, const RealType& p)
     { 
       // Quantile or Percent Point arcsine function or
       // Inverse Cumulative probability distribution function CDF.
@@ -482,7 +482,7 @@ namespace boost
     } // quantile
 
     template <class RealType, class Policy>
-    BOOST_MATH_HOST_DEVICE inline RealType quantile(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
     { 
       // Complement Quantile or Percent Point arcsine function.
       // Return the number of expected x for a given
diff --git a/include/boost/math/distributions/binomial.hpp b/include/boost/math/distributions/binomial.hpp
index 9a2bc73b1d..d17f8636b5 100644
--- a/include/boost/math/distributions/binomial.hpp
+++ b/include/boost/math/distributions/binomial.hpp
@@ -101,7 +101,7 @@ namespace boost
      namespace binomial_detail{
         // common error checking routines for binomial distribution functions:
         template <class RealType, class Policy>
-        BOOST_MATH_HOST_DEVICE inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
         {
            if((N < 0) || !(boost::math::isfinite)(N))
            {
@@ -113,7 +113,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_HOST_DEVICE inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
         {
            if((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
            {
@@ -125,7 +125,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_HOST_DEVICE inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
         {
            return check_success_fraction(
               function, p, result, pol)
@@ -133,7 +133,7 @@ namespace boost
                function, N, result, pol);
         }
         template <class RealType, class Policy>
-        BOOST_MATH_HOST_DEVICE inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
         {
            if(check_dist(function, N, p, result, pol) == false)
               return false;
@@ -154,7 +154,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_HOST_DEVICE inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
         {
            if((check_dist(function, N, p, result, pol) && detail::check_probability(function, prob, result, pol)) == false)
               return false;
@@ -162,7 +162,7 @@ namespace boost
         }
 
          template <class T, class Policy>
-         BOOST_MATH_HOST_DEVICE T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
+         BOOST_MATH_GPU_ENABLED T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
          {
             BOOST_MATH_STD_USING
             // mean:
@@ -197,7 +197,7 @@ namespace boost
          }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
+      BOOST_MATH_GPU_ENABLED RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
       { // Quantile or Percent Point Binomial function.
         // Return the number of expected successes k,
         // for a given probability p.
@@ -291,11 +291,11 @@ namespace boost
             &r, Policy());
       } // binomial_distribution constructor.
 
-      BOOST_MATH_HOST_DEVICE RealType success_fraction() const
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const
       { // Probability.
         return m_p;
       }
-      BOOST_MATH_HOST_DEVICE RealType trials() const
+      BOOST_MATH_GPU_ENABLED RealType trials() const
       { // Total number of trials.
         return m_n;
       }
@@ -311,7 +311,7 @@ namespace boost
       // these functions are used
       // to obtain confidence intervals for the success fraction.
       //
-      BOOST_MATH_HOST_DEVICE static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
@@ -336,7 +336,7 @@ namespace boost
         return (t == clopper_pearson_exact_interval) ? ibeta_inv(successes, trials - successes + 1, probability, static_cast<RealType*>(nullptr), Policy())
            : ibeta_inv(successes + 0.5f, trials - successes + 0.5f, probability, static_cast<RealType*>(nullptr), Policy());
       }
-      BOOST_MATH_HOST_DEVICE static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
@@ -364,7 +364,7 @@ namespace boost
       //    or
       // "How many trials can I have to be P% sure of seeing fewer than k events?"
       //
-      BOOST_MATH_HOST_DEVICE static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
@@ -383,7 +383,7 @@ namespace boost
         return result + k;
       }
 
-      BOOST_MATH_HOST_DEVICE static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
@@ -420,33 +420,33 @@ namespace boost
       #endif
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
       { // Range of permissible values for random variable k.
         using boost::math::tools::max_value;
         return std::pair<RealType, RealType>(static_cast<RealType>(0), dist.trials());
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
       { // Range of supported values for random variable k.
         // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
         return std::pair<RealType, RealType>(static_cast<RealType>(0),  dist.trials());
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
       { // Mean of Binomial distribution = np.
         return  dist.trials() * dist.success_fraction();
       } // mean
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
       { // Variance of Binomial distribution = np(1-p).
         return  dist.trials() * dist.success_fraction() * (1 - dist.success_fraction());
       } // variance
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_GPU_ENABLED RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Probability Density/Mass Function.
         BOOST_FPU_EXCEPTION_GUARD
 
@@ -502,7 +502,7 @@ namespace boost
       } // pdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_GPU_ENABLED inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -574,7 +574,7 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -651,19 +651,19 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
       {
          return binomial_detail::quantile_imp(dist, p, RealType(1-p), false);
       } // quantile
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       {
          return binomial_detail::quantile_imp(c.dist, RealType(1-c.param), c.param, true);
       } // quantile
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -672,7 +672,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType median(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType median(const binomial_distribution<RealType, Policy>& dist)
       { // Bounds for the median of the negative binomial distribution
         // VAN DE VEN R. ; WEBER N. C. ;
         // Univ. Sydney, school mathematics statistics, Sydney N.S.W. 2006, AUSTRALIE
@@ -690,7 +690,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -699,7 +699,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType n = dist.trials();
@@ -707,7 +707,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_HOST_DEVICE inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType q = 1 - p;
diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index cd604aad39..e742eaf3d0 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -199,7 +199,7 @@ void raise_error(const char* pfunction, const char* pmessage, const T& val)
 #endif
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
+BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
            const char* function,
            const char* message,
            const T& val,
@@ -215,7 +215,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_domain_error(
            const char* ,
            const char* ,
            const T& ,
@@ -227,7 +227,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
+BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
            const char* ,
            const char* ,
            const T& ,
@@ -240,7 +240,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
+BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
            const char* function,
            const char* message,
            const T& val,
@@ -250,7 +250,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_domain_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
+BOOST_MATH_GPU_ENABLED inline T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -264,7 +264,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -274,7 +274,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -284,7 +284,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
+BOOST_MATH_GPU_ENABLED inline T raise_pole_error(
            const char* function,
            const char* message,
            const T& val,
@@ -294,7 +294,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_pole_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::throw_on_error>&)
@@ -309,7 +309,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* function,
            const char* message,
            const T& val,
@@ -325,7 +325,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -336,7 +336,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
            const char* ,
            const char* ,
            const T&,
@@ -348,7 +348,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -360,7 +360,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* ,
            const char* ,
            const T&,
@@ -373,7 +373,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::user_error>&)
@@ -382,7 +382,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* function,
            const char* message,
            const T& val,
@@ -396,7 +396,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_overflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_underflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::throw_on_error>&)
@@ -411,7 +411,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_underflow_error(
            const char* ,
            const char* ,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -422,7 +422,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_underflow_error(
            const char* /* function */,
            const char* /* message */,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
@@ -434,7 +434,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
+BOOST_MATH_GPU_ENABLED inline T raise_underflow_error(
            const char* function,
            const char* message,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::user_error>&)
@@ -443,7 +443,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_underflow_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
+BOOST_MATH_GPU_ENABLED inline T raise_denorm_error(
            const char* function,
            const char* message,
            const T& /* val */,
@@ -459,7 +459,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline constexpr T raise_denorm_error(
+BOOST_MATH_GPU_ENABLED inline constexpr T raise_denorm_error(
            const char* ,
            const char* ,
            const T&  val,
@@ -471,7 +471,7 @@ BOOST_MATH_HOST_DEVICE inline constexpr T raise_denorm_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
+BOOST_MATH_GPU_ENABLED inline T raise_denorm_error(
            const char* ,
            const char* ,
            const T& val,
@@ -484,7 +484,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
+BOOST_MATH_GPU_ENABLED inline T raise_denorm_error(
            const char* function,
            const char* message,
            const T& val,
@@ -494,7 +494,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_denorm_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
+BOOST_MATH_GPU_ENABLED inline T raise_evaluation_error(
            const char* function,
            const char* message,
            const T& val,
@@ -510,7 +510,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(
+BOOST_MATH_GPU_ENABLED constexpr T raise_evaluation_error(
            const char* ,
            const char* ,
            const T& val,
@@ -522,7 +522,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
+BOOST_MATH_GPU_ENABLED inline T raise_evaluation_error(
            const char* ,
            const char* ,
            const T& val,
@@ -535,7 +535,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
+BOOST_MATH_GPU_ENABLED inline T raise_evaluation_error(
            const char* function,
            const char* message,
            const T& val,
@@ -545,7 +545,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_evaluation_error(
 }
 
 template <class T, class TargetType>
-BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
+BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
            const char* function,
            const char* message,
            const T& val,
@@ -562,7 +562,7 @@ BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
 }
 
 template <class T, class TargetType>
-BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(
+BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(
            const char* ,
            const char* ,
            const T& val,
@@ -576,7 +576,7 @@ BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(
 }
 
 template <class T, class TargetType>
-BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
+BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
            const char* ,
            const char* ,
            const T& val,
@@ -590,7 +590,7 @@ BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
    return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
 }
 template <class T, class TargetType>
-BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
+BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
            const char* function,
            const char* message,
            const T& val,
@@ -601,7 +601,7 @@ BOOST_MATH_HOST_DEVICE inline TargetType raise_rounding_error(
 }
 
 template <class T, class R>
-BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
+BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
            const char* function,
            const char* message,
            const T& val,
@@ -618,7 +618,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-BOOST_MATH_HOST_DEVICE inline constexpr T raise_indeterminate_result_error(
+BOOST_MATH_GPU_ENABLED inline constexpr T raise_indeterminate_result_error(
            const char* ,
            const char* ,
            const T& ,
@@ -631,7 +631,7 @@ BOOST_MATH_HOST_DEVICE inline constexpr T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
+BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
            const char* ,
            const char* ,
            const T& ,
@@ -645,7 +645,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
 }
 
 template <class T, class R>
-BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
+BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
            const char* function,
            const char* message,
            const T& val,
@@ -658,7 +658,7 @@ BOOST_MATH_HOST_DEVICE inline T raise_indeterminate_result_error(
 }  // namespace detail
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_domain_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::domain_error_type policy_type;
    return detail::raise_domain_error(
@@ -667,7 +667,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_domain_error(const char* function, cons
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_pole_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::pole_error_type policy_type;
    return detail::raise_pole_error(
@@ -676,7 +676,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_pole_error(const char* function, const
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::overflow_error_type policy_type;
    return detail::raise_overflow_error<T>(
@@ -685,7 +685,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, co
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::overflow_error_type policy_type;
    return detail::raise_overflow_error(
@@ -694,7 +694,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_overflow_error(const char* function, co
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_underflow_error(const char* function, const char* message, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::underflow_error_type policy_type;
    return detail::raise_underflow_error<T>(
@@ -703,7 +703,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_underflow_error(const char* function, c
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_denorm_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_denorm_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::denorm_error_type policy_type;
    return detail::raise_denorm_error<T>(
@@ -713,7 +713,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_denorm_error(const char* function, cons
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_evaluation_error(const char* function, const char* message, const T& val, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::evaluation_error_type policy_type;
    return detail::raise_evaluation_error(
@@ -722,7 +722,7 @@ BOOST_MATH_HOST_DEVICE constexpr T raise_evaluation_error(const char* function,
 }
 
 template <class T, class TargetType, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(const char* function, const char* message, const T& val, const TargetType& t, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(const char* function, const char* message, const T& val, const TargetType& t, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::rounding_error_type policy_type;
    return detail::raise_rounding_error(
@@ -731,7 +731,7 @@ BOOST_MATH_HOST_DEVICE constexpr TargetType raise_rounding_error(const char* fun
 }
 
 template <class T, class R, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T raise_indeterminate_result_error(const char* function, const char* message, const T& val, const R& result, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED constexpr T raise_indeterminate_result_error(const char* function, const char* message, const T& val, const R& result, const Policy&) noexcept(is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T))
 {
    typedef typename Policy::indeterminate_result_error_type policy_type;
    return detail::raise_indeterminate_result_error(
@@ -746,7 +746,7 @@ namespace detail
 {
 
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    BOOST_MATH_STD_USING
    if(fabs(val) > tools::max_value<R>())
@@ -758,7 +758,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(T val, R* resu
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -768,7 +768,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_overflow(std::complex<T
    return r;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    if((val != 0) && (static_cast<R>(val) == 0))
    {
@@ -778,7 +778,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(T val, R* res
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -788,7 +788,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_underflow(std::complex<
    return r;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    BOOST_MATH_STD_USING
    if((fabs(val) < static_cast<T>(tools::min_value<R>())) && (static_cast<R>(val) != 0))
@@ -799,7 +799,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(T val, R* result
    return false;
 }
 template <class R, class T, class Policy>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T> val, R* result, const char* function, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && (Policy::value != throw_on_error) && (Policy::value != user_error))
 {
    typedef typename R::value_type r_type;
    r_type re, im;
@@ -811,28 +811,28 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE bool check_denorm(std::complex<T>
 
 // Default instantiations with ignore_error policy.
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_overflow(T /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_overflow(T /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_overflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_overflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const overflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_underflow(T /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_underflow(T /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_underflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_underflow(std::complex<T> /* val */, R* /* result */, const char* /* function */, const underflow_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_denorm(T /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_denorm(T /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 template <class R, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE constexpr bool check_denorm(std::complex<T> /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE constexpr bool check_denorm(std::complex<T> /* val */, R* /* result*/, const char* /* function */, const denorm_error<ignore_error>&) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T))
 { return false; }
 
 } // namespace detail
 
 template <class R, class Policy, class T>
-BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noexcept(BOOST_MATH_IS_FLOAT(R) && BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    typedef typename Policy::overflow_error_type overflow_type;
    typedef typename Policy::underflow_error_type underflow_type;
@@ -852,7 +852,7 @@ BOOST_MATH_HOST_DEVICE BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, co
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE inline void check_series_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_GPU_ENABLED inline void check_series_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    if(max_iter >= policies::get_max_series_iterations<Policy>())
       raise_evaluation_error<T>(
@@ -861,7 +861,7 @@ BOOST_MATH_HOST_DEVICE inline void check_series_iterations(const char* function,
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE inline void check_root_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
+BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, std::uintmax_t max_iter, const Policy& pol) noexcept(BOOST_MATH_IS_FLOAT(T) && is_noexcept_error_policy<Policy>::value)
 {
    if(max_iter >= policies::get_max_root_iterations<Policy>())
       raise_evaluation_error<T>(
@@ -878,7 +878,7 @@ namespace detail{
 // that value usually comes from one of the error handlers above:
 //
 template <class T>
-BOOST_MATH_HOST_DEVICE std::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED std::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
 {
    return std::make_pair(val, val);
 }
diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index 25a43f41e6..5f3dfa7b50 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -22,9 +22,9 @@ namespace mp = tools::meta_programming;
 namespace tools{
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept;
+BOOST_MATH_GPU_ENABLED constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept;
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value);
+BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value);
 
 }
 
@@ -640,81 +640,81 @@ struct normalise<policy<detail::forwarding_arg1, detail::forwarding_arg2>,
    using type = policy<detail::forwarding_arg1, detail::forwarding_arg2>;
 };
 
-BOOST_MATH_HOST_DEVICE constexpr policy<> make_policy() noexcept
+BOOST_MATH_GPU_ENABLED constexpr policy<> make_policy() noexcept
 { return {}; }
 
 template <class A1>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1>::type make_policy(const A1&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1>::type make_policy(const A1&) noexcept
 {
    typedef typename normalise<policy<>, A1>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2>::type make_policy(const A1&, const A2&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2>::type make_policy(const A1&, const A2&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3>::type make_policy(const A1&, const A2&, const A3&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3>::type make_policy(const A1&, const A2&, const A3&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4>::type make_policy(const A1&, const A2&, const A3&, const A4&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4>::type make_policy(const A1&, const A2&, const A3&, const A4&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9, class A10>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10>::type result_type;
    return result_type();
 }
 
 template <class A1, class A2, class A3, class A4, class A5, class A6, class A7, class A8, class A9, class A10, class A11>
-BOOST_MATH_HOST_DEVICE constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&, const A11&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type make_policy(const A1&, const A2&, const A3&, const A4&, const A5&, const A6&, const A7&, const A8&, const A9&, const A10&, const A11&) noexcept
 {
    typedef typename normalise<policy<>, A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11>::type result_type;
    return result_type();
@@ -793,7 +793,7 @@ struct precision<BOOST_MATH_FLOAT128_TYPE, Policy>
 namespace detail{
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::true_type const&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits_imp(std::true_type const&) noexcept
 {
    static_assert( std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
    typedef typename boost::math::policies::precision<T, Policy>::type p_t;
@@ -801,7 +801,7 @@ BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::true_type const&) noexcept
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::false_type const&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits_imp(std::false_type const&) noexcept
 {
    return tools::digits<T>();
 }
@@ -809,26 +809,26 @@ BOOST_MATH_HOST_DEVICE constexpr int digits_imp(std::false_type const&) noexcept
 } // namespace detail
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
 {
    typedef std::integral_constant<bool, std::numeric_limits<T>::is_specialized > tag_type;
    return detail::digits_imp<T, Policy>(tag_type());
 }
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr int digits_base10(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits_base10(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
 {
    return boost::math::policies::digits<T, Policy>() * 301 / 1000L;
 }
 
 template <class Policy>
-BOOST_MATH_HOST_DEVICE constexpr unsigned long get_max_series_iterations() noexcept
+BOOST_MATH_GPU_ENABLED constexpr unsigned long get_max_series_iterations() noexcept
 {
    typedef typename Policy::max_series_iterations_type iter_type;
    return iter_type::value;
 }
 
 template <class Policy>
-BOOST_MATH_HOST_DEVICE constexpr unsigned long get_max_root_iterations() noexcept
+BOOST_MATH_GPU_ENABLED constexpr unsigned long get_max_root_iterations() noexcept
 {
    typedef typename Policy::max_root_iterations_type iter_type;
    return iter_type::value;
@@ -839,7 +839,7 @@ namespace detail{
 template <class T, class Digits, class Small, class Default>
 struct series_factor_calc
 {
-   BOOST_MATH_HOST_DEVICE static T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static T get() noexcept(std::is_floating_point<T>::value)
    {
       return ldexp(T(1.0), 1 - Digits::value);
    }
@@ -848,7 +848,7 @@ struct series_factor_calc
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::true_type, std::true_type>
 {
-   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
@@ -856,7 +856,7 @@ struct series_factor_calc<T, Digits, std::true_type, std::true_type>
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::true_type, std::false_type>
 {
-   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return 1 / static_cast<T>(static_cast<std::uintmax_t>(1u) << (Digits::value - 1));
    }
@@ -864,14 +864,14 @@ struct series_factor_calc<T, Digits, std::true_type, std::false_type>
 template <class T, class Digits>
 struct series_factor_calc<T, Digits, std::false_type, std::true_type>
 {
-   BOOST_MATH_HOST_DEVICE static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
 };
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_floating_point<T>::value)
 {
    static_assert(std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
    static_assert(std::numeric_limits<T>::radix == 2, "std::numeric_limits<T>::radix == 2");
@@ -883,7 +883,7 @@ BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::true_type const&) noexce
 }
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floating_point<T>::value)
 {
    return tools::epsilon<T>();
 }
@@ -891,7 +891,7 @@ BOOST_MATH_HOST_DEVICE constexpr T get_epsilon_imp(std::false_type const&) noexc
 } // namespace detail
 
 template <class T, class Policy>
-BOOST_MATH_HOST_DEVICE constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    typedef std::integral_constant<bool, (std::numeric_limits<T>::is_specialized && (std::numeric_limits<T>::radix == 2)) > tag_type;
    return detail::get_epsilon_imp<T, Policy>(tag_type());
diff --git a/include/boost/math/special_functions/fpclassify.hpp b/include/boost/math/special_functions/fpclassify.hpp
index 617d818488..ed75fa35df 100644
--- a/include/boost/math/special_functions/fpclassify.hpp
+++ b/include/boost/math/special_functions/fpclassify.hpp
@@ -77,31 +77,31 @@ is used.
 
 */
 
-#ifdef BOOST_MATH_ENABLE_CUDA
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
 
 namespace boost { namespace math {
 
-template<> inline BOOST_MATH_HOST_DEVICE bool (isnan)(float x) { return x != x; }
-template<> inline BOOST_MATH_HOST_DEVICE bool (isnan)(double x) { return x != x; }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isnan)(float x) { return x != x; }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isnan)(double x) { return x != x; }
 
-template<> inline BOOST_MATH_HOST_DEVICE bool (isinf)(float x) { return x > FLT_MAX || x < -FLT_MAX; }
-template<> inline BOOST_MATH_HOST_DEVICE bool (isinf)(double x) { return x > DBL_MAX || x < -DBL_MAX; }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isinf)(float x) { return x > FLT_MAX || x < -FLT_MAX; }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isinf)(double x) { return x > DBL_MAX || x < -DBL_MAX; }
 
-template<> inline BOOST_MATH_HOST_DEVICE bool (isfinite)(float x) {  return !isnan(x) && !isinf(x);  }
-template<> inline BOOST_MATH_HOST_DEVICE bool (isfinite)(double x) {  return !isnan(x) && !isinf(x); }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isfinite)(float x) {  return !isnan(x) && !isinf(x);  }
+template<> inline BOOST_MATH_GPU_ENABLED bool (isfinite)(double x) {  return !isnan(x) && !isinf(x); }
 
-template<> inline BOOST_MATH_HOST_DEVICE bool (isnormal)(float x)
+template<> inline BOOST_MATH_GPU_ENABLED bool (isnormal)(float x)
 {
    if(x < 0) x = -x;
    return (x >= FLT_MIN) && (x <= FLT_MAX);
 }
-template<> inline BOOST_MATH_HOST_DEVICE bool (isnormal)(double x)
+template<> inline BOOST_MATH_GPU_ENABLED bool (isnormal)(double x)
 {
    if(x < 0) x = -x;
    return (x >= DBL_MIN) && (x <= DBL_MAX);
 }
 
-template<> inline BOOST_MATH_HOST_DEVICE int (fpclassify)(float t)
+template<> inline BOOST_MATH_GPU_ENABLED int (fpclassify)(float t)
 {
    if((boost::math::isnan)(t))
       return FP_NAN;
@@ -125,7 +125,7 @@ template<> inline BOOST_MATH_HOST_DEVICE int (fpclassify)(float t)
    return FP_NAN;
 }
 
-template<> inline BOOST_MATH_HOST_DEVICE int (fpclassify)(double t)
+template<> inline BOOST_MATH_GPU_ENABLED int (fpclassify)(double t)
 {
    if((boost::math::isnan)(t))
       return FP_NAN;
diff --git a/include/boost/math/tools/polynomial.hpp b/include/boost/math/tools/polynomial.hpp
index 8d87fbf68c..5d395cdbed 100644
--- a/include/boost/math/tools/polynomial.hpp
+++ b/include/boost/math/tools/polynomial.hpp
@@ -32,7 +32,7 @@
 namespace boost{ namespace math{ namespace tools{
 
 template <class T>
-BOOST_MATH_HOST_DEVICE T chebyshev_coefficient(unsigned n, unsigned m)
+BOOST_MATH_GPU_ENABLED T chebyshev_coefficient(unsigned n, unsigned m)
 {
    BOOST_MATH_STD_USING
    if(m > n)
@@ -56,7 +56,7 @@ BOOST_MATH_HOST_DEVICE T chebyshev_coefficient(unsigned n, unsigned m)
 }
 
 template <class Seq>
-BOOST_MATH_HOST_DEVICE Seq polynomial_to_chebyshev(const Seq& s)
+BOOST_MATH_GPU_ENABLED Seq polynomial_to_chebyshev(const Seq& s)
 {
    // Converts a Polynomial into Chebyshev form:
    typedef typename Seq::value_type value_type;
@@ -92,7 +92,7 @@ BOOST_MATH_HOST_DEVICE Seq polynomial_to_chebyshev(const Seq& s)
 }
 
 template <class Seq, class T>
-BOOST_MATH_HOST_DEVICE T evaluate_chebyshev(const Seq& a, const T& x)
+BOOST_MATH_GPU_ENABLED T evaluate_chebyshev(const Seq& a, const T& x)
 {
    // Clenshaw's formula:
    typedef typename Seq::difference_type difference_type;
@@ -124,7 +124,7 @@ namespace detail {
 * subtlety of distinction.
 */
 template <typename T, typename N>
-BOOST_MATH_HOST_DEVICE typename std::enable_if<!std::numeric_limits<T>::is_integer, void >::type
+BOOST_MATH_GPU_ENABLED typename std::enable_if<!std::numeric_limits<T>::is_integer, void >::type
 division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N k)
 {
     q[k] = u[n + k] / v[n];
@@ -136,7 +136,7 @@ division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N
 }
 
 template <class T, class N>
-BOOST_MATH_HOST_DEVICE T integer_power(T t, N n)
+BOOST_MATH_GPU_ENABLED T integer_power(T t, N n)
 {
    switch(n)
    {
@@ -167,7 +167,7 @@ BOOST_MATH_HOST_DEVICE T integer_power(T t, N n)
 * don't currently have that subtlety of distinction.
 */
 template <typename T, typename N>
-BOOST_MATH_HOST_DEVICE typename std::enable_if<std::numeric_limits<T>::is_integer, void >::type
+BOOST_MATH_GPU_ENABLED typename std::enable_if<std::numeric_limits<T>::is_integer, void >::type
 division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N k)
 {
     q[k] = u[n + k] * integer_power(v[n], k);
@@ -187,7 +187,7 @@ division_impl(polynomial<T> &q, polynomial<T> &u, const polynomial<T>& v, N n, N
  * @param   v   Divisor.
  */
 template <typename T>
-BOOST_MATH_HOST_DEVICE std::pair< polynomial<T>, polynomial<T> >
+BOOST_MATH_GPU_ENABLED std::pair< polynomial<T>, polynomial<T> >
 division(polynomial<T> u, const polynomial<T>& v)
 {
     BOOST_MATH_ASSERT(v.size() <= u.size());
@@ -218,7 +218,7 @@ division(polynomial<T> u, const polynomial<T>& v)
 struct negate
 {
    template <class T>
-   BOOST_MATH_HOST_DEVICE T operator()(T const &x) const
+   BOOST_MATH_GPU_ENABLED T operator()(T const &x) const
    {
       return -x;
    }
@@ -227,7 +227,7 @@ struct negate
 struct plus
 {
    template <class T, class U>
-   BOOST_MATH_HOST_DEVICE T operator()(T const &x, U const& y) const
+   BOOST_MATH_GPU_ENABLED T operator()(T const &x, U const& y) const
    {
       return x + y;
    }
@@ -236,7 +236,7 @@ struct plus
 struct minus
 {
    template <class T, class U>
-   BOOST_MATH_HOST_DEVICE T operator()(T const &x, U const& y) const
+   BOOST_MATH_GPU_ENABLED T operator()(T const &x, U const& y) const
    {
       return x - y;
    }
@@ -248,13 +248,13 @@ struct minus
  * Returns the zero element for multiplication of polynomials.
  */
 template <class T>
-BOOST_MATH_HOST_DEVICE polynomial<T> zero_element(std::multiplies< polynomial<T> >)
+BOOST_MATH_GPU_ENABLED polynomial<T> zero_element(std::multiplies< polynomial<T> >)
 {
     return polynomial<T>();
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE polynomial<T> identity_element(std::multiplies< polynomial<T> >)
+BOOST_MATH_GPU_ENABLED polynomial<T> identity_element(std::multiplies< polynomial<T> >)
 {
     return polynomial<T>(T(1));
 }
@@ -264,7 +264,7 @@ BOOST_MATH_HOST_DEVICE polynomial<T> identity_element(std::multiplies< polynomia
  * This function is not defined for division by zero: user beware.
  */
 template <typename T>
-BOOST_MATH_HOST_DEVICE std::pair< polynomial<T>, polynomial<T> >
+BOOST_MATH_GPU_ENABLED std::pair< polynomial<T>, polynomial<T> >
 quotient_remainder(const polynomial<T>& dividend, const polynomial<T>& divisor)
 {
     BOOST_MATH_ASSERT(divisor);
@@ -283,51 +283,51 @@ class polynomial
    typedef typename std::vector<T>::size_type size_type;
 
    // construct:
-   BOOST_MATH_HOST_DEVICE polynomial()= default;
+   BOOST_MATH_GPU_ENABLED polynomial()= default;
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE polynomial(const U* data, unsigned order)
+   BOOST_MATH_GPU_ENABLED polynomial(const U* data, unsigned order)
       : m_data(data, data + order + 1)
    {
        normalize();
    }
 
    template <class Iterator>
-   BOOST_MATH_HOST_DEVICE polynomial(Iterator first, Iterator last)
+   BOOST_MATH_GPU_ENABLED polynomial(Iterator first, Iterator last)
       : m_data(first, last)
    {
        normalize();
    }
 
    template <class Iterator>
-   BOOST_MATH_HOST_DEVICE polynomial(Iterator first, unsigned length)
+   BOOST_MATH_GPU_ENABLED polynomial(Iterator first, unsigned length)
       : m_data(first, std::next(first, length + 1))
    {
        normalize();
    }
 
-   BOOST_MATH_HOST_DEVICE polynomial(std::vector<T>&& p) : m_data(std::move(p))
+   BOOST_MATH_GPU_ENABLED polynomial(std::vector<T>&& p) : m_data(std::move(p))
    {
       normalize();
    }
 
    template <class U, typename std::enable_if<std::is_convertible<U, T>::value, bool>::type = true>
-   BOOST_MATH_HOST_DEVICE explicit polynomial(const U& point)
+   BOOST_MATH_GPU_ENABLED explicit polynomial(const U& point)
    {
        if (point != U(0))
           m_data.push_back(point);
    }
 
    // move:
-   BOOST_MATH_HOST_DEVICE polynomial(polynomial&& p) noexcept
+   BOOST_MATH_GPU_ENABLED polynomial(polynomial&& p) noexcept
       : m_data(std::move(p.m_data)) { }
 
    // copy:
-   BOOST_MATH_HOST_DEVICE polynomial(const polynomial& p)
+   BOOST_MATH_GPU_ENABLED polynomial(const polynomial& p)
       : m_data(p.m_data) { }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE polynomial(const polynomial<U>& p)
+   BOOST_MATH_GPU_ENABLED polynomial(const polynomial<U>& p)
    {
       m_data.resize(p.size());
       for(unsigned i = 0; i < p.size(); ++i)
@@ -337,17 +337,17 @@ class polynomial
    }
 #ifdef BOOST_MATH_HAS_IS_CONST_ITERABLE
     template <class Range, typename std::enable_if<boost::math::tools::detail::is_const_iterable<Range>::value, bool>::type = true>
-    BOOST_MATH_HOST_DEVICE explicit polynomial(const Range& r)
+    BOOST_MATH_GPU_ENABLED explicit polynomial(const Range& r)
        : polynomial(r.begin(), r.end()) 
     {
     }
 #endif
-    BOOST_MATH_HOST_DEVICE polynomial(std::initializer_list<T> l) : polynomial(std::begin(l), std::end(l))
+    BOOST_MATH_GPU_ENABLED polynomial(std::initializer_list<T> l) : polynomial(std::begin(l), std::end(l))
     {
     }
 
     polynomial&
-    BOOST_MATH_HOST_DEVICE operator=(std::initializer_list<T> l)
+    BOOST_MATH_GPU_ENABLED operator=(std::initializer_list<T> l)
     {
         m_data.assign(std::begin(l), std::end(l));
         normalize();
@@ -356,47 +356,47 @@ class polynomial
 
 
    // access:
-   BOOST_MATH_HOST_DEVICE size_type size() const { return m_data.size(); }
-   BOOST_MATH_HOST_DEVICE size_type degree() const
+   BOOST_MATH_GPU_ENABLED size_type size() const { return m_data.size(); }
+   BOOST_MATH_GPU_ENABLED size_type degree() const
    {
        if (size() == 0)
           BOOST_MATH_THROW_EXCEPTION(std::logic_error("degree() is undefined for the zero polynomial."));
        return m_data.size() - 1;
    }
-   BOOST_MATH_HOST_DEVICE value_type& operator[](size_type i)
+   BOOST_MATH_GPU_ENABLED value_type& operator[](size_type i)
    {
       return m_data[i];
    }
-   BOOST_MATH_HOST_DEVICE const value_type& operator[](size_type i) const
+   BOOST_MATH_GPU_ENABLED const value_type& operator[](size_type i) const
    {
       return m_data[i];
    }
 
-   BOOST_MATH_HOST_DEVICE T evaluate(T z) const
+   BOOST_MATH_GPU_ENABLED T evaluate(T z) const
    {
       return this->operator()(z);
    }
 
-   BOOST_MATH_HOST_DEVICE T operator()(T z) const
+   BOOST_MATH_GPU_ENABLED T operator()(T z) const
    {
       return m_data.size() > 0 ? boost::math::tools::evaluate_polynomial((m_data).data(), z, m_data.size()) : T(0);
    }
-   BOOST_MATH_HOST_DEVICE std::vector<T> chebyshev() const
+   BOOST_MATH_GPU_ENABLED std::vector<T> chebyshev() const
    {
       return polynomial_to_chebyshev(m_data);
    }
 
-   BOOST_MATH_HOST_DEVICE std::vector<T> const& data() const
+   BOOST_MATH_GPU_ENABLED std::vector<T> const& data() const
    {
        return m_data;
    }
 
-   BOOST_MATH_HOST_DEVICE std::vector<T> & data()
+   BOOST_MATH_GPU_ENABLED std::vector<T> & data()
    {
        return m_data;
    }
 
-   BOOST_MATH_HOST_DEVICE polynomial<T> prime() const
+   BOOST_MATH_GPU_ENABLED polynomial<T> prime() const
    {
 #ifdef _MSC_VER
       // Disable int->float conversion warning:
@@ -418,7 +418,7 @@ class polynomial
 #endif
    }
 
-   BOOST_MATH_HOST_DEVICE polynomial<T> integrate() const
+   BOOST_MATH_GPU_ENABLED polynomial<T> integrate() const
    {
       std::vector<T> i_data(m_data.size() + 1);
       // Choose integration constant such that P(0) = 0.
@@ -431,20 +431,20 @@ class polynomial
    }
 
    // operators:
-   BOOST_MATH_HOST_DEVICE polynomial& operator =(polynomial&& p) noexcept
+   BOOST_MATH_GPU_ENABLED polynomial& operator =(polynomial&& p) noexcept
    {
        m_data = std::move(p.m_data);
        return *this;
    }
 
-   BOOST_MATH_HOST_DEVICE polynomial& operator =(const polynomial& p)
+   BOOST_MATH_GPU_ENABLED polynomial& operator =(const polynomial& p)
    {
        m_data = p.m_data;
        return *this;
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator +=(const U& value)
+   BOOST_MATH_GPU_ENABLED typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator +=(const U& value)
    {
        addition(value);
        normalize();
@@ -452,7 +452,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator -=(const U& value)
+   BOOST_MATH_GPU_ENABLED typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator -=(const U& value)
    {
        subtraction(value);
        normalize();
@@ -460,7 +460,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator *=(const U& value)
+   BOOST_MATH_GPU_ENABLED typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator *=(const U& value)
    {
       multiplication(value);
       normalize();
@@ -468,7 +468,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator /=(const U& value)
+   BOOST_MATH_GPU_ENABLED typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator /=(const U& value)
    {
        division(value);
        normalize();
@@ -476,7 +476,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator %=(const U& /*value*/)
+   BOOST_MATH_GPU_ENABLED typename std::enable_if<std::is_constructible<T, U>::value, polynomial&>::type operator %=(const U& /*value*/)
    {
        // We can always divide by a scalar, so there is no remainder:
        this->set_zero();
@@ -484,7 +484,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator +=(const polynomial<U>& value)
+   BOOST_MATH_GPU_ENABLED polynomial& operator +=(const polynomial<U>& value)
    {
       addition(value);
       normalize();
@@ -492,7 +492,7 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator -=(const polynomial<U>& value)
+   BOOST_MATH_GPU_ENABLED polynomial& operator -=(const polynomial<U>& value)
    {
        subtraction(value);
        normalize();
@@ -500,7 +500,7 @@ class polynomial
    }
 
    template <typename U, typename V>
-   BOOST_MATH_HOST_DEVICE void multiply(const polynomial<U>& a, const polynomial<V>& b) {
+   BOOST_MATH_GPU_ENABLED void multiply(const polynomial<U>& a, const polynomial<V>& b) {
        if (!a || !b)
        {
            this->set_zero();
@@ -514,28 +514,28 @@ class polynomial
    }
 
    template <class U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator *=(const polynomial<U>& value)
+   BOOST_MATH_GPU_ENABLED polynomial& operator *=(const polynomial<U>& value)
    {
       this->multiply(*this, value);
       return *this;
    }
 
    template <typename U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator /=(const polynomial<U>& value)
+   BOOST_MATH_GPU_ENABLED polynomial& operator /=(const polynomial<U>& value)
    {
        *this = quotient_remainder(*this, value).first;
        return *this;
    }
 
    template <typename U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator %=(const polynomial<U>& value)
+   BOOST_MATH_GPU_ENABLED polynomial& operator %=(const polynomial<U>& value)
    {
        *this = quotient_remainder(*this, value).second;
        return *this;
    }
 
    template <typename U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator >>=(U const &n)
+   BOOST_MATH_GPU_ENABLED polynomial& operator >>=(U const &n)
    {
        BOOST_MATH_ASSERT(n <= m_data.size());
        m_data.erase(m_data.begin(), m_data.begin() + n);
@@ -543,7 +543,7 @@ class polynomial
    }
 
    template <typename U>
-   BOOST_MATH_HOST_DEVICE polynomial& operator <<=(U const &n)
+   BOOST_MATH_GPU_ENABLED polynomial& operator <<=(U const &n)
    {
        m_data.insert(m_data.begin(), n, static_cast<T>(0));
        normalize();
@@ -551,33 +551,33 @@ class polynomial
    }
 
    // Convenient and efficient query for zero.
-   BOOST_MATH_HOST_DEVICE bool is_zero() const
+   BOOST_MATH_GPU_ENABLED bool is_zero() const
    {
        return m_data.empty();
    }
 
    // Conversion to bool.
-   BOOST_MATH_HOST_DEVICE inline explicit operator bool() const
+   BOOST_MATH_GPU_ENABLED inline explicit operator bool() const
    {
        return !m_data.empty();
    }
 
    // Fast way to set a polynomial to zero.
-   BOOST_MATH_HOST_DEVICE void set_zero()
+   BOOST_MATH_GPU_ENABLED void set_zero()
    {
        m_data.clear();
    }
 
     /** Remove zero coefficients 'from the top', that is for which there are no
     *        non-zero coefficients of higher degree. */
-   BOOST_MATH_HOST_DEVICE void normalize()
+   BOOST_MATH_GPU_ENABLED void normalize()
    {
       m_data.erase(std::find_if(m_data.rbegin(), m_data.rend(), [](const T& x)->bool { return x != T(0); }).base(), m_data.end());
    }
 
 private:
     template <class U, class R>
-    BOOST_MATH_HOST_DEVICE polynomial& addition(const U& value, R op)
+    BOOST_MATH_GPU_ENABLED polynomial& addition(const U& value, R op)
     {
         if(m_data.size() == 0)
             m_data.resize(1, 0);
@@ -586,19 +586,19 @@ class polynomial
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& addition(const U& value)
+    BOOST_MATH_GPU_ENABLED polynomial& addition(const U& value)
     {
         return addition(value, detail::plus());
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& subtraction(const U& value)
+    BOOST_MATH_GPU_ENABLED polynomial& subtraction(const U& value)
     {
         return addition(value, detail::minus());
     }
 
     template <class U, class R>
-    BOOST_MATH_HOST_DEVICE polynomial& addition(const polynomial<U>& value, R op)
+    BOOST_MATH_GPU_ENABLED polynomial& addition(const polynomial<U>& value, R op)
     {
         if (m_data.size() < value.size())
             m_data.resize(value.size(), 0);
@@ -608,26 +608,26 @@ class polynomial
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& addition(const polynomial<U>& value)
+    BOOST_MATH_GPU_ENABLED polynomial& addition(const polynomial<U>& value)
     {
         return addition(value, detail::plus());
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& subtraction(const polynomial<U>& value)
+    BOOST_MATH_GPU_ENABLED polynomial& subtraction(const polynomial<U>& value)
     {
         return addition(value, detail::minus());
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& multiplication(const U& value)
+    BOOST_MATH_GPU_ENABLED polynomial& multiplication(const U& value)
     {
        std::transform(m_data.begin(), m_data.end(), m_data.begin(), [&](const T& x)->T { return x * value; });
        return *this;
     }
 
     template <class U>
-    BOOST_MATH_HOST_DEVICE polynomial& division(const U& value)
+    BOOST_MATH_GPU_ENABLED polynomial& division(const U& value)
     {
        std::transform(m_data.begin(), m_data.end(), m_data.begin(), [&](const T& x)->T { return x / value; });
        return *this;
@@ -638,7 +638,7 @@ class polynomial
 
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator + (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result(a);
    result += b;
@@ -646,26 +646,26 @@ BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (const polynomial<T>& a,
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (polynomial<T>&& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator + (polynomial<T>&& a, const polynomial<T>& b)
 {
    a += b;
    return std::move(a);
 }
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (const polynomial<T>& a, polynomial<T>&& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator + (const polynomial<T>& a, polynomial<T>&& b)
 {
    b += a;
    return b;
 }
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator + (polynomial<T>&& a, polynomial<T>&& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator + (polynomial<T>&& a, polynomial<T>&& b)
 {
    a += b;
    return a;
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator - (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result(a);
    result -= b;
@@ -673,26 +673,26 @@ BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (const polynomial<T>& a,
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (polynomial<T>&& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator - (polynomial<T>&& a, const polynomial<T>& b)
 {
    a -= b;
    return a;
 }
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (const polynomial<T>& a, polynomial<T>&& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator - (const polynomial<T>& a, polynomial<T>&& b)
 {
    b -= a;
    return -b;
 }
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator - (polynomial<T>&& a, polynomial<T>&& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator - (polynomial<T>&& a, polynomial<T>&& b)
 {
    a -= b;
    return a;
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator * (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator * (const polynomial<T>& a, const polynomial<T>& b)
 {
    polynomial<T> result;
    result.multiply(a, b);
@@ -700,94 +700,94 @@ BOOST_MATH_HOST_DEVICE inline polynomial<T> operator * (const polynomial<T>& a,
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator / (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator / (const polynomial<T>& a, const polynomial<T>& b)
 {
    return quotient_remainder(a, b).first;
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE inline polynomial<T> operator % (const polynomial<T>& a, const polynomial<T>& b)
+BOOST_MATH_GPU_ENABLED inline polynomial<T> operator % (const polynomial<T>& a, const polynomial<T>& b)
 {
    return quotient_remainder(a, b).second;
 }
 
 template <class T, class U>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (polynomial<T> a, const U& b)
 {
    a += b;
    return a;
 }
 
 template <class T, class U>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (polynomial<T> a, const U& b)
 {
    a -= b;
    return a;
 }
 
 template <class T, class U>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (polynomial<T> a, const U& b)
 {
    a *= b;
    return a;
 }
 
 template <class T, class U>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator / (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator / (polynomial<T> a, const U& b)
 {
    a /= b;
    return a;
 }
 
 template <class T, class U>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator % (const polynomial<T>&, const U&)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator % (const polynomial<T>&, const U&)
 {
    // Since we can always divide by a scalar, result is always an empty polynomial:
    return polynomial<T>();
 }
 
 template <class U, class T>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (const U& a, polynomial<T> b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator + (const U& a, polynomial<T> b)
 {
    b += a;
    return b;
 }
 
 template <class U, class T>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (const U& a, polynomial<T> b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator - (const U& a, polynomial<T> b)
 {
    b -= a;
    return -b;
 }
 
 template <class U, class T>
-BOOST_MATH_HOST_DEVICE inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (const U& a, polynomial<T> b)
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<T, U>::value, polynomial<T> >::type operator * (const U& a, polynomial<T> b)
 {
    b *= a;
    return b;
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE bool operator == (const polynomial<T> &a, const polynomial<T> &b)
+BOOST_MATH_GPU_ENABLED bool operator == (const polynomial<T> &a, const polynomial<T> &b)
 {
     return a.data() == b.data();
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE bool operator != (const polynomial<T> &a, const polynomial<T> &b)
+BOOST_MATH_GPU_ENABLED bool operator != (const polynomial<T> &a, const polynomial<T> &b)
 {
     return a.data() != b.data();
 }
 
 template <typename T, typename U>
-BOOST_MATH_HOST_DEVICE polynomial<T> operator >> (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED polynomial<T> operator >> (polynomial<T> a, const U& b)
 {
     a >>= b;
     return a;
 }
 
 template <typename T, typename U>
-BOOST_MATH_HOST_DEVICE polynomial<T> operator << (polynomial<T> a, const U& b)
+BOOST_MATH_GPU_ENABLED polynomial<T> operator << (polynomial<T> a, const U& b)
 {
     a <<= b;
     return a;
@@ -795,26 +795,26 @@ BOOST_MATH_HOST_DEVICE polynomial<T> operator << (polynomial<T> a, const U& b)
 
 // Unary minus (negate).
 template <class T>
-BOOST_MATH_HOST_DEVICE polynomial<T> operator - (polynomial<T> a)
+BOOST_MATH_GPU_ENABLED polynomial<T> operator - (polynomial<T> a)
 {
     std::transform(a.data().begin(), a.data().end(), a.data().begin(), detail::negate());
     return a;
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE bool odd(polynomial<T> const &a)
+BOOST_MATH_GPU_ENABLED bool odd(polynomial<T> const &a)
 {
     return a.size() > 0 && a[0] != static_cast<T>(0);
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE bool even(polynomial<T> const &a)
+BOOST_MATH_GPU_ENABLED bool even(polynomial<T> const &a)
 {
     return !odd(a);
 }
 
 template <class T>
-BOOST_MATH_HOST_DEVICE polynomial<T> pow(polynomial<T> base, int exp)
+BOOST_MATH_GPU_ENABLED polynomial<T> pow(polynomial<T> base, int exp)
 {
     if (exp < 0)
         return policies::raise_domain_error(
@@ -838,7 +838,7 @@ BOOST_MATH_HOST_DEVICE polynomial<T> pow(polynomial<T> base, int exp)
 }
 
 template <class charT, class traits, class T>
-BOOST_MATH_HOST_DEVICE inline std::basic_ostream<charT, traits>& operator << (std::basic_ostream<charT, traits>& os, const polynomial<T>& poly)
+BOOST_MATH_GPU_ENABLED inline std::basic_ostream<charT, traits>& operator << (std::basic_ostream<charT, traits>& os, const polynomial<T>& poly)
 {
    os << "{ ";
    for(unsigned i = 0; i < poly.size(); ++i)
diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 8a2c2367a3..86b8e99824 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -143,16 +143,16 @@ constexpr T epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TY
    return std::numeric_limits<T>::epsilon();
 }
 
-#ifdef BOOST_MATH_ENABLE_CUDA
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
 
 template <>
-BOOST_MATH_HOST_DEVICE constexpr float epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
+BOOST_MATH_GPU_ENABLED constexpr float epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
 {
    return FLT_EPSILON;
 }
 
 template <>
-BOOST_MATH_HOST_DEVICE constexpr double epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
+BOOST_MATH_GPU_ENABLED constexpr double epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
 {
    return DBL_EPSILON;
 }
@@ -246,7 +246,7 @@ inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(
 #endif
 
 template <class T>
-BOOST_MATH_HOST_DEVICE constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(std::is_floating_point<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::epsilon<T>(std::integral_constant<bool, ::std::numeric_limits<T>::is_specialized>());

From 14d5b3b2f8df727dfc443af554e986acb0e08ca4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 16:32:57 -0400
Subject: [PATCH 032/399] Refactor macros for SYCL limited support

---
 include/boost/math/tools/config.hpp | 30 +++++++++++++++++++++++------
 1 file changed, 24 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index ae3716716d..eafe53fdc0 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -667,8 +667,9 @@ namespace boost{ namespace math{
 //
 
 #ifdef __CUDACC__
-#  define BOOST_MATH_GPU_ENABLED __host__ __device__
+#  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
+
 #  ifndef BOOST_MATH_ENABLE_CUDA
 #    define BOOST_MATH_ENABLE_CUDA
 #  endif
@@ -687,25 +688,42 @@ namespace boost{ namespace math{
 
 #elif defined(SYCL_LANGUAGE_VERSION)
 
-#  define BOOST_MATH_GPU_ENABLED SYCL_EXTERNAL
+#  define BOOST_MATH_SYCL_ENABLED SYCL_EXTERNAL
 #  define BOOST_MATH_HAS_GPU_SUPPORT
 
+#  ifndef BOOST_MATH_ENABLE_SYCL
+#    define BOOST_MATH_ENABLE_SYCL
+#  endif
+
 #  ifndef BOOST_MATH_NO_EXCEPTIONS
 #    define BOOST_MATH_NO_EXCEPTIONS
 #  endif
 
+// spir64 does not support long double
+#  define BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+
 #  undef BOOST_MATH_FORCEINLINE
-#  define BOOST_MATH_FORCEINLINE inline 
+#  define BOOST_MATH_FORCEINLINE inline
 
 #  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
 
-#else
+#endif
 
-#  define BOOST_MATH_GPU_ENABLED
-#  define BOOST_MATH_QUIET_NAN(T) std::numeric_limits<T>::quiet_NaN();
+#ifndef BOOST_MATH_CUDA_ENABLED
+#  define BOOST_MATH_CUDA_ENABLED
+#endif
+
+#ifndef BOOST_MATH_SYCL_ENABLED
+#  define BOOST_MATH_SYCL_ENABLED
+#endif
 
+#ifndef BOOST_MATH_QUIET_NAN
+#  define BOOST_MATH_QUIET_NAN(T) std::numeric_limits<T>::quiet_NaN();
 #endif
 
+// Not all functions that allow CUDA allow SYCL (e.g. Recursion is disallowed by SYCL)
+#  define BOOST_MATH_GPU_ENABLED BOOST_MATH_CUDA_ENABLED BOOST_MATH_SYCL_ENABLED
+
 // Static variables are not allowed with CUDA or C++20 modules
 // See if we can inline them instead
 

From 1d6c5765e85f45cf318e0494709915c3ac10c2ff Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 16:38:51 -0400
Subject: [PATCH 033/399] Limit binomial distribution to CUDA

---
 include/boost/math/distributions/binomial.hpp | 54 +++++++++----------
 1 file changed, 27 insertions(+), 27 deletions(-)

diff --git a/include/boost/math/distributions/binomial.hpp b/include/boost/math/distributions/binomial.hpp
index d17f8636b5..4c1f8bfa00 100644
--- a/include/boost/math/distributions/binomial.hpp
+++ b/include/boost/math/distributions/binomial.hpp
@@ -101,7 +101,7 @@ namespace boost
      namespace binomial_detail{
         // common error checking routines for binomial distribution functions:
         template <class RealType, class Policy>
-        BOOST_MATH_GPU_ENABLED inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
+        BOOST_MATH_CUDA_ENABLED inline bool check_N(const char* function, const RealType& N, RealType* result, const Policy& pol)
         {
            if((N < 0) || !(boost::math::isfinite)(N))
            {
@@ -113,7 +113,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_GPU_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_CUDA_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
         {
            if((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
            {
@@ -125,7 +125,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
+        BOOST_MATH_CUDA_ENABLED inline bool check_dist(const char* function, const RealType& N, const RealType& p, RealType* result, const Policy& pol)
         {
            return check_success_fraction(
               function, p, result, pol)
@@ -133,7 +133,7 @@ namespace boost
                function, N, result, pol);
         }
         template <class RealType, class Policy>
-        BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
+        BOOST_MATH_CUDA_ENABLED inline bool check_dist_and_k(const char* function, const RealType& N, const RealType& p, RealType k, RealType* result, const Policy& pol)
         {
            if(check_dist(function, N, p, result, pol) == false)
               return false;
@@ -154,7 +154,7 @@ namespace boost
            return true;
         }
         template <class RealType, class Policy>
-        BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
+        BOOST_MATH_CUDA_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& N, RealType p, RealType prob, RealType* result, const Policy& pol)
         {
            if((check_dist(function, N, p, result, pol) && detail::check_probability(function, prob, result, pol)) == false)
               return false;
@@ -162,7 +162,7 @@ namespace boost
         }
 
          template <class T, class Policy>
-         BOOST_MATH_GPU_ENABLED T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
+         BOOST_MATH_CUDA_ENABLED T inverse_binomial_cornish_fisher(T n, T sf, T p, T q, const Policy& pol)
          {
             BOOST_MATH_STD_USING
             // mean:
@@ -197,7 +197,7 @@ namespace boost
          }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
+      BOOST_MATH_CUDA_ENABLED RealType quantile_imp(const binomial_distribution<RealType, Policy>& dist, const RealType& p, const RealType& q, bool comp)
       { // Quantile or Percent Point Binomial function.
         // Return the number of expected successes k,
         // for a given probability p.
@@ -291,11 +291,11 @@ namespace boost
             &r, Policy());
       } // binomial_distribution constructor.
 
-      BOOST_MATH_GPU_ENABLED RealType success_fraction() const
+      BOOST_MATH_CUDA_ENABLED RealType success_fraction() const
       { // Probability.
         return m_p;
       }
-      BOOST_MATH_GPU_ENABLED RealType trials() const
+      BOOST_MATH_CUDA_ENABLED RealType trials() const
       { // Total number of trials.
         return m_n;
       }
@@ -311,7 +311,7 @@ namespace boost
       // these functions are used
       // to obtain confidence intervals for the success fraction.
       //
-      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
+      BOOST_MATH_CUDA_ENABLED static RealType find_lower_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
@@ -336,7 +336,7 @@ namespace boost
         return (t == clopper_pearson_exact_interval) ? ibeta_inv(successes, trials - successes + 1, probability, static_cast<RealType*>(nullptr), Policy())
            : ibeta_inv(successes + 0.5f, trials - successes + 0.5f, probability, static_cast<RealType*>(nullptr), Policy());
       }
-      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
+      BOOST_MATH_CUDA_ENABLED static RealType find_upper_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability,
@@ -364,7 +364,7 @@ namespace boost
       //    or
       // "How many trials can I have to be P% sure of seeing fewer than k events?"
       //
-      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
+      BOOST_MATH_CUDA_ENABLED static RealType find_minimum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
@@ -383,7 +383,7 @@ namespace boost
         return result + k;
       }
 
-      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
+      BOOST_MATH_CUDA_ENABLED static RealType find_maximum_number_of_trials(
          RealType k,     // number of events
          RealType p,     // success fraction
          RealType alpha) // risk level
@@ -420,33 +420,33 @@ namespace boost
       #endif
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
       { // Range of permissible values for random variable k.
         using boost::math::tools::max_value;
         return std::pair<RealType, RealType>(static_cast<RealType>(0), dist.trials());
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
       { // Range of supported values for random variable k.
         // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
         return std::pair<RealType, RealType>(static_cast<RealType>(0),  dist.trials());
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType mean(const binomial_distribution<RealType, Policy>& dist)
       { // Mean of Binomial distribution = np.
         return  dist.trials() * dist.success_fraction();
       } // mean
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType variance(const binomial_distribution<RealType, Policy>& dist)
       { // Variance of Binomial distribution = np(1-p).
         return  dist.trials() * dist.success_fraction() * (1 - dist.success_fraction());
       } // variance
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_CUDA_ENABLED RealType pdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Probability Density/Mass Function.
         BOOST_FPU_EXCEPTION_GUARD
 
@@ -502,7 +502,7 @@ namespace boost
       } // pdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
+      BOOST_MATH_CUDA_ENABLED inline RealType cdf(const binomial_distribution<RealType, Policy>& dist, const RealType& k)
       { // Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -574,7 +574,7 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_CUDA_ENABLED inline RealType cdf(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function Binomial.
         // The random variate k is the number of successes in n trials.
         // k argument may be integral, signed, or unsigned, or floating point.
@@ -651,19 +651,19 @@ namespace boost
       } // binomial cdf
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_CUDA_ENABLED inline RealType quantile(const binomial_distribution<RealType, Policy>& dist, const RealType& p)
       {
          return binomial_detail::quantile_imp(dist, p, RealType(1-p), false);
       } // quantile
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_CUDA_ENABLED RealType quantile(const complemented2_type<binomial_distribution<RealType, Policy>, RealType>& c)
       {
          return binomial_detail::quantile_imp(c.dist, RealType(1-c.param), c.param, true);
       } // quantile
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType mode(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -672,7 +672,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType median(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType median(const binomial_distribution<RealType, Policy>& dist)
       { // Bounds for the median of the negative binomial distribution
         // VAN DE VEN R. ; WEBER N. C. ;
         // Univ. Sydney, school mathematics statistics, Sydney N.S.W. 2006, AUSTRALIE
@@ -690,7 +690,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType skewness(const binomial_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING // ADL of std functions.
          RealType p = dist.success_fraction();
@@ -699,7 +699,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType kurtosis(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType n = dist.trials();
@@ -707,7 +707,7 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED inline RealType kurtosis_excess(const binomial_distribution<RealType, Policy>& dist)
       {
          RealType p = dist.success_fraction();
          RealType q = 1 - p;

From 2bb07f2a57a0aaf5dd72f119b26cbe3a17c8274e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 16:39:04 -0400
Subject: [PATCH 034/399] Disable calls to errno with SYCL

---
 include/boost/math/policies/error_handling.hpp | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index e742eaf3d0..2c67f251cf 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -233,7 +233,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
            const T& ,
            const ::boost::math::policies::domain_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return BOOST_MATH_QUIET_NAN(T);
@@ -353,7 +355,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
@@ -366,7 +370,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const T&,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
@@ -427,7 +433,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_underflow_error(
            const char* /* message */,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return T(0);
@@ -477,7 +485,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_denorm_error(
            const T& val,
            const  ::boost::math::policies::denorm_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return val;
@@ -528,7 +538,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_evaluation_error(
            const T& val,
            const  ::boost::math::policies::evaluation_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return val;
@@ -583,7 +595,9 @@ BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
            const TargetType&,
            const  ::boost::math::policies::rounding_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    static_assert(std::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
@@ -638,7 +652,9 @@ BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
            const R& result,
            const ::boost::math::policies::indeterminate_result_error< ::boost::math::policies::errno_on_error>&)
 {
+   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
+   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return result;

From 235f5c9ffc34cd8b8833555989216b1c1aa8420d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 19 Jul 2024 16:52:15 -0400
Subject: [PATCH 035/399] Replace static const char* with constexpr auto

---
 include/boost/math/distributions/arcsine.hpp | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index a1d06b7db0..59bf666b9c 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -348,7 +348,7 @@ namespace boost
       BOOST_FPU_EXCEPTION_GUARD
       BOOST_MATH_STD_USING // For ADL of std functions.
 
-      static const char* function = "boost::math::pdf(arcsine_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::pdf(arcsine_distribution<%1%> const&, %1%)";
 
       RealType lo = dist.x_min();
       RealType hi = dist.x_max();
@@ -373,7 +373,7 @@ namespace boost
     { // Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
 
-      static const char* function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
 
       RealType x_min = dist.x_min();
       RealType x_max = dist.x_max();
@@ -405,7 +405,7 @@ namespace boost
     BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<arcsine_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function arcsine.
       BOOST_MATH_STD_USING // For ADL of std functions.
-      static const char* function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::cdf(arcsine_distribution<%1%> const&, %1%)";
 
       RealType x = c.param;
       arcsine_distribution<RealType, Policy> const& dist = c.dist;
@@ -452,7 +452,7 @@ namespace boost
 
       using boost::math::constants::half_pi;
 
-      static const char* function = "boost::math::quantile(arcsine_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::quantile(arcsine_distribution<%1%> const&, %1%)";
 
       RealType result = 0; // of argument checks:
       RealType x_min = dist.x_min();
@@ -490,7 +490,7 @@ namespace boost
       BOOST_MATH_STD_USING // For ADL of std functions.
 
       using boost::math::constants::half_pi;
-      static const char* function = "boost::math::quantile(arcsine_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::quantile(arcsine_distribution<%1%> const&, %1%)";
 
       // Error checks:
       RealType q = c.param;

From 8594af7ad01dbf02266d7c44e2b3a8b8af3edead Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 14:34:17 -0400
Subject: [PATCH 036/399] Update polynomial and rationals

---
 .../tools/detail/polynomial_horner1_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner1_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner1_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner1_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner1_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner1_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner1_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner1_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner1_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner1_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner1_2.hpp     |  6 +-
 .../tools/detail/polynomial_horner1_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner1_3.hpp     |  8 +--
 .../tools/detail/polynomial_horner1_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner1_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner1_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner1_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner1_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner1_9.hpp     | 20 +++----
 .../tools/detail/polynomial_horner2_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner2_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner2_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner2_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner2_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner2_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner2_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner2_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner2_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner2_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner2_2.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner2_3.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner2_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner2_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner2_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner2_9.hpp     | 20 +++----
 .../tools/detail/polynomial_horner3_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner3_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner3_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner3_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner3_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner3_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner3_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner3_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner3_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner3_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner3_2.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner3_3.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner3_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner3_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner3_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner3_9.hpp     | 20 +++----
 .../math/tools/detail/rational_horner1_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner1_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner1_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner1_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner1_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner1_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner1_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner1_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner1_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner1_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner1_2.hpp  |  6 +-
 .../math/tools/detail/rational_horner1_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner1_3.hpp  |  8 +--
 .../math/tools/detail/rational_horner1_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner1_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner1_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner1_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner1_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner1_9.hpp  | 20 +++----
 .../math/tools/detail/rational_horner2_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner2_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner2_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner2_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner2_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner2_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner2_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner2_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner2_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner2_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner2_2.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner2_3.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner2_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner2_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner2_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner2_9.hpp  | 20 +++----
 .../math/tools/detail/rational_horner3_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner3_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner3_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner3_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner3_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner3_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner3_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner3_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner3_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner3_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner3_2.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner3_3.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner3_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner3_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner3_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner3_9.hpp  | 20 +++----
 tools/generate_rational_code.cpp              | 60 +++++++++----------
 115 files changed, 1410 insertions(+), 1410 deletions(-)

diff --git a/include/boost/math/tools/detail/polynomial_horner1_10.hpp b/include/boost/math/tools/detail/polynomial_horner1_10.hpp
index 6876af2d24..37e4cba010 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_10.hpp
@@ -12,67 +12,67 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_11.hpp b/include/boost/math/tools/detail/polynomial_horner1_11.hpp
index a5154c7a68..885490f223 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_11.hpp
@@ -12,73 +12,73 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_12.hpp b/include/boost/math/tools/detail/polynomial_horner1_12.hpp
index 82bf88c28e..f540345926 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_12.hpp
@@ -12,79 +12,79 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_13.hpp b/include/boost/math/tools/detail/polynomial_horner1_13.hpp
index f61c553dd9..e9e13bd529 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_13.hpp
@@ -12,85 +12,85 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_14.hpp b/include/boost/math/tools/detail/polynomial_horner1_14.hpp
index 76e9f07b25..eaa18bdc56 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_14.hpp
@@ -12,91 +12,91 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_15.hpp b/include/boost/math/tools/detail/polynomial_horner1_15.hpp
index bca8cf7241..c4a8804498 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_15.hpp
@@ -12,97 +12,97 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_16.hpp b/include/boost/math/tools/detail/polynomial_horner1_16.hpp
index 16ddb081dd..5c262cc63b 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_16.hpp
@@ -12,103 +12,103 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_17.hpp b/include/boost/math/tools/detail/polynomial_horner1_17.hpp
index 5828621fb8..90d49a0bd8 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_17.hpp
@@ -12,109 +12,109 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_18.hpp b/include/boost/math/tools/detail/polynomial_horner1_18.hpp
index a2a1c12f4c..58fb83fd36 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_18.hpp
@@ -12,115 +12,115 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_19.hpp b/include/boost/math/tools/detail/polynomial_horner1_19.hpp
index 83ede26b5a..18a6af2d3f 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_19.hpp
@@ -12,121 +12,121 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_2.hpp b/include/boost/math/tools/detail/polynomial_horner1_2.hpp
index 93d0f7c9c8..645e3f8785 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_2.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_20.hpp b/include/boost/math/tools/detail/polynomial_horner1_20.hpp
index d770209113..47584e7871 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_20.hpp
@@ -12,127 +12,127 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((((a[19] * x + a[18]) * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_3.hpp b/include/boost/math/tools/detail/polynomial_horner1_3.hpp
index 0fde1a7430..420bbcc28c 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_3.hpp
@@ -12,25 +12,25 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_4.hpp b/include/boost/math/tools/detail/polynomial_horner1_4.hpp
index 9e589791c3..930798e74f 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_5.hpp b/include/boost/math/tools/detail/polynomial_horner1_5.hpp
index 64dc00251d..b97a8f9ebc 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_6.hpp b/include/boost/math/tools/detail/polynomial_horner1_6.hpp
index dbc06347f3..6a699f5175 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_6.hpp
@@ -12,43 +12,43 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_7.hpp b/include/boost/math/tools/detail/polynomial_horner1_7.hpp
index 1472b2ede0..2aceeeca16 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_7.hpp
@@ -12,49 +12,49 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_8.hpp b/include/boost/math/tools/detail/polynomial_horner1_8.hpp
index 95edfa0c60..0486d642fe 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_8.hpp
@@ -12,55 +12,55 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_9.hpp b/include/boost/math/tools/detail/polynomial_horner1_9.hpp
index f434a26c4b..b0838014b7 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_9.hpp
@@ -12,61 +12,61 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_10.hpp b/include/boost/math/tools/detail/polynomial_horner2_10.hpp
index 1fce239a47..2a680d7560 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_10.hpp
@@ -12,72 +12,72 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_11.hpp b/include/boost/math/tools/detail/polynomial_horner2_11.hpp
index 3cf086c3b1..7036eec3f5 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_11.hpp
@@ -12,79 +12,79 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_12.hpp b/include/boost/math/tools/detail/polynomial_horner2_12.hpp
index e9f8eae7c6..fbbf2a3fa8 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_12.hpp
@@ -12,86 +12,86 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_13.hpp b/include/boost/math/tools/detail/polynomial_horner2_13.hpp
index d9d2a5e24a..46fb3859db 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_13.hpp
@@ -12,93 +12,93 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_14.hpp b/include/boost/math/tools/detail/polynomial_horner2_14.hpp
index b4280597a8..d1c326e0f6 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_14.hpp
@@ -12,100 +12,100 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_15.hpp b/include/boost/math/tools/detail/polynomial_horner2_15.hpp
index 89a7a46f53..d679cfeaf5 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_15.hpp
@@ -12,107 +12,107 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_16.hpp b/include/boost/math/tools/detail/polynomial_horner2_16.hpp
index d2379d2bc1..0f3ed8f6c8 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_16.hpp
@@ -12,114 +12,114 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_17.hpp b/include/boost/math/tools/detail/polynomial_horner2_17.hpp
index d1921efc49..7783c4c81d 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_17.hpp
@@ -12,121 +12,121 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_18.hpp b/include/boost/math/tools/detail/polynomial_horner2_18.hpp
index 945c4e403b..4e3b57f987 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_18.hpp
@@ -12,128 +12,128 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_19.hpp b/include/boost/math/tools/detail/polynomial_horner2_19.hpp
index a3049354ca..9eca8ef114 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_19.hpp
@@ -12,135 +12,135 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_2.hpp b/include/boost/math/tools/detail/polynomial_horner2_2.hpp
index 8b3a7dcd83..857d43fdb9 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_20.hpp b/include/boost/math/tools/detail/polynomial_horner2_20.hpp
index a4ccc93b3e..2a83590256 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_20.hpp
@@ -12,142 +12,142 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((((a[19] * x2 + a[17]) * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_3.hpp b/include/boost/math/tools/detail/polynomial_horner2_3.hpp
index d0b988cf81..b5956cdaf3 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_4.hpp b/include/boost/math/tools/detail/polynomial_horner2_4.hpp
index 7f0708680c..9194a18682 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_5.hpp b/include/boost/math/tools/detail/polynomial_horner2_5.hpp
index f4e7b809b0..4e20c214a1 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_6.hpp b/include/boost/math/tools/detail/polynomial_horner2_6.hpp
index 764e522505..a33168d5ed 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_6.hpp
@@ -12,44 +12,44 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_7.hpp b/include/boost/math/tools/detail/polynomial_horner2_7.hpp
index 50fb3333cb..2f135756c5 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_7.hpp
@@ -12,51 +12,51 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_8.hpp b/include/boost/math/tools/detail/polynomial_horner2_8.hpp
index c74b19d435..4c59602f9e 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_8.hpp
@@ -12,58 +12,58 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_9.hpp b/include/boost/math/tools/detail/polynomial_horner2_9.hpp
index 7d6e7e421f..0b60c3c04d 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_9.hpp
@@ -12,65 +12,65 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner3_10.hpp b/include/boost/math/tools/detail/polynomial_horner3_10.hpp
index b980b1b3d2..3386fcae4f 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_11.hpp b/include/boost/math/tools/detail/polynomial_horner3_11.hpp
index 2ab4b2ac3a..f24ebb0249 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_12.hpp b/include/boost/math/tools/detail/polynomial_horner3_12.hpp
index 4606427277..73916940d4 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_13.hpp b/include/boost/math/tools/detail/polynomial_horner3_13.hpp
index d35fa904f2..44ec9a84ce 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_14.hpp b/include/boost/math/tools/detail/polynomial_horner3_14.hpp
index 346b9dc28e..4d4e9e21c4 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_15.hpp b/include/boost/math/tools/detail/polynomial_horner3_15.hpp
index 500bc32317..b7cf83dd11 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_16.hpp b/include/boost/math/tools/detail/polynomial_horner3_16.hpp
index 269f367390..fbf504f3f6 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_17.hpp b/include/boost/math/tools/detail/polynomial_horner3_17.hpp
index 1d97a6f154..c7af11b654 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_18.hpp b/include/boost/math/tools/detail/polynomial_horner3_18.hpp
index 80e49cbb12..feceac694b 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_19.hpp b/include/boost/math/tools/detail/polynomial_horner3_19.hpp
index eae3775e06..6a9a4ea6f0 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -406,7 +406,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_2.hpp b/include/boost/math/tools/detail/polynomial_horner3_2.hpp
index 6281674205..69925be1cd 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_20.hpp b/include/boost/math/tools/detail/polynomial_horner3_20.hpp
index 00f8caae2a..8dda51139f 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -406,7 +406,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -447,7 +447,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_3.hpp b/include/boost/math/tools/detail/polynomial_horner3_3.hpp
index 8f69c2bfef..30e68ac2a4 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_4.hpp b/include/boost/math/tools/detail/polynomial_horner3_4.hpp
index 34db812343..e3c9b16f36 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_5.hpp b/include/boost/math/tools/detail/polynomial_horner3_5.hpp
index ed955e4a70..c02467da08 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_6.hpp b/include/boost/math/tools/detail/polynomial_horner3_6.hpp
index 96d9a6ddad..ad71255bf7 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_7.hpp b/include/boost/math/tools/detail/polynomial_horner3_7.hpp
index 80a9f3af4a..31e0afa66a 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_8.hpp b/include/boost/math/tools/detail/polynomial_horner3_8.hpp
index ee526ad736..33121b204d 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_9.hpp b/include/boost/math/tools/detail/polynomial_horner3_9.hpp
index a17ce909c7..c9f717133b 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_c
 }
 
 template <class T, class V>
-inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/rational_horner1_10.hpp b/include/boost/math/tools/detail/rational_horner1_10.hpp
index 6a04128ca6..346ac34ecc 100644
--- a/include/boost/math/tools/detail/rational_horner1_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_10.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_11.hpp b/include/boost/math/tools/detail/rational_horner1_11.hpp
index d43e53433f..74ed24a744 100644
--- a/include/boost/math/tools/detail/rational_horner1_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_11.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_12.hpp b/include/boost/math/tools/detail/rational_horner1_12.hpp
index 33d19eb380..9072d1698b 100644
--- a/include/boost/math/tools/detail/rational_horner1_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_12.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_13.hpp b/include/boost/math/tools/detail/rational_horner1_13.hpp
index 2069aa5150..1e5c750926 100644
--- a/include/boost/math/tools/detail/rational_horner1_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_13.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_14.hpp b/include/boost/math/tools/detail/rational_horner1_14.hpp
index 5ebcde6260..75b9bde42c 100644
--- a/include/boost/math/tools/detail/rational_horner1_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_14.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_15.hpp b/include/boost/math/tools/detail/rational_horner1_15.hpp
index 9da8e1b711..47f18a3c44 100644
--- a/include/boost/math/tools/detail/rational_horner1_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_15.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_16.hpp b/include/boost/math/tools/detail/rational_horner1_16.hpp
index 203ba78196..fec9a51a2e 100644
--- a/include/boost/math/tools/detail/rational_horner1_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_16.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_17.hpp b/include/boost/math/tools/detail/rational_horner1_17.hpp
index e382d2931a..b26dac95c6 100644
--- a/include/boost/math/tools/detail/rational_horner1_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_17.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_18.hpp b/include/boost/math/tools/detail/rational_horner1_18.hpp
index 66f668ee35..074a6359bb 100644
--- a/include/boost/math/tools/detail/rational_horner1_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_18.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_19.hpp b/include/boost/math/tools/detail/rational_horner1_19.hpp
index 9cd1391434..a1cceaeab8 100644
--- a/include/boost/math/tools/detail/rational_horner1_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_19.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -228,7 +228,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((((b[18] * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_2.hpp b/include/boost/math/tools/detail/rational_horner1_2.hpp
index f42cbfc645..81250ba10a 100644
--- a/include/boost/math/tools/detail/rational_horner1_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_2.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_20.hpp b/include/boost/math/tools/detail/rational_horner1_20.hpp
index 0a6c2a0f26..63763fd8c9 100644
--- a/include/boost/math/tools/detail/rational_horner1_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_20.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -228,7 +228,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((((b[18] * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -240,7 +240,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((((a[19] * x + a[18]) * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((((b[19] * x + b[18]) * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_3.hpp b/include/boost/math/tools/detail/rational_horner1_3.hpp
index d0ab213b3c..1aebe20d31 100644
--- a/include/boost/math/tools/detail/rational_horner1_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_3.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_4.hpp b/include/boost/math/tools/detail/rational_horner1_4.hpp
index 44f40114a1..8175f348cd 100644
--- a/include/boost/math/tools/detail/rational_horner1_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_4.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_5.hpp b/include/boost/math/tools/detail/rational_horner1_5.hpp
index db032f15e1..93c11c1ef3 100644
--- a/include/boost/math/tools/detail/rational_horner1_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_5.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_6.hpp b/include/boost/math/tools/detail/rational_horner1_6.hpp
index 4de5143ca9..a59cceb247 100644
--- a/include/boost/math/tools/detail/rational_horner1_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_6.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_7.hpp b/include/boost/math/tools/detail/rational_horner1_7.hpp
index 7d4ef69e9a..eaa023a502 100644
--- a/include/boost/math/tools/detail/rational_horner1_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_7.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_8.hpp b/include/boost/math/tools/detail/rational_horner1_8.hpp
index bf4d7f57e3..5624c814f3 100644
--- a/include/boost/math/tools/detail/rational_horner1_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_8.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_9.hpp b/include/boost/math/tools/detail/rational_horner1_9.hpp
index cf3be7f824..c94e7ed421 100644
--- a/include/boost/math/tools/detail/rational_horner1_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_9.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner2_10.hpp b/include/boost/math/tools/detail/rational_horner2_10.hpp
index 1a59aa334c..0e4fd54ead 100644
--- a/include/boost/math/tools/detail/rational_horner2_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_11.hpp b/include/boost/math/tools/detail/rational_horner2_11.hpp
index 1333a40bc8..841c8bd490 100644
--- a/include/boost/math/tools/detail/rational_horner2_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_12.hpp b/include/boost/math/tools/detail/rational_horner2_12.hpp
index a37cf5a05f..3e783c577c 100644
--- a/include/boost/math/tools/detail/rational_horner2_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_13.hpp b/include/boost/math/tools/detail/rational_horner2_13.hpp
index 648f3079c5..a3afa653d9 100644
--- a/include/boost/math/tools/detail/rational_horner2_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_14.hpp b/include/boost/math/tools/detail/rational_horner2_14.hpp
index 7771c3da91..377c1ad42a 100644
--- a/include/boost/math/tools/detail/rational_horner2_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_15.hpp b/include/boost/math/tools/detail/rational_horner2_15.hpp
index 03fae0d947..9082d03f8b 100644
--- a/include/boost/math/tools/detail/rational_horner2_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_16.hpp b/include/boost/math/tools/detail/rational_horner2_16.hpp
index d8565e104b..64173bffe0 100644
--- a/include/boost/math/tools/detail/rational_horner2_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_17.hpp b/include/boost/math/tools/detail/rational_horner2_17.hpp
index bd8990e0c2..5ae8cb4281 100644
--- a/include/boost/math/tools/detail/rational_horner2_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_18.hpp b/include/boost/math/tools/detail/rational_horner2_18.hpp
index 38b99ecf17..ebe440e62c 100644
--- a/include/boost/math/tools/detail/rational_horner2_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_19.hpp b/include/boost/math/tools/detail/rational_horner2_19.hpp
index b77d2eb0b9..c1a2d43830 100644
--- a/include/boost/math/tools/detail/rational_horner2_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -266,7 +266,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_2.hpp b/include/boost/math/tools/detail/rational_horner2_2.hpp
index 9c4fe47a74..e1dd400ae4 100644
--- a/include/boost/math/tools/detail/rational_horner2_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_20.hpp b/include/boost/math/tools/detail/rational_horner2_20.hpp
index 485639dcef..50a63c1287 100644
--- a/include/boost/math/tools/detail/rational_horner2_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -266,7 +266,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -282,7 +282,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_3.hpp b/include/boost/math/tools/detail/rational_horner2_3.hpp
index d19993cce1..ab0d029aac 100644
--- a/include/boost/math/tools/detail/rational_horner2_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_4.hpp b/include/boost/math/tools/detail/rational_horner2_4.hpp
index 847f26dc4e..147f5d1da6 100644
--- a/include/boost/math/tools/detail/rational_horner2_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_5.hpp b/include/boost/math/tools/detail/rational_horner2_5.hpp
index 8633d5dc13..db5907b6fb 100644
--- a/include/boost/math/tools/detail/rational_horner2_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_6.hpp b/include/boost/math/tools/detail/rational_horner2_6.hpp
index 4555426334..b71bc150a8 100644
--- a/include/boost/math/tools/detail/rational_horner2_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_7.hpp b/include/boost/math/tools/detail/rational_horner2_7.hpp
index 6a5c704d1c..da5b1476ac 100644
--- a/include/boost/math/tools/detail/rational_horner2_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_8.hpp b/include/boost/math/tools/detail/rational_horner2_8.hpp
index 9ec861fc5f..b047ad9486 100644
--- a/include/boost/math/tools/detail/rational_horner2_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_9.hpp b/include/boost/math/tools/detail/rational_horner2_9.hpp
index c76755cb22..4eed1c4307 100644
--- a/include/boost/math/tools/detail/rational_horner2_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_10.hpp b/include/boost/math/tools/detail/rational_horner3_10.hpp
index 773532cd55..1fe94f8e39 100644
--- a/include/boost/math/tools/detail/rational_horner3_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_11.hpp b/include/boost/math/tools/detail/rational_horner3_11.hpp
index a712fff090..1a4277a82f 100644
--- a/include/boost/math/tools/detail/rational_horner3_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_12.hpp b/include/boost/math/tools/detail/rational_horner3_12.hpp
index 5b87374abf..5deb0f3743 100644
--- a/include/boost/math/tools/detail/rational_horner3_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_13.hpp b/include/boost/math/tools/detail/rational_horner3_13.hpp
index 11591668b8..6c6857f31d 100644
--- a/include/boost/math/tools/detail/rational_horner3_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_14.hpp b/include/boost/math/tools/detail/rational_horner3_14.hpp
index 04f31249d4..1aadb35deb 100644
--- a/include/boost/math/tools/detail/rational_horner3_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_15.hpp b/include/boost/math/tools/detail/rational_horner3_15.hpp
index 4b9cffd48a..0f79e5b0dd 100644
--- a/include/boost/math/tools/detail/rational_horner3_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_16.hpp b/include/boost/math/tools/detail/rational_horner3_16.hpp
index 3a384dcc5f..b7c6e96c1c 100644
--- a/include/boost/math/tools/detail/rational_horner3_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_17.hpp b/include/boost/math/tools/detail/rational_horner3_17.hpp
index 1c9435e74a..25328e7ff9 100644
--- a/include/boost/math/tools/detail/rational_horner3_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_18.hpp b/include/boost/math/tools/detail/rational_horner3_18.hpp
index b133e2bafc..335b895c48 100644
--- a/include/boost/math/tools/detail/rational_horner3_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_19.hpp b/include/boost/math/tools/detail/rational_horner3_19.hpp
index ca35d3b68f..22d24403ef 100644
--- a/include/boost/math/tools/detail/rational_horner3_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1302,7 +1302,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_2.hpp b/include/boost/math/tools/detail/rational_horner3_2.hpp
index 9c4fe47a74..e1dd400ae4 100644
--- a/include/boost/math/tools/detail/rational_horner3_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_20.hpp b/include/boost/math/tools/detail/rational_horner3_20.hpp
index 58109ac305..f97124afb9 100644
--- a/include/boost/math/tools/detail/rational_horner3_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1302,7 +1302,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1452,7 +1452,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_3.hpp b/include/boost/math/tools/detail/rational_horner3_3.hpp
index d19993cce1..ab0d029aac 100644
--- a/include/boost/math/tools/detail/rational_horner3_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_4.hpp b/include/boost/math/tools/detail/rational_horner3_4.hpp
index 847f26dc4e..147f5d1da6 100644
--- a/include/boost/math/tools/detail/rational_horner3_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_5.hpp b/include/boost/math/tools/detail/rational_horner3_5.hpp
index cc77fd560c..af1c76f1c6 100644
--- a/include/boost/math/tools/detail/rational_horner3_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_6.hpp b/include/boost/math/tools/detail/rational_horner3_6.hpp
index 73920ad018..05d626ac8a 100644
--- a/include/boost/math/tools/detail/rational_horner3_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_7.hpp b/include/boost/math/tools/detail/rational_horner3_7.hpp
index 8e30ecf310..2d91a5c501 100644
--- a/include/boost/math/tools/detail/rational_horner3_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_8.hpp b/include/boost/math/tools/detail/rational_horner3_8.hpp
index a8f93f3a3e..3a6ea4ff09 100644
--- a/include/boost/math/tools/detail/rational_horner3_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_9.hpp b/include/boost/math/tools/detail/rational_horner3_9.hpp
index 064d984d3f..d20149b22f 100644
--- a/include/boost/math/tools/detail/rational_horner3_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::
 }
 
 template <class T, class U, class V>
-inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/tools/generate_rational_code.cpp b/tools/generate_rational_code.cpp
index 2da7e000ea..92b7da9a10 100644
--- a/tools/generate_rational_code.cpp
+++ b/tools/generate_rational_code.cpp
@@ -40,13 +40,13 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n";
@@ -55,7 +55,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   return static_cast<V>(";
          
@@ -90,28 +90,28 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>(a[1] * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>((a[2] * x + a[1]) * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);\n"
          "}\n\n";
@@ -120,7 +120,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   V x2 = x * x;\n"
          "   return static_cast<V>(";
@@ -186,28 +186,28 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>(a[1] * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>((a[2] * x + a[1]) * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);\n"
          "}\n\n";
@@ -216,7 +216,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   V x2 = x * x;\n"
          "   V t[2];\n";
@@ -281,13 +281,13 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_RAT_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n";
@@ -296,7 +296,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n"
          "     return static_cast<V>((";
@@ -361,28 +361,28 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_RAT_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));\n"
          "}\n\n";
@@ -391,7 +391,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n   {\n"
          "      V x2 = x * x;\n"
@@ -577,28 +577,28 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_RAT_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));\n"
          "}\n\n";
@@ -607,7 +607,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n   {\n"
          "      V x2 = x * x;\n"

From 04c33f8cad3408716853657737cad60cb6fe6196 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:00:18 -0400
Subject: [PATCH 037/399] Add additional overflow error overloads

---
 .../boost/math/policies/error_handling.hpp    | 26 +++++++++++++++++++
 1 file changed, 26 insertions(+)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 2c67f251cf..6509b47c34 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -337,6 +337,32 @@ BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
    return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr float raise_overflow_error<float>(
+           const char* ,
+           const char* ,
+           const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(float)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return static_cast<float>(INFINITY);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr double raise_overflow_error<double>(
+           const char* ,
+           const char* ,
+           const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(double)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return INFINITY;
+}
+
+#endif
+
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
            const char* ,

From 282a40191dd1db8e20546ecd711a2d4bb6f5b54a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:01:17 -0400
Subject: [PATCH 038/399] Add GPU safe max, min, and swap function macros

---
 include/boost/math/tools/config.hpp | 23 ++++++++++++++++++++++-
 1 file changed, 22 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index eafe53fdc0..63057e47f3 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -724,6 +724,27 @@ namespace boost{ namespace math{
 // Not all functions that allow CUDA allow SYCL (e.g. Recursion is disallowed by SYCL)
 #  define BOOST_MATH_GPU_ENABLED BOOST_MATH_CUDA_ENABLED BOOST_MATH_SYCL_ENABLED
 
+// Additional functions that need replaced/marked up
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+template <class T>
+BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
+template <class T>
+BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_min(const T& a, const T& b) { return a < b ? a : b; }
+template <class T>
+BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { return a > b ? a : b; }
+
+#define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b);
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) gpu_safe_min(a, b);
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) gpu_safe_max(a, b);
+
+#else
+
+#define BOOST_MATH_GPU_SAFE_SWAP(a, b) std::swap(a, b);
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) (std::min)(a, b);
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) (std::max)(a, b);
+
+#endif
+
 // Static variables are not allowed with CUDA or C++20 modules
 // See if we can inline them instead
 
@@ -731,7 +752,7 @@ namespace boost{ namespace math{
 #  define BOOST_MATH_STATIC_CONSTEXPR inline constexpr
 #  define BOOST_MATH_STATIC static
 #else
-#  ifndef BOOST_MATH_ENABLE_CUDA
+#  ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #    define BOOST_MATH_STATIC_CONSTEXPR static constexpr
 #    define BOOST_MATH_STATIC static
 #  else

From b39f01db24349d7badd3d160ae1d1e9c76c6855e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:01:52 -0400
Subject: [PATCH 039/399] Add log1p GPU support

---
 .../boost/math/special_functions/log1p.hpp    | 52 +++++++++----------
 .../boost/math/special_functions/math_fwd.hpp |  4 +-
 2 files changed, 28 insertions(+), 28 deletions(-)

diff --git a/include/boost/math/special_functions/log1p.hpp b/include/boost/math/special_functions/log1p.hpp
index 9b8a8e0eb7..fc7308eb67 100644
--- a/include/boost/math/special_functions/log1p.hpp
+++ b/include/boost/math/special_functions/log1p.hpp
@@ -47,16 +47,16 @@ namespace detail
   {
      typedef T result_type;
 
-     log1p_series(T x)
+     BOOST_MATH_GPU_ENABLED log1p_series(T x)
         : k(0), m_mult(-x), m_prod(-1){}
 
-     T operator()()
+     BOOST_MATH_GPU_ENABLED T operator()()
      {
         m_prod *= m_mult;
         return m_prod / ++k;
      }
 
-     int count()const
+     BOOST_MATH_GPU_ENABLED int count()const
      {
         return k;
      }
@@ -79,12 +79,12 @@ namespace detail
 // it performs no better than log(1+x): which is to say not very well at all.
 //
 template <class T, class Policy>
-T log1p_imp(T const & x, const Policy& pol, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const std::integral_constant<int, 0>&)
 { // The function returns the natural logarithm of 1 + x.
    typedef typename tools::promote_args<T>::type result_type;
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::log1p<%1%>(%1%)";
+   constexpr auto function = "boost::math::log1p<%1%>(%1%)";
 
    if((x < -1) || (boost::math::isnan)(x))
       return policies::raise_domain_error<T>(
@@ -110,7 +110,7 @@ T log1p_imp(T const & x, const Policy& pol, const std::integral_constant<int, 0>
 }
 
 template <class T, class Policy>
-T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
@@ -135,7 +135,7 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>
    // Expected Error Term:                         1.843e-017
    // Maximum Relative Change in Control Points:   8.138e-004
    // Max Error found at double precision =        3.250766e-016
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
        static_cast<T>(0.15141069795941984e-16L),
        static_cast<T>(0.35495104378055055e-15L),
        static_cast<T>(0.33333333333332835L),
@@ -145,7 +145,7 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>
        static_cast<T>(0.13703234928513215L),
        static_cast<T>(0.011294864812099712L)
      };
-   static const T Q[] = {
+   BOOST_MATH_STATIC const T Q[] = {
        static_cast<T>(1L),
        static_cast<T>(3.7274719063011499L),
        static_cast<T>(5.5387948649720334L),
@@ -163,11 +163,11 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>
 }
 
 template <class T, class Policy>
-T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::log1p<%1%>(%1%)";
+   constexpr auto function = "boost::math::log1p<%1%>(%1%)";
 
    if(x < -1)
       return policies::raise_domain_error<T>(
@@ -188,7 +188,7 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>
    // Expected Error Term:                         8.088e-20
    // Maximum Relative Change in Control Points:   9.648e-05
    // Max Error found at long double precision =   2.242324e-19
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.807533446680736736712e-19),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.490881544804798926426e-18),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.333333333333333373941),
@@ -199,7 +199,7 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.0706537026422828914622),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00441709903782239229447)
    };
-   static const T Q[] = {
+   BOOST_MATH_STATIC const T Q[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 64, 4.26423872346263928361),
       BOOST_MATH_BIG_CONSTANT(T, 64, 7.48189472704477708962),
@@ -218,7 +218,7 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>
 }
 
 template <class T, class Policy>
-T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 24>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
@@ -244,13 +244,13 @@ T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 24>
    // Maximum Relative Change in Control Points:   2.509e-04
    // Max Error found at double precision =        6.910422e-08
    // Max Error found at float precision =         8.357242e-08
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
       -0.671192866803148236519e-7L,
       0.119670999140731844725e-6L,
       0.333339469182083148598L,
       0.237827183019664122066L
    };
-   static const T Q[] = {
+   BOOST_MATH_STATIC const T Q[] = {
       1L,
       1.46348272586988539733L,
       0.497859871350117338894L,
@@ -268,20 +268,20 @@ struct log1p_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init(tag());
       }
       template <int N>
-      static void do_init(const std::integral_constant<int, N>&){}
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, N>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 64>&)
       {
          boost::math::log1p(static_cast<T>(0.25), Policy());
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
       initializer.force_instantiate();
    }
@@ -294,7 +294,7 @@ const typename log1p_initializer<T, Policy, tag>::init log1p_initializer<T, Poli
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type log1p(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -328,7 +328,7 @@ inline typename tools::promote_args<T>::type log1p(T x, const Policy&)
 #if defined(BOOST_HAS_LOG1P) && !(defined(__osf__) && defined(__DECCXX_VER))
 #  ifdef BOOST_MATH_USE_C99
 template <class Policy>
-inline float log1p(float x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline float log1p(float x, const Policy& pol)
 {
    if(x < -1)
       return policies::raise_domain_error<float>(
@@ -340,7 +340,7 @@ inline float log1p(float x, const Policy& pol)
 }
 #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
 template <class Policy>
-inline long double log1p(long double x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline long double log1p(long double x, const Policy& pol)
 {
    if(x < -1)
       return policies::raise_domain_error<long double>(
@@ -365,7 +365,7 @@ inline float log1p(float x, const Policy& pol)
 }
 #endif
 template <class Policy>
-inline double log1p(double x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline double log1p(double x, const Policy& pol)
 {
    if(x < -1)
       return policies::raise_domain_error<double>(
@@ -425,7 +425,7 @@ inline long double log1p(long double x, const Policy& pol)
 #endif
 
 template <class T>
-inline typename tools::promote_args<T>::type log1p(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x)
 {
    return boost::math::log1p(x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 3e5d6a7625..ee43684ce6 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -568,10 +568,10 @@ namespace boost
 
    // log1p is log(x + 1)
    template <class T>
-   tools::promote_args_t<T> log1p(T);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> log1p(T);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> log1p(T, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> log1p(T, const Policy&);
 
    // log1pmx is log(x + 1) - x
    template <class T>

From 23b6d289ad6587b9d8e0597c9b66e5905564b5c4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:02:13 -0400
Subject: [PATCH 040/399] Add precision helper functions

---
 include/boost/math/tools/precision.hpp | 64 ++++++++++++++++++++++++--
 1 file changed, 60 insertions(+), 4 deletions(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 86b8e99824..d82144466d 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -10,6 +10,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/assert.hpp>
 #include <boost/math/policies/policy.hpp>
 #include <type_traits>
@@ -54,6 +55,22 @@ inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(std
 } // Also used as a finite 'infinite' value for - and +infinity, for example:
 // -max_value<double> = -1.79769e+308, max_value<double> = 1.79769e+308.
 
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr float max_value<float>() noexcept
+{
+   return FLT_MAX;
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr double max_value<double>() noexcept
+{
+   return DBL_MAX;
+}
+
+#endif
+
 template <class T>
 inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
@@ -62,6 +79,22 @@ inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std:
    return (std::numeric_limits<T>::min)();
 }
 
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr float min_value<float>() noexcept
+{
+   return FLT_MIN;
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr double min_value<double>() noexcept
+{
+   return DBL_MIN;
+}
+
+#endif
+
 namespace detail{
 //
 // Logarithmic limits come next, note that although
@@ -72,13 +105,13 @@ namespace detail{
 // For type float first:
 //
 template <class T>
-inline constexpr T log_max_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return 88.0f;
 }
 
 template <class T>
-inline constexpr T log_min_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return -87.0f;
 }
@@ -86,13 +119,13 @@ inline constexpr T log_min_value(const std::integral_constant<int, 128>& BOOST_M
 // Now double:
 //
 template <class T>
-inline constexpr T log_max_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return 709.0;
 }
 
 template <class T>
-inline constexpr T log_min_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return -708.0;
 }
@@ -257,6 +290,29 @@ BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPE
 #endif
 }
 
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr float epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(float)) noexcept(true)
+{
+   return FLT_EPSILON;
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr double epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(double)) noexcept(true)
+{
+   return DBL_EPSILON;
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED constexpr long double epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(long double)) noexcept(true)
+{
+   return LDBL_EPSILON;
+}
+
+
+#endif
+
 namespace detail{
 
 template <class T>

From d9c4fab159005e30a83782fb19678928f09b6b0f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:02:25 -0400
Subject: [PATCH 041/399] Markup big_constant

---
 include/boost/math/tools/big_constant.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/big_constant.hpp b/include/boost/math/tools/big_constant.hpp
index eaa34dd230..2fdfec7826 100644
--- a/include/boost/math/tools/big_constant.hpp
+++ b/include/boost/math/tools/big_constant.hpp
@@ -43,12 +43,12 @@ typedef double largest_float;
 #endif
 
 template <class T>
-inline constexpr T make_big_value(largest_float v, const char*, std::true_type const&, std::false_type const&) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED constexpr T make_big_value(largest_float v, const char*, std::true_type const&, std::false_type const&) BOOST_MATH_NOEXCEPT(T)
 {
    return static_cast<T>(v);
 }
 template <class T>
-inline constexpr T make_big_value(largest_float v, const char*, std::true_type const&, std::true_type const&) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED constexpr T make_big_value(largest_float v, const char*, std::true_type const&, std::true_type const&) BOOST_MATH_NOEXCEPT(T)
 {
    return static_cast<T>(v);
 }

From 910775040b2b6362da060a3da382bbfae6cc70eb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:02:45 -0400
Subject: [PATCH 042/399] Add support for lanczos and change storage duration

---
 .../boost/math/special_functions/lanczos.hpp  | 208 +++++++++---------
 1 file changed, 104 insertions(+), 104 deletions(-)

diff --git a/include/boost/math/special_functions/lanczos.hpp b/include/boost/math/special_functions/lanczos.hpp
index d75a968cdb..7a1934c80c 100644
--- a/include/boost/math/special_functions/lanczos.hpp
+++ b/include/boost/math/special_functions/lanczos.hpp
@@ -48,7 +48,7 @@ namespace boost{ namespace math{ namespace lanczos{
 // Default version assumes all g() values are the same.
 //
 template <class L>
-inline double lanczos_g_near_1_and_2(const L&)
+BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const L&)
 {
    return L::g();
 }
@@ -66,10 +66,10 @@ struct lanczos6 : public std::integral_constant<int, 35>
    // double precision:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[6] = {
+      BOOST_MATH_STATIC const T num[6] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 8706.349592549009182288174442774377925882)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 8523.650341121874633477483696775067709735)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 3338.029219476423550899999750161289306564)),
@@ -77,7 +77,7 @@ struct lanczos6 : public std::integral_constant<int, 35>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 63.99951844938187085666201263218840287667)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 2.506628274631006311133031631822390264407))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
          static_cast<std::uint16_t>(0u),
          static_cast<std::uint16_t>(24u),
          static_cast<std::uint16_t>(50u),
@@ -90,10 +90,10 @@ struct lanczos6 : public std::integral_constant<int, 35>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[6] = {
+      BOOST_MATH_STATIC const T num[6] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 32.81244541029783471623665933780748627823)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 32.12388941444332003446077108933558534361)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 12.58034729455216106950851080138931470954)),
@@ -101,7 +101,7 @@ struct lanczos6 : public std::integral_constant<int, 35>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 0.2412010548258800231126240760264822486599)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 0.009446967704539249494420221613134244048319))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
          static_cast<std::uint16_t>(0u),
          static_cast<std::uint16_t>(24u),
          static_cast<std::uint16_t>(50u),
@@ -115,10 +115,10 @@ struct lanczos6 : public std::integral_constant<int, 35>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[5] = {
+      BOOST_MATH_STATIC const T d[5] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 2.044879010930422922760429926121241330235)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, -2.751366405578505366591317846728753993668)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 1.02282965224225004296750609604264824677)),
@@ -135,10 +135,10 @@ struct lanczos6 : public std::integral_constant<int, 35>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[5] = {
+      BOOST_MATH_STATIC const T d[5] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 5.748142489536043490764289256167080091892)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, -7.734074268282457156081021756682138251825)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 2.875167944990511006997713242805893543947)),
@@ -155,7 +155,7 @@ struct lanczos6 : public std::integral_constant<int, 35>
       return result;
    }
 
-   static double g(){ return 5.581000000000000405009359383257105946541; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 5.581000000000000405009359383257105946541; }
 };
 
 //
@@ -170,10 +170,10 @@ struct lanczos11 : public std::integral_constant<int, 60>
    // extended-double precision:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[11] = {
+      BOOST_MATH_STATIC const T num[11] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 38474670393.31776828316099004518914832218)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 36857665043.51950660081971227404959150474)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 15889202453.72942008945006665994637853242)),
@@ -186,7 +186,7 @@ struct lanczos11 : public std::integral_constant<int, 60>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 261.6140441641668190791708576058805625502)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 2.506628274631000502415573855452633787834))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(362880u),
          static_cast<std::uint32_t>(1026576u),
@@ -204,10 +204,10 @@ struct lanczos11 : public std::integral_constant<int, 60>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[11] = {
+      BOOST_MATH_STATIC const T num[11] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 709811.662581657956893540610814842699825)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 679979.847415722640161734319823103390728)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 293136.785721159725251629480984140341656)),
@@ -220,7 +220,7 @@ struct lanczos11 : public std::integral_constant<int, 60>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 0.004826466289237661857584712046231435101741)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 0.4624429436045378766270459638520555557321e-4))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(362880u),
          static_cast<std::uint32_t>(1026576u),
@@ -239,10 +239,10 @@ struct lanczos11 : public std::integral_constant<int, 60>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[10] = {
+      BOOST_MATH_STATIC const T d[10] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 4.005853070677940377969080796551266387954)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, -13.17044315127646469834125159673527183164)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 17.19146865350790353683895137079288129318)),
@@ -264,10 +264,10 @@ struct lanczos11 : public std::integral_constant<int, 60>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[10] = {
+      BOOST_MATH_STATIC const T d[10] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 19.05889633808148715159575716844556056056)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, -62.66183664701721716960978577959655644762)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 81.7929198065004751699057192860287512027)),
@@ -289,7 +289,7 @@ struct lanczos11 : public std::integral_constant<int, 60>
       return result;
    }
 
-   static double g(){ return 10.90051099999999983936049829935654997826; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 10.90051099999999983936049829935654997826; }
 };
 
 //
@@ -304,10 +304,10 @@ struct lanczos13 : public std::integral_constant<int, 72>
    // higher precision:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[13] = {
+      BOOST_MATH_STATIC const T num[13] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 44012138428004.60895436261759919070125699)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 41590453358593.20051581730723108131357995)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 18013842787117.99677796276038389462742949)),
@@ -322,7 +322,7 @@ struct lanczos13 : public std::integral_constant<int, 72>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 381.8801248632926870394389468349331394196)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 2.506628274631000502415763426076722427007))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(39916800u),
          static_cast<std::uint32_t>(120543840u),
@@ -342,10 +342,10 @@ struct lanczos13 : public std::integral_constant<int, 72>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[13] = {
+      BOOST_MATH_STATIC const T num[13] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 86091529.53418537217994842267760536134841)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 81354505.17858011242874285785316135398567)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 35236626.38815461910817650960734605416521)),
@@ -360,7 +360,7 @@ struct lanczos13 : public std::integral_constant<int, 72>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 0.0007469903808915448316510079585999893674101)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 0.4903180573459871862552197089738373164184e-5))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(39916800u),
          static_cast<std::uint32_t>(120543840u),
@@ -381,10 +381,10 @@ struct lanczos13 : public std::integral_constant<int, 72>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[12] = {
+      BOOST_MATH_STATIC const T d[12] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 4.832115561461656947793029596285626840312)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, -19.86441536140337740383120735104359034688)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 33.9927422807443239927197864963170585331)),
@@ -408,10 +408,10 @@ struct lanczos13 : public std::integral_constant<int, 72>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[12] = {
+      BOOST_MATH_STATIC const T d[12] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 26.96979819614830698367887026728396466395)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, -110.8705424709385114023884328797900204863)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 189.7258846119231466417015694690434770085)),
@@ -435,7 +435,7 @@ struct lanczos13 : public std::integral_constant<int, 72>
       return result;
    }
 
-   static double g(){ return 13.1445650000000000545696821063756942749; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 13.1445650000000000545696821063756942749; }
 };
 
 //
@@ -449,10 +449,10 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
    // Use for float precision, when evaluated as a float:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[6] = {
+      BOOST_MATH_STATIC const T num[6] = {
          static_cast<T>(58.52061591769095910314047740215847630266L),
          static_cast<T>(182.5248962595894264831189414768236280862L),
          static_cast<T>(211.0971093028510041839168287718170827259L),
@@ -460,7 +460,7 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
          static_cast<T>(27.5192015197455403062503721613097825345L),
          static_cast<T>(2.50662858515256974113978724717473206342L)
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
          static_cast<std::uint16_t>(0u),
          static_cast<std::uint16_t>(24u),
          static_cast<std::uint16_t>(50u),
@@ -473,10 +473,10 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[6] = {
+      BOOST_MATH_STATIC const T num[6] = {
          static_cast<T>(14.0261432874996476619570577285003839357L),
          static_cast<T>(43.74732405540314316089531289293124360129L),
          static_cast<T>(50.59547402616588964511581430025589038612L),
@@ -484,7 +484,7 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
          static_cast<T>(6.595765571169314946316366571954421695196L),
          static_cast<T>(0.6007854010515290065101128585795542383721L)
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
          static_cast<std::uint16_t>(0u),
          static_cast<std::uint16_t>(24u),
          static_cast<std::uint16_t>(50u),
@@ -498,10 +498,10 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[5] = {
+      BOOST_MATH_STATIC const T d[5] = {
          static_cast<T>(0.4922488055204602807654354732674868442106L),
          static_cast<T>(0.004954497451132152436631238060933905650346L),
          static_cast<T>(-0.003374784572167105840686977985330859371848L),
@@ -518,10 +518,10 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[5] = {
+      BOOST_MATH_STATIC const T d[5] = {
          static_cast<T>(0.6534966888520080645505805298901130485464L),
          static_cast<T>(0.006577461728560758362509168026049182707101L),
          static_cast<T>(-0.004480276069269967207178373559014835978161L),
@@ -538,7 +538,7 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
       return result;
    }
 
-   static double g(){ return 1.428456135094165802001953125; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 1.428456135094165802001953125; }
 };
 
 //
@@ -552,10 +552,10 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
    // Use for double precision, when evaluated as a double:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[13] = {
+      BOOST_MATH_STATIC const T num[13] = {
          static_cast<T>(23531376880.41075968857200767445163675473L),
          static_cast<T>(42919803642.64909876895789904700198885093L),
          static_cast<T>(35711959237.35566804944018545154716670596L),
@@ -570,7 +570,7 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
          static_cast<T>(210.8242777515793458725097339207133627117L),
          static_cast<T>(2.506628274631000270164908177133837338626L)
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(39916800u),
          static_cast<std::uint32_t>(120543840u),
@@ -590,10 +590,10 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[13] = {
+      BOOST_MATH_STATIC const T num[13] = {
          static_cast<T>(56906521.91347156388090791033559122686859L),
          static_cast<T>(103794043.1163445451906271053616070238554L),
          static_cast<T>(86363131.28813859145546927288977868422342L),
@@ -608,7 +608,7 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
          static_cast<T>(0.5098416655656676188125178644804694509993L),
          static_cast<T>(0.006061842346248906525783753964555936883222L)
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
          static_cast<std::uint32_t>(0u),
          static_cast<std::uint32_t>(39916800u),
          static_cast<std::uint32_t>(120543840u),
@@ -629,10 +629,10 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[12] = {
+      BOOST_MATH_STATIC const T d[12] = {
          static_cast<T>(2.208709979316623790862569924861841433016L),
          static_cast<T>(-3.327150580651624233553677113928873034916L),
          static_cast<T>(1.483082862367253753040442933770164111678L),
@@ -656,10 +656,10 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[12] = {
+      BOOST_MATH_STATIC const T d[12] = {
          static_cast<T>(6.565936202082889535528455955485877361223L),
          static_cast<T>(-9.8907772644920670589288081640128194231L),
          static_cast<T>(4.408830289125943377923077727900630927902L),
@@ -683,7 +683,7 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
       return result;
    }
 
-   static double g(){ return 6.024680040776729583740234375; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 6.024680040776729583740234375; }
 };
 
 //
@@ -697,10 +697,10 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
    // Use for extended-double precision, when evaluated as an extended-double:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[17] = {
+      BOOST_MATH_STATIC const T num[17] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 553681095419291969.2230556393350368550504)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 731918863887667017.2511276782146694632234)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 453393234285807339.4627124634539085143364)),
@@ -719,7 +719,7 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 488.0063567520005730476791712814838113252)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.50662827463100050241576877135758834683))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
          BOOST_MATH_INT_VALUE_SUFFIX(0, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(1307674368000, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(4339163001600, uLL),
@@ -743,10 +743,10 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[17] = {
+      BOOST_MATH_STATIC const T num[17] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2715894658327.717377557655133124376674911)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3590179526097.912105038525528721129550434)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2223966599737.814969312127353235818710172)),
@@ -765,7 +765,7 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.002393749522058449186690627996063983095463)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.1229541408909435212800785616808830746135e-4))
       };
-      static const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
          BOOST_MATH_INT_VALUE_SUFFIX(0, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(1307674368000, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(4339163001600, uLL),
@@ -790,10 +790,10 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[16] = {
+      BOOST_MATH_STATIC const T d[16] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.493645054286536365763334986866616581265)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -16.95716370392468543800733966378143997694)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 26.19196892983737527836811770970479846644)),
@@ -821,10 +821,10 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[16] = {
+      BOOST_MATH_STATIC const T d[16] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 23.56409085052261327114594781581930373708)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -88.92116338946308797946237246006238652361)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 137.3472822086847596961177383569603988797)),
@@ -852,7 +852,7 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
       return result;
    }
 
-   static double g(){ return 12.2252227365970611572265625; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 12.2252227365970611572265625; }
 };
 
 //
@@ -869,7 +869,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[24] = {
+      BOOST_MATH_STATIC const T num[24] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 2029889364934367661624137213253.22102954656825019111612712252027267955023987678816620961507)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 2338599599286656537526273232565.2727349714338768161421882478417543004440597874814359063158)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 1288527989493833400335117708406.3953711906175960449186720680201425446299360322830739180195)),
@@ -895,7 +895,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 1151.61895453463992438325318456328526085882924197763140514450975619271382783957699017875304)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 2.50662827463100050241576528481104515966515623051532908941425544355490413900497467936202516))
       };
-      static const T denom[24] = {
+      BOOST_MATH_STATIC const T denom[24] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.0)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.112400072777760768e22)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.414847677933545472e22)),
@@ -929,7 +929,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[24] = {
+      BOOST_MATH_STATIC const T num[24] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 3035162425359883494754.02878223286972654682199012688209026810841953293372712802258398358538)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 3496756894406430103600.16057175075063458536101374170860226963245118484234495645518505519827)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 1926652656689320888654.01954015145958293168365236755537645929361841917596501251362171653478)),
@@ -955,7 +955,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.172194142179211139195966608011235161516824700287310869949928393345257114743230967204370963e-5)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.374799931707148855771381263542708435935402853962736029347951399323367765509988401336565436e-8))
       };
-      static const T denom[24] = {
+      BOOST_MATH_STATIC const T denom[24] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.0)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.112400072777760768e22)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 0.414847677933545472e22)),
@@ -990,7 +990,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[23] = {
+      BOOST_MATH_STATIC const T d[23] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 7.4734083002469026177867421609938203388868806387315406134072298925733950040583068760685908)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, -50.4225805042247530267317342133388132970816607563062253708655085754357843064134941138154171)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 152.288200621747008570784082624444625293884063492396162110698238568311211546361189979357019)),
@@ -1028,7 +1028,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[23] = {
+      BOOST_MATH_STATIC const T d[23] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 61.4165001061101455341808888883960361969557848005400286332291451422461117307237198559485365)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, -414.372973678657049667308134761613915623353625332248315105320470271523320700386200587519147)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 113, 1251.50505818554680171298972755376376836161706773644771875668053742215217922228357204561873)),
@@ -1078,7 +1078,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[27] = {
+      BOOST_MATH_STATIC const T num[27] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 2.532923291341302819860952064783714673718970e+36)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 2.715272050979243637524956158081893927075092e+36)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 1.399396313336459710065708403038293278484916e+36)),
@@ -1107,7 +1107,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 1.580741273679785112052701460119954412080073e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 2.506628274631000502415765284811045253005320e+00))
       };
-      static const T denom[27] = {
+      BOOST_MATH_STATIC const T denom[27] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 0.000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 1.551121004333098598400000000000000000000000e+25)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 5.919012881170120359936000000000000000000000e+25)),
@@ -1144,7 +1144,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[27] = {
+      BOOST_MATH_STATIC const T num[27] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 4.630539114451826442425094380936505531231478e+25)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 4.963898228350662244301785145431331232866294e+25)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 2.558292778812387748738731408569861630189290e+25)),
@@ -1173,7 +1173,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 2.889816806780013044430000551700375309307825e-08)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 4.582468135039046226997146555551548992616343e-11))
       };
-      static const T denom[27] = {
+      BOOST_MATH_STATIC const T denom[27] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 0.000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 1.551121004333098598400000000000000000000000e+25)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 5.919012881170120359936000000000000000000000e+25)),
@@ -1211,7 +1211,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[34] = {
+      BOOST_MATH_STATIC const T d[34] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 6.264579889722939745225908247624593169040293e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, -3.470545597111704235784909052092266897169254e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 8.398164226943527197542310295220360303173237e+01)),
@@ -1260,7 +1260,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[34] = {
+      BOOST_MATH_STATIC const T d[34] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 4.391991857844535020743473289228849738381662e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, -2.433141291692735004291785549611375831426138e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 134, 5.887812040849956173864447000497922705559488e+02)),
@@ -1326,7 +1326,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[35] = {
+      BOOST_MATH_STATIC const T num[35] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.17215050716253100021302249837728942659410271586236104e+50)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.51055117651708470336913962553466820524801246971658127e+50)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 1.40813458996718289733677017073036013655624930344397267e+50)),
@@ -1363,7 +1363,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.50897418653428667959996348205296461689142907811767371e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.50662827463100050241576528481104525300698674060984055e+00))
       };
-      static const T denom[35] = {
+      BOOST_MATH_STATIC const T denom[35] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 0.00000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 8.68331761881188649551819440128000000000000000000000000e+36)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 3.55043336733310191803732770947072000000000000000000000e+37)),
@@ -1408,7 +1408,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[35] = {
+      BOOST_MATH_STATIC const T num[35] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.84421398435712762388902267099927585742388886580864424e+37)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 3.28731583799033736725852757551292030085556435695468295e+37)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 1.84381150359300352571680869181416248982215282642834936e+37)),
@@ -1445,7 +1445,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 3.28525092722679899458094768960179796663588010298597603e-10)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 3.28217919006153582429216342066702743329957749672852350e-13))
       };
-      static const T denom[35] = {
+      BOOST_MATH_STATIC const T denom[35] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 0.00000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 8.68331761881188649551819440128000000000000000000000000e+36)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 3.55043336733310191803732770947072000000000000000000000e+37)),
@@ -1491,7 +1491,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[42] = {
+      BOOST_MATH_STATIC const T d[42] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 8.2258008829795701933757823508857131818190413131511363e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, -6.1680809698202901664719598422224259984110345848176138e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 2.0937956909159916126016144892534179459545368045658870e+02)),
@@ -1548,7 +1548,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[42] = {
+      BOOST_MATH_STATIC const T d[42] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 7.3782193657165970743894979068466124765194827248379940e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, -5.5325256602067816772285455933211570612342576586214891e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 168, 1.8780522570799869937961476290263461833002660531646012e+03)),
@@ -1621,7 +1621,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[48] = {
+      BOOST_MATH_STATIC const T num[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 5.761757987425932419978923296640371540367427757167447418730589877e+70)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 8.723233313564421930629677035555276136256253817229396631458438691e+70)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 6.460052620548943146316510839385235752729444155384745952604400014e+70)),
@@ -1671,7 +1671,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 3.749690888961891063146468955091435916957208840312184463551812828e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 2.506628274631000502415765284811045253006986740609938316629929233e+00))
       };
-      static const T denom[48] = {
+      BOOST_MATH_STATIC const T denom[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 0.000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 5.502622159812088949850305428800254892961651752960000000000000000e+57)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 2.430336111272256671478593169569751383305061494947840000000000000e+58)),
@@ -1729,7 +1729,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[48] = {
+      BOOST_MATH_STATIC const T num[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 1.775732062655417998910881298714821053061055705608286949609421120e+58)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 2.688437299644448784121592662352787426980194425446481703306505899e+58)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 1.990941408817264621124181941423397180231807676408175000011574647e+58)),
@@ -1779,7 +1779,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 1.155627562127299657410444702080985966726894475302009989071093439e-09)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 7.725246714864934496649491688787278190129598018071339049048385845e-13))
       };
-      static const T denom[48] = {
+      BOOST_MATH_STATIC const T denom[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 0.000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 5.502622159812088949850305428800254892961651752960000000000000000e+57)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 2.430336111272256671478593169569751383305061494947840000000000000e+58)),
@@ -1838,7 +1838,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[47] = {
+      BOOST_MATH_STATIC const T d[47] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 1.059629332377126683204423480567078764834299559082175332563440691e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, -1.045539783916612448318159279915745234781500064405838259582295756e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 4.784116147862702971548198855631720823614071322755242269800139953e+02)),
@@ -1900,7 +1900,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[47] = {
+      BOOST_MATH_STATIC const T d[47] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 1.201442621036266842137537764128372139686555918574926377003612763e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, -1.185467427150643969519910927764836582205108528009141221591420898e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 201, 5.424388386017623557963301151646679462091516489317860889362683594e+03)),
@@ -1973,7 +1973,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[49] = {
+      BOOST_MATH_STATIC const T num[49] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.019754080776483553135944314398390557182640085494778723336498544843678485e+75)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.676059842235360762770131859925648183945167646928679564649946220888559950e+75)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.735650057396761011129552305882284776566019938011364428733911563803428382e+75)),
@@ -2024,7 +2024,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 4.390800780998954208500039666019609185743083611214630479125238184115750385e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.506628274631000502415765284811045253006986740609938316629923576327386304e+00))
       };
-      static const T denom[49] = {
+      BOOST_MATH_STATIC const T denom[49] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 0.000000000000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.586232415111681806429643551536119799691976323891200000000000000000000000e+59)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.147760594457772724544789095126583405046340554378444800000000000000000000e+60)),
@@ -2083,7 +2083,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[49] = {
+      BOOST_MATH_STATIC const T num[49] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 9.256115936295239128792053510340342045264892843178101822334871337037830072e+59)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.226382973449509462464247401218271019985727521806127065773488938845990367e+60)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 7.954125855720840120393676022050001333138789037332565663424594891457273557e+59)),
@@ -2134,7 +2134,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.012213341659767638341287600182102653785253052492980766472349845276996656e-12)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.148735984247176123115370642724455566337349193609892794757225210307646070e-15))
       };
-      static const T denom[49] = {
+      BOOST_MATH_STATIC const T denom[49] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 0.000000000000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 2.586232415111681806429643551536119799691976323891200000000000000000000000e+59)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.147760594457772724544789095126583405046340554378444800000000000000000000e+60)),
@@ -2194,7 +2194,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[48] = {
+      BOOST_MATH_STATIC const T d[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.233965513689195496302526816415068018137532804347903252026160914018410959e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, -1.432567696701419045483804034990696504881298696037704685583731202573594084e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 7.800990151010204780591569831451389602736047219596430673280355834870101274e+02)),
@@ -2257,7 +2257,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[48] = {
+      BOOST_MATH_STATIC const T d[48] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.614127734928823683399031924928203896697519780457812139739363243361356121e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, -1.873915620620241270111954934939697069495813017577862172724257417200307532e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 234, 1.020433263568799913803105156119729477192007677199414299858195073560627451e+04)),
@@ -2337,7 +2337,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[52] = {
+      BOOST_MATH_STATIC const T num[52] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 6.2155666558597192337239536765115831322604714024167432764126799013946738944179064162e+86)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 6.4127424062560995063147129656553600039438028633959646865531341376543275935920940510e+86)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 3.2432219642804430367752303997394644425738553439619047355470691880100895245432999409e+86)),
@@ -2391,7 +2391,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 6.3192906485096381210566149918556620595525679738152760526187454875638091923687554946e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 2.5066282746310005024157652848110452530069867406099383166299235763422936546004304390e+00))
       };
-      static const T denom[52] = {
+      BOOST_MATH_STATIC const T denom[52] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 0.0000000000000000000000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 3.0414093201713378043612608166064768844377641568960512000000000000000000000000000000e+64)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.3683925049359750564345782687270252191318781054337155072000000000000000000000000000e+65)),
@@ -2453,7 +2453,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
-      static const T num[52] = {
+      BOOST_MATH_STATIC const T num[52] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.2968364952374867351881152115042817894191583875220489481700563388077315440993668645e+65)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.3379758994539627857606593702434364057385206718035611620158459666404856221820703129e+65)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 6.7667661507089657936560642518188013126674666141084536651063996312630940638352438169e+64)),
@@ -2507,7 +2507,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.3184778139696006596104645792244972612333458493576785210966728195969324996631733257e-18)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 5.2299125832253333486600023635817464870204660970908989075481425992405717273229096642e-22))
       };
-      static const T denom[52] = {
+      BOOST_MATH_STATIC const T denom[52] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 0.0000000000000000000000000000000000000000000000000000000000000000000000000000000000e+00)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 3.0414093201713378043612608166064768844377641568960512000000000000000000000000000000e+64)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.3683925049359750564345782687270252191318781054337155072000000000000000000000000000e+65)),
@@ -2570,7 +2570,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[56] = {
+      BOOST_MATH_STATIC const T d[56] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.4249481633301349696310814410227012806541100102720500928500445853537331413655453290e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, -1.9263209672927829270913652941762375058727326960303110137656951784697992824730035351e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.2326134462101140657073655882621393643823409472993225649429843685598155061860815843e+03)),
@@ -2641,7 +2641,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
-      static const T d[56] = {
+      BOOST_MATH_STATIC const T d[56] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 2.1359871474796665853092357455924330354587340093067807143261699873815704783987359772e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, -2.8875414095359657817766255009397774415784763914903057809977502598124862632510767554e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 267, 1.8476787764422274017528261804071971508619123082396685980448133660376964287516316704e+04)),
@@ -2726,7 +2726,7 @@ struct undefined_lanczos : public std::integral_constant<int, (std::numeric_limi
 template <class Real, class Policy>
 struct lanczos
 {
-   static constexpr auto target_precision = policies::precision<Real, Policy>::type::value <= 0 ? (std::numeric_limits<int>::max)()-2 : 
+   BOOST_MATH_STATIC constexpr auto target_precision = policies::precision<Real, Policy>::type::value <= 0 ? (std::numeric_limits<int>::max)()-2 : 
                                                                                                    policies::precision<Real, Policy>::type::value;
 
    using type = typename std::conditional<(target_precision <= lanczos6m24::value), lanczos6m24, 

From 50d01bf0671cbb4be923ecd2ed7e5273c2ae7659 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:03:00 -0400
Subject: [PATCH 043/399] Apply GPU to rationals and series evaluations

---
 include/boost/math/tools/rational.hpp | 32 +++++++++++++--------------
 include/boost/math/tools/series.hpp   | 18 +++++++--------
 2 files changed, 25 insertions(+), 25 deletions(-)

diff --git a/include/boost/math/tools/rational.hpp b/include/boost/math/tools/rational.hpp
index 69b7251539..b65700f623 100644
--- a/include/boost/math/tools/rational.hpp
+++ b/include/boost/math/tools/rational.hpp
@@ -168,12 +168,12 @@ namespace boost{ namespace math{ namespace tools{
 // Forward declaration to keep two phase lookup happy:
 //
 template <class T, class U>
-U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U);
+BOOST_MATH_GPU_ENABLED U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U);
 
 namespace detail{
 
 template <class T, class V, class Tag>
-inline V evaluate_polynomial_c_imp(const T* a, const V& val, const Tag*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& val, const Tag*) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, val, Tag::value);
 }
@@ -186,7 +186,7 @@ inline V evaluate_polynomial_c_imp(const T* a, const V& val, const Tag*) BOOST_M
 // the loop expanded versions above:
 //
 template <class T, class U>
-inline U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    BOOST_MATH_ASSERT(count > 0);
    U sum = static_cast<U>(poly[count - 1]);
@@ -202,14 +202,14 @@ inline U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST
 // implementations above:
 //
 template <std::size_t N, class T, class V>
-inline V evaluate_polynomial(const T(&a)[N], const V& val) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const T(&a)[N], const V& val) BOOST_MATH_NOEXCEPT(V)
 {
    typedef std::integral_constant<int, N> tag_type;
    return detail::evaluate_polynomial_c_imp(static_cast<const T*>(a), val, static_cast<tag_type const*>(nullptr));
 }
 
 template <std::size_t N, class T, class V>
-inline V evaluate_polynomial(const std::array<T,N>& a, const V& val) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const std::array<T,N>& a, const V& val) BOOST_MATH_NOEXCEPT(V)
 {
    typedef std::integral_constant<int, N> tag_type;
    return detail::evaluate_polynomial_c_imp(static_cast<const T*>(a.data()), val, static_cast<tag_type const*>(nullptr));
@@ -218,19 +218,19 @@ inline V evaluate_polynomial(const std::array<T,N>& a, const V& val) BOOST_MATH_
 // Even polynomials are trivial: just square the argument!
 //
 template <class T, class U>
-inline U evaluate_even_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_even_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    return evaluate_polynomial(poly, U(z*z), count);
 }
 
 template <std::size_t N, class T, class V>
-inline V evaluate_even_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
 }
 
 template <std::size_t N, class T, class V>
-inline V evaluate_even_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
 }
@@ -238,32 +238,32 @@ inline V evaluate_even_polynomial(const std::array<T,N>& a, const V& z) BOOST_MA
 // Odd polynomials come next:
 //
 template <class T, class U>
-inline U evaluate_odd_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_odd_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    return poly[0] + z * evaluate_polynomial(poly+1, U(z*z), count-1);
 }
 
 template <std::size_t N, class T, class V>
-inline V evaluate_odd_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    typedef std::integral_constant<int, N-1> tag_type;
    return a[0] + z * detail::evaluate_polynomial_c_imp(static_cast<const T*>(a) + 1, V(z*z), static_cast<tag_type const*>(nullptr));
 }
 
 template <std::size_t N, class T, class V>
-inline V evaluate_odd_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    typedef std::integral_constant<int, N-1> tag_type;
    return a[0] + z * detail::evaluate_polynomial_c_imp(static_cast<const T*>(a.data()) + 1, V(z*z), static_cast<tag_type const*>(nullptr));
 }
 
 template <class T, class U, class V>
-V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V);
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V);
 
 namespace detail{
 
 template <class T, class U, class V, class Tag>
-inline V evaluate_rational_c_imp(const T* num, const U* denom, const V& z, const Tag*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* num, const U* denom, const V& z, const Tag*) BOOST_MATH_NOEXCEPT(V)
 {
    return boost::math::tools::evaluate_rational(num, denom, z, Tag::value);
 }
@@ -278,7 +278,7 @@ inline V evaluate_rational_c_imp(const T* num, const U* denom, const V& z, const
 // in our Lanczos code for example.
 //
 template <class T, class U, class V>
-V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V)
 {
    V z(z_);
    V s1, s2;
@@ -311,13 +311,13 @@ V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count
 }
 
 template <std::size_t N, class T, class U, class V>
-inline V evaluate_rational(const T(&a)[N], const U(&b)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const T(&a)[N], const U(&b)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return detail::evaluate_rational_c_imp(a, b, z, static_cast<const std::integral_constant<int, N>*>(nullptr));
 }
 
 template <std::size_t N, class T, class U, class V>
-inline V evaluate_rational(const std::array<T,N>& a, const std::array<U,N>& b, const V& z) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const std::array<T,N>& a, const std::array<U,N>& b, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return detail::evaluate_rational_c_imp(a.data(), b.data(), z, static_cast<std::integral_constant<int, N>*>(nullptr));
 }
diff --git a/include/boost/math/tools/series.hpp b/include/boost/math/tools/series.hpp
index a4822fea43..a4b5cc6265 100644
--- a/include/boost/math/tools/series.hpp
+++ b/include/boost/math/tools/series.hpp
@@ -21,7 +21,7 @@ namespace boost{ namespace math{ namespace tools{
 // Simple series summation come first:
 //
 template <class Functor, class U, class V>
-inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
 
@@ -44,14 +44,14 @@ inline typename Functor::result_type sum_series(Functor& func, const U& factor,
 }
 
 template <class Functor, class U>
-inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    typename Functor::result_type init_value = 0;
    return sum_series(func, factor, max_terms, init_value);
 }
 
 template <class Functor, class U>
-inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
@@ -60,7 +60,7 @@ inline typename Functor::result_type sum_series(Functor& func, int bits, std::ui
 }
 
 template <class Functor>
-inline typename Functor::result_type sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
@@ -70,7 +70,7 @@ inline typename Functor::result_type sum_series(Functor& func, int bits) noexcep
 }
 
 template <class Functor>
-inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
@@ -79,7 +79,7 @@ inline typename Functor::result_type sum_series(Functor& func, int bits, std::ui
 }
 
 template <class Functor, class U>
-inline typename Functor::result_type sum_series(Functor& func, int bits, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
    std::uintmax_t iters = (std::numeric_limits<std::uintmax_t>::max)();
@@ -89,7 +89,7 @@ inline typename Functor::result_type sum_series(Functor& func, int bits, const U
 // Checked summation:
 //
 template <class Functor, class U, class V>
-inline typename Functor::result_type checked_sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value, V& norm) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type checked_sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value, V& norm) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
 
@@ -125,7 +125,7 @@ inline typename Functor::result_type checked_sum_series(Functor& func, const U&
 // in any case the result is still much better than a naive summation.
 //
 template <class Functor>
-inline typename Functor::result_type kahan_sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
 
@@ -148,7 +148,7 @@ inline typename Functor::result_type kahan_sum_series(Functor& func, int bits) n
 }
 
 template <class Functor>
-inline typename Functor::result_type kahan_sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
 {
    BOOST_MATH_STD_USING
 

From 15bade2426618a0b2bc323a43813a87e4a2b27d0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:03:14 -0400
Subject: [PATCH 044/399] Allow beta to be used on GPU

---
 include/boost/math/special_functions/beta.hpp | 95 ++++++++++---------
 .../boost/math/special_functions/math_fwd.hpp | 54 +++++------
 2 files changed, 79 insertions(+), 70 deletions(-)

diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index c36e1f0d0c..c9b4eec2fc 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -31,14 +32,16 @@ namespace detail{
 // Implementation of Beta(a,b) using the Lanczos approximation:
 //
 template <class T, class Lanczos, class Policy>
-T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // for ADL of std names
 
+   #ifndef BOOST_MATH_NO_EXCEPTIONS
    if(a <= 0)
       return policies::raise_domain_error<T>("boost::math::beta<%1%>(%1%,%1%)", "The arguments to the beta function must be greater than zero (got a=%1%).", a, pol);
    if(b <= 0)
       return policies::raise_domain_error<T>("boost::math::beta<%1%>(%1%,%1%)", "The arguments to the beta function must be greater than zero (got b=%1%).", b, pol);
+   #endif
 
    T result;  // LCOV_EXCL_LINE
 
@@ -85,7 +88,9 @@ T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
    */
 
    if(a < b)
-      std::swap(a, b);
+   {
+      BOOST_MATH_GPU_SAFE_SWAP(a, b);
+   }
 
    // Lanczos calculation:
    T agh = static_cast<T>(a + Lanczos::g() - 0.5f);
@@ -121,7 +126,7 @@ T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
 // (Caution this is slow!!!):
 //
 template <class T, class Policy>
-T beta_imp(T a, T b, const lanczos::undefined_lanczos& l, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const lanczos::undefined_lanczos& l, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -204,7 +209,7 @@ T beta_imp(T a, T b, const lanczos::undefined_lanczos& l, const Policy& pol)
 // horrendous cancellation errors.
 //
 template <class T, class Lanczos, class Policy>
-T ibeta_power_terms(T a,
+BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
                         T b,
                         T x,
                         T y,
@@ -445,7 +450,7 @@ T ibeta_power_terms(T a,
 // This version is generic, slow, and does not use the Lanczos approximation.
 //
 template <class T, class Policy>
-T ibeta_power_terms(T a,
+BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
                         T b,
                         T x,
                         T y,
@@ -554,7 +559,7 @@ T ibeta_power_terms(T a,
          // exp(a * log1p((xb - ya) / a + p + p(xb - ya) / a))
          //
          // Analogously, when a > b we can just swap all the terms around.
-         // 
+         //
          // Finally, there are a few cases (x or y is unity) when the above logic can't be used
          // or where there is no logarithmic cancellation and accuracy is better just using
          // the regular formula:
@@ -628,8 +633,8 @@ template <class T>
 struct ibeta_series_t
 {
    typedef T result_type;
-   ibeta_series_t(T a_, T b_, T x_, T mult) : result(mult), x(x_), apn(a_), poch(1-b_), n(1) {}
-   T operator()()
+   BOOST_MATH_GPU_ENABLED ibeta_series_t(T a_, T b_, T x_, T mult) : result(mult), x(x_), apn(a_), poch(1-b_), n(1) {}
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = result / apn;
       apn += 1;
@@ -644,7 +649,7 @@ struct ibeta_series_t
 };
 
 template <class T, class Lanczos, class Policy>
-T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool normalised, T* p_derivative, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool normalised, T* p_derivative, T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -722,7 +727,7 @@ T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool normalised, T* p_deriva
 // Incomplete Beta series again, this time without Lanczos support:
 //
 template <class T, class Policy>
-T ibeta_series(T a, T b, T x, T s0, const boost::math::lanczos::undefined_lanczos& l, bool normalised, T* p_derivative, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::lanczos::undefined_lanczos& l, bool normalised, T* p_derivative, T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -788,9 +793,9 @@ struct ibeta_fraction2_t
 {
    typedef std::pair<T, T> result_type;
 
-   ibeta_fraction2_t(T a_, T b_, T x_, T y_) : a(a_), b(b_), x(x_), y(y_), m(0) {}
+   BOOST_MATH_GPU_ENABLED ibeta_fraction2_t(T a_, T b_, T x_, T y_) : a(a_), b(b_), x(x_), y(y_), m(0) {}
 
-   result_type operator()()
+   BOOST_MATH_GPU_ENABLED result_type operator()()
    {
       T aN = (a + m - 1) * (a + b + m - 1) * m * (b - m) * x * x;
       T denom = (a + 2 * m - 1);
@@ -813,7 +818,7 @@ struct ibeta_fraction2_t
 // Evaluate the incomplete beta via the continued fraction representation:
 //
 template <class T, class Policy>
-inline T ibeta_fraction2(T a, T b, T x, T y, const Policy& pol, bool normalised, T* p_derivative)
+BOOST_MATH_GPU_ENABLED inline T ibeta_fraction2(T a, T b, T x, T y, const Policy& pol, bool normalised, T* p_derivative)
 {
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
    BOOST_MATH_STD_USING
@@ -836,7 +841,7 @@ inline T ibeta_fraction2(T a, T b, T x, T y, const Policy& pol, bool normalised,
 // Computes the difference between ibeta(a,b,x) and ibeta(a+k,b,x):
 //
 template <class T, class Policy>
-T ibeta_a_step(T a, T b, T x, T y, int k, const Policy& pol, bool normalised, T* p_derivative)
+BOOST_MATH_GPU_ENABLED T ibeta_a_step(T a, T b, T x, T y, int k, const Policy& pol, bool normalised, T* p_derivative)
 {
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
 
@@ -870,7 +875,7 @@ T ibeta_a_step(T a, T b, T x, T y, int k, const Policy& pol, bool normalised, T*
 // it is currently only called for small k.
 //
 template <class T>
-inline T rising_factorial_ratio(T a, T b, int k)
+BOOST_MATH_GPU_ENABLED inline T rising_factorial_ratio(T a, T b, int k)
 {
    // calculate:
    // (a)(a+1)(a+2)...(a+k-1)
@@ -911,13 +916,17 @@ template <>
 struct Pn_size<float>
 {
    static constexpr unsigned value = 15; // ~8-15 digit accuracy
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
    static_assert(::boost::math::max_factorial<float>::value >= 30, "Type does not provide for 8-15 digits of accuracy.");
+#endif
 };
 template <>
 struct Pn_size<double>
 {
    static constexpr unsigned value = 30; // 16-20 digit accuracy
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
    static_assert(::boost::math::max_factorial<double>::value >= 60, "Type does not provide for 16-20 digits of accuracy.");
+#endif
 };
 template <>
 struct Pn_size<long double>
@@ -927,7 +936,7 @@ struct Pn_size<long double>
 };
 
 template <class T, class Policy>
-T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& pol, bool normalised)
+BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& pol, bool normalised)
 {
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
    BOOST_MATH_STD_USING
@@ -1033,7 +1042,7 @@ T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& po
 // complement of the binomial distribution cdf and use this finite sum.
 //
 template <class T, class Policy>
-T binomial_ccdf(T n, T k, T x, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T binomial_ccdf(T n, T k, T x, T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -1098,7 +1107,7 @@ T binomial_ccdf(T n, T k, T x, T y, const Policy& pol)
 // each domain:
 //
 template <class T, class Policy>
-T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_derivative)
+BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_derivative)
 {
    static const char* function = "boost::math::ibeta<%1%>(%1%, %1%, %1%)";
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
@@ -1184,8 +1193,8 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
    }
    if(a == 1)
    {
-      std::swap(a, b);
-      std::swap(x, y);
+      BOOST_MATH_GPU_SAFE_SWAP(a, b);
+      BOOST_MATH_GPU_SAFE_SWAP(x, y);
       invert = !invert;
    }
    if(b == 1)
@@ -1218,8 +1227,8 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
    {
       if(x > 0.5)
       {
-         std::swap(a, b);
-         std::swap(x, y);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
          invert = !invert;
          BOOST_MATH_INSTRUMENT_VARIABLE(invert);
       }
@@ -1243,8 +1252,8 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
          }
          else
          {
-            std::swap(a, b);
-            std::swap(x, y);
+            BOOST_MATH_GPU_SAFE_SWAP(a, b);
+            BOOST_MATH_GPU_SAFE_SWAP(x, y);
             invert = !invert;
             if(y >= 0.3)
             {
@@ -1309,8 +1318,8 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
          }
          else
          {
-            std::swap(a, b);
-            std::swap(x, y);
+            BOOST_MATH_GPU_SAFE_SWAP(a, b);
+            BOOST_MATH_GPU_SAFE_SWAP(x, y);
             invert = !invert;
 
             if(y >= 0.3)
@@ -1387,8 +1396,8 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
       }
       if(lambda < 0)
       {
-         std::swap(a, b);
-         std::swap(x, y);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
          invert = !invert;
          BOOST_MATH_INSTRUMENT_VARIABLE(invert);
       }
@@ -1502,13 +1511,13 @@ T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_de
 } // template <class T, class Lanczos>T ibeta_imp(T a, T b, T x, const Lanczos& l, bool inv, bool normalised)
 
 template <class T, class Policy>
-inline T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised)
+BOOST_MATH_GPU_ENABLED inline T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised)
 {
    return ibeta_imp(a, b, x, pol, inv, normalised, static_cast<T*>(nullptr));
 }
 
 template <class T, class Policy>
-T ibeta_derivative_imp(T a, T b, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ibeta_derivative_imp(T a, T b, T x, const Policy& pol)
 {
    static const char* function = "ibeta_derivative<%1%>(%1%,%1%,%1%)";
    //
@@ -1559,7 +1568,7 @@ T ibeta_derivative_imp(T a, T b, T x, const Policy& pol)
 // Some forwarding functions that disambiguate the third argument type:
 //
 template <class RT1, class RT2, class Policy>
-inline typename tools::promote_args<RT1, RT2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2>::type
    beta(RT1 a, RT2 b, const Policy&, const std::true_type*)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1576,7 +1585,7 @@ inline typename tools::promote_args<RT1, RT2>::type
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::beta_imp(static_cast<value_type>(a), static_cast<value_type>(b), evaluation_type(), forwarding_policy()), "boost::math::beta<%1%>(%1%,%1%)");
 }
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    beta(RT1 a, RT2 b, RT3 x, const std::false_type*)
 {
    return boost::math::beta(a, b, x, policies::policy<>());
@@ -1589,7 +1598,7 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
 // and forward to the implementation functions:
 //
 template <class RT1, class RT2, class A>
-inline typename tools::promote_args<RT1, RT2, A>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, A>::type
    beta(RT1 a, RT2 b, A arg)
 {
    using tag = typename policies::is_policy<A>::type;
@@ -1598,14 +1607,14 @@ inline typename tools::promote_args<RT1, RT2, A>::type
 }
 
 template <class RT1, class RT2>
-inline typename tools::promote_args<RT1, RT2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2>::type
    beta(RT1 a, RT2 b)
 {
    return boost::math::beta(a, b, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    beta(RT1 a, RT2 b, RT3 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1622,7 +1631,7 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    betac(RT1 a, RT2 b, RT3 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1638,14 +1647,14 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::ibeta_imp(static_cast<value_type>(a), static_cast<value_type>(b), static_cast<value_type>(x), forwarding_policy(), true, false), "boost::math::betac<%1%>(%1%,%1%,%1%)");
 }
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    betac(RT1 a, RT2 b, RT3 x)
 {
    return boost::math::betac(a, b, x, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibeta(RT1 a, RT2 b, RT3 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1661,14 +1670,14 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::ibeta_imp(static_cast<value_type>(a), static_cast<value_type>(b), static_cast<value_type>(x), forwarding_policy(), false, true), "boost::math::ibeta<%1%>(%1%,%1%,%1%)");
 }
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibeta(RT1 a, RT2 b, RT3 x)
 {
    return boost::math::ibeta(a, b, x, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibetac(RT1 a, RT2 b, RT3 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1684,14 +1693,14 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::ibeta_imp(static_cast<value_type>(a), static_cast<value_type>(b), static_cast<value_type>(x), forwarding_policy(), true, true), "boost::math::ibetac<%1%>(%1%,%1%,%1%)");
 }
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibetac(RT1 a, RT2 b, RT3 x)
 {
    return boost::math::ibetac(a, b, x, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibeta_derivative(RT1 a, RT2 b, RT3 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1707,7 +1716,7 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::ibeta_derivative_imp(static_cast<value_type>(a), static_cast<value_type>(b), static_cast<value_type>(x), forwarding_policy()), "boost::math::ibeta_derivative<%1%>(%1%,%1%,%1%)");
 }
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibeta_derivative(RT1 a, RT2 b, RT3 x)
 {
    return boost::math::ibeta_derivative(a, b, x, policies::policy<>());
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index ee43684ce6..6119c8e863 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -39,111 +39,111 @@ namespace boost
 
    // Beta functions.
    template <class RT1, class RT2>
-   tools::promote_args_t<RT1, RT2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2>
          beta(RT1 a, RT2 b); // Beta function (2 arguments).
 
    template <class RT1, class RT2, class A>
-   tools::promote_args_t<RT1, RT2, A>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, A>
          beta(RT1 a, RT2 b, A x); // Beta function (3 arguments).
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          beta(RT1 a, RT2 b, RT3 x, const Policy& pol); // Beta function (3 arguments).
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          betac(RT1 a, RT2 b, RT3 x);
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          betac(RT1 a, RT2 b, RT3 x, const Policy& pol);
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta(RT1 a, RT2 b, RT3 x); // Incomplete beta function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta(RT1 a, RT2 b, RT3 x, const Policy& pol); // Incomplete beta function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac(RT1 a, RT2 b, RT3 x); // Incomplete beta complement function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac(RT1 a, RT2 b, RT3 x, const Policy& pol); // Incomplete beta complement function.
 
    template <class T1, class T2, class T3, class T4>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ibeta_inv(T1 a, T2 b, T3 p, T4* py);
 
    template <class T1, class T2, class T3, class T4, class Policy>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ibeta_inv(T1 a, T2 b, T3 p, T4* py, const Policy& pol);
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_inv(RT1 a, RT2 b, RT3 p); // Incomplete beta inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_inv(RT1 a, RT2 b, RT3 p, const Policy&); // Incomplete beta inverse function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_inva(RT1 a, RT2 b, RT3 p); // Incomplete beta inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_inva(RT1 a, RT2 b, RT3 p, const Policy&); // Incomplete beta inverse function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_invb(RT1 a, RT2 b, RT3 p); // Incomplete beta inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_invb(RT1 a, RT2 b, RT3 p, const Policy&); // Incomplete beta inverse function.
 
    template <class T1, class T2, class T3, class T4>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ibetac_inv(T1 a, T2 b, T3 q, T4* py);
 
    template <class T1, class T2, class T3, class T4, class Policy>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ibetac_inv(T1 a, T2 b, T3 q, T4* py, const Policy& pol);
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_inv(RT1 a, RT2 b, RT3 q); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_inv(RT1 a, RT2 b, RT3 q, const Policy&); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_inva(RT1 a, RT2 b, RT3 q); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_inva(RT1 a, RT2 b, RT3 q, const Policy&); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_invb(RT1 a, RT2 b, RT3 q); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibetac_invb(RT1 a, RT2 b, RT3 q, const Policy&); // Incomplete beta complement inverse function.
 
    template <class RT1, class RT2, class RT3>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_derivative(RT1 a, RT2 b, RT3 x);  // derivative of incomplete beta
 
    template <class RT1, class RT2, class RT3, class Policy>
-   tools::promote_args_t<RT1, RT2, RT3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2, RT3>
          ibeta_derivative(RT1 a, RT2 b, RT3 x, const Policy& pol);  // derivative of incomplete beta
 
    // Binomial:

From 4f555750f9e51b13fdf3064928bbd9afa69444f2 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:29:36 -0400
Subject: [PATCH 045/399] Disable SSE2 lanczos on GPU

---
 include/boost/math/special_functions/lanczos.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/lanczos.hpp b/include/boost/math/special_functions/lanczos.hpp
index 7a1934c80c..b804bf8294 100644
--- a/include/boost/math/special_functions/lanczos.hpp
+++ b/include/boost/math/special_functions/lanczos.hpp
@@ -2748,7 +2748,7 @@ struct lanczos
 } // namespace boost
 
 #if !defined(_CRAYC) && !defined(__CUDACC__) && (!defined(__GNUC__) || (__GNUC__ > 3) || ((__GNUC__ == 3) && (__GNUC_MINOR__ > 3)))
-#if ((defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(__SSE2__) || defined(_M_AMD64) || defined(_M_X64)) && !defined(_MANAGED)
+#if ((defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(__SSE2__) || defined(_M_AMD64) || defined(_M_X64)) && !defined(_MANAGED) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
 #include <boost/math/special_functions/detail/lanczos_sse2.hpp>
 #endif
 #endif

From 47282d3af5485d62bdcc463bd5f85fed3fef86d0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 22 Jul 2024 15:39:59 -0400
Subject: [PATCH 046/399] Changes to allow beta on SYCL

---
 include/boost/math/special_functions/beta.hpp |  4 +-
 .../special_functions/detail/ibeta_inv_ab.hpp | 52 +++++++++----------
 .../detail/ibeta_inverse.hpp                  |  4 +-
 3 files changed, 30 insertions(+), 30 deletions(-)

diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index c9b4eec2fc..769c4589a3 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -1109,7 +1109,7 @@ BOOST_MATH_GPU_ENABLED T binomial_ccdf(T n, T k, T x, T y, const Policy& pol)
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_derivative)
 {
-   static const char* function = "boost::math::ibeta<%1%>(%1%, %1%, %1%)";
+   constexpr auto function = "boost::math::ibeta<%1%>(%1%, %1%, %1%)";
    typedef typename lanczos::lanczos<T, Policy>::type lanczos_type;
    BOOST_MATH_STD_USING // for ADL of std math functions.
 
@@ -1519,7 +1519,7 @@ BOOST_MATH_GPU_ENABLED inline T ibeta_imp(T a, T b, T x, const Policy& pol, bool
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_derivative_imp(T a, T b, T x, const Policy& pol)
 {
-   static const char* function = "ibeta_derivative<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "ibeta_derivative<%1%>(%1%,%1%,%1%)";
    //
    // start with the usual error checks:
    //
diff --git a/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp b/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
index 0ce0d7560e..9e30db2a37 100644
--- a/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
+++ b/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
@@ -173,7 +173,7 @@ typename tools::promote_args<RT1, RT2, RT3>::type
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   static const char* function = "boost::math::ibeta_inva<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ibeta_inva<%1%>(%1%,%1%,%1%)";
    if(p == 0)
    {
       return policies::raise_overflow_error<result_type>(function, 0, Policy());
@@ -185,28 +185,28 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::ibeta_inv_ab_imp(
-         static_cast<value_type>(b), 
-         static_cast<value_type>(x), 
-         static_cast<value_type>(p), 
-         static_cast<value_type>(1 - static_cast<value_type>(p)), 
-         false, pol), 
+         static_cast<value_type>(b),
+         static_cast<value_type>(x),
+         static_cast<value_type>(p),
+         static_cast<value_type>(1 - static_cast<value_type>(p)),
+         false, pol),
       function);
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type 
+typename tools::promote_args<RT1, RT2, RT3>::type
       ibetac_inva(RT1 b, RT2 x, RT3 q, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
-      Policy, 
-      policies::promote_float<false>, 
-      policies::promote_double<false>, 
+      Policy,
+      policies::promote_float<false>,
+      policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   static const char* function = "boost::math::ibetac_inva<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ibetac_inva<%1%>(%1%,%1%,%1%)";
    if(q == 1)
    {
       return policies::raise_overflow_error<result_type>(function, 0, Policy());
@@ -218,28 +218,28 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::ibeta_inv_ab_imp(
-         static_cast<value_type>(b), 
-         static_cast<value_type>(x), 
-         static_cast<value_type>(1 - static_cast<value_type>(q)), 
-         static_cast<value_type>(q), 
+         static_cast<value_type>(b),
+         static_cast<value_type>(x),
+         static_cast<value_type>(1 - static_cast<value_type>(q)),
+         static_cast<value_type>(q),
          false, pol),
       function);
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type 
+typename tools::promote_args<RT1, RT2, RT3>::type
       ibeta_invb(RT1 a, RT2 x, RT3 p, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
-      Policy, 
-      policies::promote_float<false>, 
-      policies::promote_double<false>, 
+      Policy,
+      policies::promote_float<false>,
+      policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   static const char* function = "boost::math::ibeta_invb<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ibeta_invb<%1%>(%1%,%1%,%1%)";
    if(p == 0)
    {
       return tools::min_value<result_type>();
@@ -251,19 +251,19 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(
       detail::ibeta_inv_ab_imp(
-         static_cast<value_type>(a), 
-         static_cast<value_type>(x), 
-         static_cast<value_type>(p), 
-         static_cast<value_type>(1 - static_cast<value_type>(p)), 
+         static_cast<value_type>(a),
+         static_cast<value_type>(x),
+         static_cast<value_type>(p),
+         static_cast<value_type>(1 - static_cast<value_type>(p)),
          true, pol),
       function);
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type 
+typename tools::promote_args<RT1, RT2, RT3>::type
       ibetac_invb(RT1 a, RT2 x, RT3 q, const Policy& pol)
 {
-   static const char* function = "boost::math::ibeta_invb<%1%>(%1%, %1%, %1%)";
+   constexpr auto function = "boost::math::ibeta_invb<%1%>(%1%, %1%, %1%)";
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::normalise<
diff --git a/include/boost/math/special_functions/detail/ibeta_inverse.hpp b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
index 70f17a0b1a..9e4fb08d4e 100644
--- a/include/boost/math/special_functions/detail/ibeta_inverse.hpp
+++ b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
@@ -971,7 +971,7 @@ template <class T1, class T2, class T3, class T4, class Policy>
 inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibeta_inv(T1 a, T2 b, T3 p, T4* py, const Policy& pol)
 {
-   static const char* function = "boost::math::ibeta_inv<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ibeta_inv<%1%>(%1%,%1%,%1%)";
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T1, T2, T3, T4>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -1029,7 +1029,7 @@ template <class T1, class T2, class T3, class T4, class Policy>
 inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibetac_inv(T1 a, T2 b, T3 q, T4* py, const Policy& pol)
 {
-   static const char* function = "boost::math::ibetac_inv<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ibetac_inv<%1%>(%1%,%1%,%1%)";
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T1, T2, T3, T4>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;

From 72afe906469038372e8ef786dbf63b6af887fbd7 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 23 Jul 2024 22:56:27 +0900
Subject: [PATCH 047/399] Add mapairy document graphs

---
 doc/distributions/mapairy.qbk           |   21 +-
 doc/equations/mapairy_ref1.svg          |   86 ++
 doc/graphs/mapairy_ccdf_accuracy_64.png |  Bin 0 -> 42101 bytes
 doc/graphs/mapairy_cdf_accuracy_64.png  |  Bin 0 -> 37709 bytes
 doc/graphs/mapairy_pdf1.svg             | 1465 +++++++++++++++++++++++
 doc/graphs/mapairy_pdf2.svg             | 1414 ++++++++++++++++++++++
 doc/graphs/mapairy_pdf_accuracy_64.png  |  Bin 0 -> 44189 bytes
 7 files changed, 2982 insertions(+), 4 deletions(-)
 create mode 100644 doc/equations/mapairy_ref1.svg
 create mode 100644 doc/graphs/mapairy_ccdf_accuracy_64.png
 create mode 100644 doc/graphs/mapairy_cdf_accuracy_64.png
 create mode 100644 doc/graphs/mapairy_pdf1.svg
 create mode 100644 doc/graphs/mapairy_pdf2.svg
 create mode 100644 doc/graphs/mapairy_pdf_accuracy_64.png

diff --git a/doc/distributions/mapairy.qbk b/doc/distributions/mapairy.qbk
index e10f598cec..97d624a932 100644
--- a/doc/distributions/mapairy.qbk
+++ b/doc/distributions/mapairy.qbk
@@ -29,11 +29,11 @@ This distribution is also defined as [beta] = −1, which is inverted about the
 [@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
 given by:
 
-[equation mapairy_ref1]
+[equation mapairy_ref1]  [/f(x; \mu=0, c=1/\sqrt[3]{18}) = 2 \exp \left( \frac{2}{3} x^3 \right) \left( -x \mathrm{Ai}(x^2) - \mathrm{Ai}'(x^2) \right)]
 
 The location parameter [mu] is the location of the distribution,
 while the scale parameter [c] determines the width of the distribution.  If the location is
-zero, and the scale 1, then the result is a standard mapairy
+zero, and the scale 1, then the result is a standard map-airy
 distribution.
 
 The distribution describes the probability distribution of the area under a Brownian excursion over a unit interval.
@@ -55,7 +55,7 @@ the distribution:
 Constructs a mapairy distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
 values (location = 0, scale = 1)
-then the result is a Standard mapairy Distribution.
+then the result is a Standard map-airy Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
 
@@ -72,7 +72,7 @@ Returns the scale parameter of the distribution.
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
 
-Note however that the mapairy distribution does not have a skewness,
+Note however that the map-airy distribution does not have a skewness,
 kurtosis, etc. See __math_undefined
 [/link math_toolkit.pol_ref.assert_undefined mathematically undefined function]
 to control whether these should fail to compile with a BOOST_STATIC_ASSERTION_FAILURE,
@@ -87,6 +87,18 @@ The domain of the random variable is \[-[max_value], +[min_value]\].
 
 The error is within 4 epsilon except for the rapidly decaying left tail.
 
+Errors in the PDF at 64-bit double precision:
+
+[$../graphs/mapairy_pdf_accuracy_64.png]
+
+Errors in the CDF at 64-bit double precision:
+
+[$../graphs/mapairy_cdf_accuracy_64.png]
+
+Errors in the CDF-complement at 64-bit double precision:
+
+[$../graphs/mapairy_ccdf_accuracy_64.png]
+
 [h4 Implementation]
 
 See references.
@@ -100,6 +112,7 @@ DOI: 10.36227/techrxiv.172053942.27675733/v1, 2024.
 [endsect][/section:mapairy_dist mapairy]
 
 [/ mapairy.qbk
+  Copyright Takuma Yoshimura 2024.
   Distributed under the Boost Software License, Version 1.0.
   (See accompanying file LICENSE_1_0.txt or copy at
   http://www.boost.org/LICENSE_1_0.txt).
diff --git a/doc/equations/mapairy_ref1.svg b/doc/equations/mapairy_ref1.svg
new file mode 100644
index 0000000000..f0052a3bac
--- /dev/null
+++ b/doc/equations/mapairy_ref1.svg
@@ -0,0 +1,86 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<!-- This file was generated by dvisvgm 3.0.3 -->
+<svg version='1.1' xmlns='http://www.w3.org/2000/svg' xmlns:xlink='http://www.w3.org/1999/xlink' width='263.480388pt' height='23.910579pt' viewBox='101.883774 63.760885 263.480388 23.910579'>
+<defs>
+<path id='g1-48' d='M2.022416-3.291656C2.078207-3.410212 2.085181-3.466002 2.085181-3.514819C2.085181-3.731009 1.889913-3.898381 1.673724-3.898381C1.408717-3.898381 1.325031-3.682192 1.290162-3.57061L.369614-.550934C.36264-.536986 .334745-.446326 .334745-.439352C.334745-.355666 .550934-.285928 .606725-.285928C.655542-.285928 .662516-.299875 .711333-.404483L2.022416-3.291656Z'/>
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From f2a0fc9723e78402aca0fb4f5058ac7dcdbbdc4a Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 23 Jul 2024 23:12:01 +0900
Subject: [PATCH 048/399] Add holtsmark document graphs

---
 doc/distributions/holtsmark.qbk           |   11 +-
 doc/equations/holtsmark_ref1.svg          |   78 ++
 doc/graphs/holtsmark_ccdf_accuracy_64.png |  Bin 0 -> 44433 bytes
 doc/graphs/holtsmark_pdf1.svg             | 1525 +++++++++++++++++++++
 doc/graphs/holtsmark_pdf2.svg             | 1423 +++++++++++++++++++
 doc/graphs/holtsmark_pdf_accuracy_64.png  |  Bin 0 -> 47341 bytes
 6 files changed, 3036 insertions(+), 1 deletion(-)
 create mode 100644 doc/equations/holtsmark_ref1.svg
 create mode 100644 doc/graphs/holtsmark_ccdf_accuracy_64.png
 create mode 100644 doc/graphs/holtsmark_pdf1.svg
 create mode 100644 doc/graphs/holtsmark_pdf2.svg
 create mode 100644 doc/graphs/holtsmark_pdf_accuracy_64.png

diff --git a/doc/distributions/holtsmark.qbk b/doc/distributions/holtsmark.qbk
index 5a0d41fb2b..49149ab929 100644
--- a/doc/distributions/holtsmark.qbk
+++ b/doc/distributions/holtsmark.qbk
@@ -29,7 +29,7 @@ with shape parameter [alpha]=3/2, [beta]=0.
 [@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
 given by:
 
-[equation holtsmark_ref1]
+[equation holtsmark_ref1]  [/f(x; \mu, c)=\frac{1}{2 \pi} \int_{-\infty}^{\infty} \exp( i t \mu - |c t|^{3/2} ) e^{-i x t} dt]
 
 The location parameter [mu] is the location of the distribution,
 while the scale parameter [c] determines the width of the distribution.
@@ -88,6 +88,14 @@ The domain of the random variable is \[-[max_value], +[min_value]\].
 
 The error is within 4 epsilon.
 
+Errors in the PDF at 64-bit double precision:
+
+[$../graphs/holtsmark_pdf_accuracy_64.png]
+
+Errors in the CDF-complement at 64-bit double precision:
+
+[$../graphs/holtsmark_ccdf_accuracy_64.png]
+
 [h4 Implementation]
 
 See references.
@@ -101,6 +109,7 @@ DOI: 10.36227/techrxiv.172054657.73020014/v1, 2024.
 [endsect][/section:holtsmark_dist holtsmark]
 
 [/ holtsmark.qbk
+  Copyright Takuma Yoshimura 2024.
   Distributed under the Boost Software License, Version 1.0.
   (See accompanying file LICENSE_1_0.txt or copy at
   http://www.boost.org/LICENSE_1_0.txt).
diff --git a/doc/equations/holtsmark_ref1.svg b/doc/equations/holtsmark_ref1.svg
new file mode 100644
index 0000000000..77e97352ec
--- /dev/null
+++ b/doc/equations/holtsmark_ref1.svg
@@ -0,0 +1,78 @@
+<?xml version='1.0' encoding='UTF-8'?>
+<!-- This file was generated by dvisvgm 3.0.3 -->
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From e407cadd0d9fcbf6015dc7c7202942cd1ee02282 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Tue, 23 Jul 2024 23:21:22 +0900
Subject: [PATCH 049/399] Add saspoint5 document graphs

---
 doc/distributions/saspoint5.qbk           |   14 +-
 doc/equations/saspoint5_ref1.svg          |   75 ++
 doc/graphs/saspoint5_ccdf_accuracy_64.png |  Bin 0 -> 44301 bytes
 doc/graphs/saspoint5_pdf1.svg             | 1445 +++++++++++++++++++++
 doc/graphs/saspoint5_pdf2.svg             | 1340 +++++++++++++++++++
 doc/graphs/saspoint5_pdf_accuracy_64.png  |  Bin 0 -> 44860 bytes
 6 files changed, 2871 insertions(+), 3 deletions(-)
 create mode 100644 doc/equations/saspoint5_ref1.svg
 create mode 100644 doc/graphs/saspoint5_ccdf_accuracy_64.png
 create mode 100644 doc/graphs/saspoint5_pdf1.svg
 create mode 100644 doc/graphs/saspoint5_pdf2.svg
 create mode 100644 doc/graphs/saspoint5_pdf_accuracy_64.png

diff --git a/doc/distributions/saspoint5.qbk b/doc/distributions/saspoint5.qbk
index a5b818eb9a..1421b5bac2 100644
--- a/doc/distributions/saspoint5.qbk
+++ b/doc/distributions/saspoint5.qbk
@@ -27,7 +27,7 @@ with shape parameter [alpha]=1/2, [beta]=0.
 [@http://en.wikipedia.org/wiki/Probability_distribution probability distribution function PDF]
 given by:
 
-[equation saspoint5_ref1]
+[equation saspoint5_ref1]  [/f(x; \mu, c)=\frac{1}{2 \pi} \int_{-\infty}^{\infty} \exp( i t \mu - \sqrt{|c t|} ) e^{-i x t} dt]
 
 The location parameter [mu] is the location of the distribution,
 while the scale parameter [c] determines the width of the distribution.
@@ -85,8 +85,15 @@ The domain of the random variable is \[-[max_value], +[min_value]\].
 
 [h4 Accuracy]
 
-For float64, the error is within 4 epsilons.
-For float128, the error is within 4 epsilons except the peak.
+The error is within 4 epsilon.
+
+Errors in the PDF at 64-bit double precision:
+
+[$../graphs/saspoint5_pdf_accuracy_64.png]
+
+Errors in the CDF-complement at 64-bit double precision:
+
+[$../graphs/saspoint5_ccdf_accuracy_64.png]
 
 [h4 Implementation]
 
@@ -100,6 +107,7 @@ DOI: 10.36227/techrxiv.172055253.37208198/v1, 2024.
 [endsect][/section:saspoint5_dist saspoint5]
 
 [/ saspoint5.qbk
+  Copyright Takuma Yoshimura 2024.
   Distributed under the Boost Software License, Version 1.0.
   (See accompanying file LICENSE_1_0.txt or copy at
   http://www.boost.org/LICENSE_1_0.txt).
diff --git a/doc/equations/saspoint5_ref1.svg b/doc/equations/saspoint5_ref1.svg
new file mode 100644
index 0000000000..b013598e24
--- /dev/null
+++ b/doc/equations/saspoint5_ref1.svg
@@ -0,0 +1,75 @@
+<?xml version='1.0' encoding='UTF-8'?>
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z?=U0bd`F9Ka+<s?zS8c`EAA}+^gl%$|NlHWU}<&zgUNrmY$QX;%SfM*Jsp2i>(2iI
D#3cOr

literal 0
HcmV?d00001


From 308bf4de04d4d81f29477c8118d9a1ab10bbff0d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:38:12 -0400
Subject: [PATCH 050/399] Fix cauchy linker errror

---
 test/test_cauchy.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/test_cauchy.cpp b/test/test_cauchy.cpp
index 002690e5f8..096858d845 100644
--- a/test/test_cauchy.cpp
+++ b/test/test_cauchy.cpp
@@ -23,12 +23,12 @@
 #include <boost/math/distributions/cauchy.hpp>
     using boost::math::cauchy_distribution;
 
-#include "test_out_of_range.hpp"
-
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
+#include "test_out_of_range.hpp"
+
 #include <iostream>
    using std::cout;
    using std::endl;

From 38596e29d3567769f65fc8b51314069decddd7a4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 11:47:07 -0400
Subject: [PATCH 051/399] Reactivate domain error for beta

---
 include/boost/math/special_functions/beta.hpp | 2 --
 1 file changed, 2 deletions(-)

diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 769c4589a3..25e524d0b3 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -36,12 +36,10 @@ BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // for ADL of std names
 
-   #ifndef BOOST_MATH_NO_EXCEPTIONS
    if(a <= 0)
       return policies::raise_domain_error<T>("boost::math::beta<%1%>(%1%,%1%)", "The arguments to the beta function must be greater than zero (got a=%1%).", a, pol);
    if(b <= 0)
       return policies::raise_domain_error<T>("boost::math::beta<%1%>(%1%,%1%)", "The arguments to the beta function must be greater than zero (got b=%1%).", b, pol);
-   #endif
 
    T result;  // LCOV_EXCL_LINE
 

From 548d6f5f4507d044639f6415865733a7c3bd4394 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 11:30:03 -0400
Subject: [PATCH 052/399] Ignore float too small errors

---
 test/beta_med_data.ipp | 4 ++++
 test/test_beta.hpp     | 4 ++++
 2 files changed, 8 insertions(+)

diff --git a/test/beta_med_data.ipp b/test/beta_med_data.ipp
index b1f35d98e1..eb3e884b8c 100644
--- a/test/beta_med_data.ipp
+++ b/test/beta_med_data.ipp
@@ -3,6 +3,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifdef __CUDACC__
+#pragma nv_diag_suppress 221
+#endif
+
    static const std::array<std::array<typename table_type<T>::type, 3>, 1830> beta_med_data = { {
       {{ SC_(0.4883005917072296142578125), SC_(0.4883005917072296142578125), SC_(3.245912809500479157065104747353807392371) }}, 
       {{ SC_(3.5808107852935791015625), SC_(0.4883005917072296142578125), SC_(1.007653173802923954909901438393379243537) }}, 
diff --git a/test/test_beta.hpp b/test/test_beta.hpp
index 63a07d18f5..e633935a3c 100644
--- a/test/test_beta.hpp
+++ b/test/test_beta.hpp
@@ -10,6 +10,10 @@
 # pragma warning (disable : 4180) // qualifier applied to function type has no meaning; ignored
 #endif
 
+#ifdef __CUDACC__
+#pragma nv_diag_suppress 221
+#endif
+
 #include <boost/math/concepts/real_concept.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>

From 7c9c76101a9517e4f04e36a0967f4d3747b6ebf9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:05:48 -0400
Subject: [PATCH 053/399] Remove SYCL macros from errno calls

---
 include/boost/math/policies/error_handling.hpp | 16 ----------------
 1 file changed, 16 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 6509b47c34..1329dba10b 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -233,9 +233,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
            const T& ,
            const ::boost::math::policies::domain_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return BOOST_MATH_QUIET_NAN(T);
@@ -381,9 +379,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* ,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
@@ -396,9 +392,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const T&,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
@@ -459,9 +453,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_underflow_error(
            const char* /* message */,
            const  ::boost::math::policies::underflow_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return T(0);
@@ -511,9 +503,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_denorm_error(
            const T& val,
            const  ::boost::math::policies::denorm_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return val;
@@ -564,9 +554,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_evaluation_error(
            const T& val,
            const  ::boost::math::policies::evaluation_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return val;
@@ -621,9 +609,7 @@ BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
            const TargetType&,
            const  ::boost::math::policies::rounding_error< ::boost::math::policies::errno_on_error>&) BOOST_MATH_NOEXCEPT(T)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = ERANGE;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    static_assert(std::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
@@ -678,9 +664,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
            const R& result,
            const ::boost::math::policies::indeterminate_result_error< ::boost::math::policies::errno_on_error>&)
 {
-   #ifndef BOOST_MATH_SYCL_ENABLED
    errno = EDOM;
-   #endif
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
    return result;

From f3f03c8f831c6f2167ca98a8792f5b0283ceb680 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:22:33 -0400
Subject: [PATCH 054/399] Adjust default policy for GPU cases

---
 include/boost/math/policies/policy.hpp | 34 ++++++++++++++++++++++++++
 1 file changed, 34 insertions(+)

diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index 5f3dfa7b50..a819a4cb6b 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -33,6 +33,40 @@ namespace policies{
 //
 // Define macros for our default policies, if they're not defined already:
 //
+
+
+//
+// Generic support for GPUs
+//
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+#  ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#    define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#  endif
+#  ifndef BOOST_MATH_PROMOTE_DOUBLE_POLICY
+#     define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+#  endif
+#endif
+
+//
+// Refined support for sycl since it does not support errno
+//
+
+#ifdef BOOST_MATH_ENABLE_SYCL
+#  ifndef BOOST_MATH_DOMAIN_ERROR_POLICY
+#    define BOOST_MATH_DOMAIN_ERROR_POLICY ignore_error
+#  endif
+#  ifndef BOOST_MATH_POLE_ERROR_POLICY
+#     define BOOST_MATH_POLE_ERROR_POLICY ignore_error
+#  endif
+#  ifndef BOOST_MATH_EVALUATION_ERROR_POLICY
+#     define BOOST_MATH_EVALUATION_ERROR_POLICY ignore_error
+#  endif
+#  ifndef BOOST_MATH_ROUNDING_ERROR_POLICY
+#     define BOOST_MATH_ROUNDING_ERROR_POLICY ignore_error
+#  endif
+#endif
+
+//
 // Special cases for exceptions disabled first:
 //
 #ifdef BOOST_MATH_NO_EXCEPTIONS

From 32b909d35a9d09b9375e27bff477c60a82752009 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:37:19 -0400
Subject: [PATCH 055/399] Adjust CML for sycl

---
 CMakeLists.txt      |  7 +++++++
 test/CMakeLists.txt | 32 +++++++++++++++++++++++++++++++-
 test/sycl_jamfile   | 16 ++++++++++++++++
 3 files changed, 54 insertions(+), 1 deletion(-)
 create mode 100644 test/sycl_jamfile

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 7e7790271c..0e3a845974 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -41,6 +41,12 @@ else()
 
 endif()
 
+if(BUILD_TESTING AND EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/test/CMakeLists.txt")
+
+  add_subdirectory(test)
+
+endif()
+
 # Only enable tests when we're the root project
 if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
 
@@ -49,4 +55,5 @@ if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
   
   include(GNUInstallDirs)
   install(DIRECTORY "include/" DESTINATION "${CMAKE_INSTALL_INCLUDEDIR}")
+
 endif()
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index e63471c891..4eba56701b 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -2,4 +2,34 @@
 # Distributed under the Boost Software License, Version 1.0.
 # https://www.boost.org/LICENSE_1_0.txt
 
-add_subdirectory(compile_test)
+include(BoostTestJamfile OPTIONAL RESULT_VARIABLE HAVE_BOOST_TEST)
+
+if(HAVE_BOOST_TEST)
+
+    if (BOOST_MATH_ENABLE_CUDA)
+
+        message(STATUS "Building boost.cuda_math with CUDA")
+
+        enable_language(CUDA)
+        set(CMAKE_CUDA_EXTENSIONS OFF)
+
+        enable_testing()
+
+        boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::cuda_math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework )
+    elseif (BOOST_MATH_ENABLE_SYCL)
+
+        message(STATUS "Building boost.cuda_math with SYCL")
+
+        set(CMAKE_CXX_COMPILER "icpx")
+        set(CMAKE_C_COMPILER "icx")
+
+        enable_testing()
+
+        boost_test_jamfile(FILE sycl_jamfile LINK_LIBRARIES Boost::cuda_math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework sycl COMPILE_OPTIONS -fsycl )
+    else()
+
+        add_subdirectory(compile_test)
+
+    endif()
+
+endif()
\ No newline at end of file
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
new file mode 100644
index 0000000000..679bae0dcf
--- /dev/null
+++ b/test/sycl_jamfile
@@ -0,0 +1,16 @@
+# Copyright 2024 Matt Borland
+# Distributed under the Boost Software License, Version 1.0.
+# https://www.boost.org/LICENSE_1_0.txt
+
+import testing ;
+import ../../config/checks/config : requires ;
+
+project : requirements
+    [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
+    ;
+
+# Distributions
+run test_arcsine.cpp ;
+
+# Special Functions
+run test_beta_simple.cpp ;

From 2148185c602439a54397b4be730d2cceb96a23ab Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:38:15 -0400
Subject: [PATCH 056/399] Add sycl compatible simple test

---
 test/test_beta_simple.cpp | 38 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 38 insertions(+)
 create mode 100644 test/test_beta_simple.cpp

diff --git a/test/test_beta_simple.cpp b/test/test_beta_simple.cpp
new file mode 100644
index 0000000000..436b14ab46
--- /dev/null
+++ b/test/test_beta_simple.cpp
@@ -0,0 +1,38 @@
+// Copyright John Maddock 2006.
+// Copyright Paul A. Bristow 2007, 2009
+// Copyright Matt Borland 2024
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <boost/math/concepts/real_concept.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include "math_unit_test.hpp"
+
+template <class T>
+void test_spots(T)
+{
+    //
+    // Basic sanity checks, tolerance is 20 epsilon expressed as a percentage:
+    //
+    T tolerance = 20;
+    T small = boost::math::tools::epsilon<T>() / 1024;
+    CHECK_ULP_CLOSE(::boost::math::beta(static_cast<T>(1), static_cast<T>(1)), static_cast<T>(1), tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(static_cast<T>(1), static_cast<T>(4)), static_cast<T>(0.25), tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(static_cast<T>(4), static_cast<T>(1)), static_cast<T>(0.25), tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(small, static_cast<T>(4)), 1/small, tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(static_cast<T>(4), small), 1/small, tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(small, static_cast<T>(4)), 1/small, tolerance);
+    CHECK_ULP_CLOSE(::boost::math::beta(static_cast<T>(4), static_cast<T>(20)), static_cast<T>(0.00002823263692828910220214568040654997176736L), tolerance);
+}
+
+int main()
+{
+    test_spots(0.0F);
+    test_spots(0.0);
+
+    return boost::math::test::report_errors();
+}

From b293df07a93448ad1490cde50fbd681818b63800 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:40:45 -0400
Subject: [PATCH 057/399] Add sycl cmake testing

---
 .github/workflows/ci.yml | 65 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 65 insertions(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index cdd5404fcf..9ea46c203f 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -546,3 +546,68 @@ jobs:
       - name: Test
         run: ../../../b2 toolset=$TOOLSET ${{ matrix.suite }} define=CI_SUPPRESS_KNOWN_ISSUES define=SLOW_COMPILER define=BOOST_MATH_STANDALONE define=BOOST_MP_STANDALONE
         working-directory: ../boost-root/libs/math/test
+  sycl-cmake-test:
+    strategy:
+      fail-fast: false
+
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Intel Apt repository
+        timeout-minutes: 1
+        run: |
+          wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+          sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+          rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+          echo "deb https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
+          sudo apt-get update
+
+      - name: Install Intel oneAPI compilers
+        timeout-minutes: 5
+        run: sudo apt-get install intel-oneapi-compiler-fortran intel-oneapi-compiler-dpcpp-cpp
+
+      - name: Setup Intel oneAPI environment
+        run: |
+          source /opt/intel/oneapi/setvars.sh
+          printenv >> $GITHUB_ENV
+
+      - name: checkout project code
+        uses: actions/checkout@v4
+
+      - name: Install Packages
+        run: |
+          sudo apt-get install -y cmake make
+
+      - name: Setup Boost
+        run: |
+          echo GITHUB_REPOSITORY: $GITHUB_REPOSITORY
+          LIBRARY=${GITHUB_REPOSITORY#*/}
+          echo LIBRARY: $LIBRARY
+          echo "LIBRARY=$LIBRARY" >> $GITHUB_ENV
+          echo GITHUB_BASE_REF: $GITHUB_BASE_REF
+          echo GITHUB_REF: $GITHUB_REF
+          REF=${GITHUB_BASE_REF:-$GITHUB_REF}
+          REF=${REF#refs/heads/}
+          echo REF: $REF
+          BOOST_BRANCH=develop && [ "$REF" == "master" ] && BOOST_BRANCH=master || true
+          echo BOOST_BRANCH: $BOOST_BRANCH
+          cd ..
+          git clone -b $BOOST_BRANCH --depth 1 https://github.com/boostorg/boost.git boost-root
+          cd boost-root
+          mkdir -p libs/$LIBRARY
+          cp -r $GITHUB_WORKSPACE/* libs/$LIBRARY
+          git submodule update --init tools/boostdep
+          python3 tools/boostdep/depinst/depinst.py --git_args "--jobs 3" $LIBRARY
+      - name: Configure
+        run: |
+          cd ../boost-root
+          mkdir __build__ && cd __build__
+          cmake -DBOOST_INCLUDE_LIBRARIES=$LIBRARY -DBUILD_TESTING=ON -DBOOST_MATH_ENABLE_SYCL=ON ..
+      - name: Build tests
+        run: |
+          cd ../boost-root/__build__
+          cmake --build . --target tests
+      - name: Run tests
+        run: |
+          cd ../boost-root/__build__
+          ctest --output-on-failure --no-tests=error

From fcf7ba8f3bf74196242e15997884f127077e23df Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:49:20 -0400
Subject: [PATCH 058/399] Small CML fixes

---
 CMakeLists.txt      | 4 +---
 test/CMakeLists.txt | 4 ++--
 2 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 0e3a845974..d05c44a9e8 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -45,10 +45,8 @@ if(BUILD_TESTING AND EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/test/CMakeLists.txt")
 
   add_subdirectory(test)
 
-endif()
-
 # Only enable tests when we're the root project
-if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
+elseif(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
 
   include(CTest)
   add_subdirectory(test)
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 4eba56701b..78d8fd4c34 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -15,7 +15,7 @@ if(HAVE_BOOST_TEST)
 
         enable_testing()
 
-        boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::cuda_math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework )
+        boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework )
     elseif (BOOST_MATH_ENABLE_SYCL)
 
         message(STATUS "Building boost.cuda_math with SYCL")
@@ -25,7 +25,7 @@ if(HAVE_BOOST_TEST)
 
         enable_testing()
 
-        boost_test_jamfile(FILE sycl_jamfile LINK_LIBRARIES Boost::cuda_math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework sycl COMPILE_OPTIONS -fsycl )
+        boost_test_jamfile(FILE sycl_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework sycl COMPILE_OPTIONS -fsycl )
     else()
 
         add_subdirectory(compile_test)

From dbee257edc62428d5b7580764aec61892df6026e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 13:57:06 -0400
Subject: [PATCH 059/399] Port fixes to run SYCL on test_arcsine

---
 test/test_arcsine.cpp | 119 ++++++++++++++++++++++--------------------
 1 file changed, 63 insertions(+), 56 deletions(-)

diff --git a/test/test_arcsine.cpp b/test/test_arcsine.cpp
index 0c2d847a96..d1ac803080 100644
--- a/test/test_arcsine.cpp
+++ b/test/test_arcsine.cpp
@@ -10,7 +10,9 @@
 
 // Tests for the arcsine Distribution.
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp> // Must be 1st include, and include_directory /libs/math/src/tr1/ is needed.
+#endif
 
 #ifdef _MSC_VER
 #  pragma warning(disable: 4127) // Conditional expression is constant.
@@ -20,7 +22,6 @@
 
 #include <boost/math/concepts/real_concept.hpp> // for real_concept.
 using ::boost::math::concepts::real_concept;
-#include <boost/math/tools/test.hpp> // for real_concept.
 
 #include <boost/math/distributions/arcsine.hpp> // for arcsine_distribution.
 using boost::math::arcsine_distribution;
@@ -42,6 +43,10 @@ using std::endl;
 #include <limits>
 using std::numeric_limits;
 
+#if defined(BOOST_CHECK_THROW) && defined(BOOST_MATH_NO_EXCEPTIONS)
+#  undef BOOST_CHECK_THROW
+#  define BOOST_CHECK_THROW(x, y)
+#endif
 
 template <class RealType>
 void test_ignore_policy(RealType)
@@ -272,7 +277,7 @@ void test_spots(RealType)
     BOOST_CHECK_EQUAL(kurtosis_excess(arcsine_01), -1.5); // 3/2
     BOOST_CHECK_EQUAL(support(arcsine_01).first, 0); //
     BOOST_CHECK_EQUAL(range(arcsine_01).first, 0); //
-    BOOST_MATH_CHECK_THROW(mode(arcsine_01), std::domain_error); //  Two modes at x_min and x_max, so throw instead.
+    BOOST_CHECK_THROW(mode(arcsine_01), std::domain_error); //  Two modes at x_min and x_max, so throw instead.
 
     // PDF
     // pdf of x = 1/4 is same as reflected value at x = 3/4.
@@ -290,11 +295,13 @@ void test_spots(RealType)
     BOOST_CHECK_CLOSE_FRACTION(pdf(arcsine_01, 0.999999), static_cast<RealType>(318.31004533885312973989414360099118178698415543136L), 100000 * tolerance);// Even less accurate.
 
     // Extreme x.
+    #ifndef BOOST_MATH_ENABLE_SYCL
     if (std::numeric_limits<RealType>::has_infinity)
     { //
       BOOST_CHECK_EQUAL(pdf(arcsine_01, 0), informax<RealType>()); //
       BOOST_CHECK_EQUAL(pdf(arcsine_01, 1), informax<RealType>()); //
     }
+    #endif
 
     BOOST_CHECK_CLOSE_FRACTION(pdf(arcsine_01, tolerance),
       1 /(sqrt(tolerance) * boost::math::constants::pi<RealType>()), 2 * tolerance); //
@@ -439,56 +446,56 @@ void test_spots(RealType)
     BOOST_CHECK_CLOSE_FRACTION(quantile(complement(as_m2m1, static_cast<RealType>(0.85643370687129372924905811522494428117838480010259L))), -static_cast<RealType>(1.95L), 4 * tolerance);
 
     // Tests that should throw:
-    BOOST_MATH_CHECK_THROW(mode(arcsine_distribution<RealType>(static_cast<RealType>(0), static_cast<RealType>(1))), std::domain_error);
+    BOOST_CHECK_THROW(mode(arcsine_distribution<RealType>(static_cast<RealType>(0), static_cast<RealType>(1))), std::domain_error);
     // mode is undefined, and must throw domain_error!
 
 
-    BOOST_MATH_CHECK_THROW( // For various bad arguments.
+    BOOST_CHECK_THROW( // For various bad arguments.
       pdf(
       arcsine_distribution<RealType>(static_cast<RealType>(+1), static_cast<RealType>(-1)), // min_x > max_x
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       pdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(0)), // bad constructor parameters.
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       pdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(-1)), // bad constructor parameters.
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       pdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(1)), // equal constructor parameters.
       static_cast<RealType>(-1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       pdf(
       arcsine_distribution<RealType>(static_cast<RealType>(0), static_cast<RealType>(1)), // bad x > 1.
       static_cast<RealType>(999)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW( // For various bad arguments.
+    BOOST_CHECK_THROW( // For various bad arguments.
       logpdf(
       arcsine_distribution<RealType>(static_cast<RealType>(+1), static_cast<RealType>(-1)), // min_x > max_x
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       logpdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(0)), // bad constructor parameters.
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       logpdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(-1)), // bad constructor parameters.
       static_cast<RealType>(1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       logpdf(
       arcsine_distribution<RealType>(static_cast<RealType>(1), static_cast<RealType>(1)), // equal constructor parameters.
       static_cast<RealType>(-1)), std::domain_error);
 
-    BOOST_MATH_CHECK_THROW(
+    BOOST_CHECK_THROW(
       logpdf(
       arcsine_distribution<RealType>(static_cast<RealType>(0), static_cast<RealType>(1)), // bad x > 1.
       static_cast<RealType>(999)), std::domain_error);
@@ -496,26 +503,26 @@ void test_spots(RealType)
     // Checks on things that are errors.
 
     // Construction with 'bad' parameters.
-    BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(+1, -1), std::domain_error); // max < min.
-    BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(+1, 0), std::domain_error);  // max < min.
+    BOOST_CHECK_THROW(arcsine_distribution<RealType>(+1, -1), std::domain_error); // max < min.
+    BOOST_CHECK_THROW(arcsine_distribution<RealType>(+1, 0), std::domain_error);  // max < min.
 
     arcsine_distribution<> dist;
-    BOOST_MATH_CHECK_THROW(pdf(dist, -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(logpdf(dist, -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(cdf(dist, -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(cdf(complement(dist, -1)), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(dist, -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(complement(dist, -1)), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(dist, -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(complement(dist, -1)), std::domain_error);
+    BOOST_CHECK_THROW(pdf(dist, -1), std::domain_error);
+    BOOST_CHECK_THROW(logpdf(dist, -1), std::domain_error);
+    BOOST_CHECK_THROW(cdf(dist, -1), std::domain_error);
+    BOOST_CHECK_THROW(cdf(complement(dist, -1)), std::domain_error);
+    BOOST_CHECK_THROW(quantile(dist, -1), std::domain_error);
+    BOOST_CHECK_THROW(quantile(complement(dist, -1)), std::domain_error);
+    BOOST_CHECK_THROW(quantile(dist, -1), std::domain_error);
+    BOOST_CHECK_THROW(quantile(complement(dist, -1)), std::domain_error);
 
     // Various combinations of bad constructor and member function parameters.
-    BOOST_MATH_CHECK_THROW(pdf(boost::math::arcsine_distribution<RealType>(0, 1), -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(pdf(boost::math::arcsine_distribution<RealType>(-1, 1), +2), std::domain_error);
-    BOOST_MATH_CHECK_THROW(logpdf(boost::math::arcsine_distribution<RealType>(0, 1), -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(logpdf(boost::math::arcsine_distribution<RealType>(-1, 1), +2), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(boost::math::arcsine_distribution<RealType>(1, 1), -1), std::domain_error);
-    BOOST_MATH_CHECK_THROW(quantile(boost::math::arcsine_distribution<RealType>(1, 1), 2), std::domain_error);
+    BOOST_CHECK_THROW(pdf(boost::math::arcsine_distribution<RealType>(0, 1), -1), std::domain_error);
+    BOOST_CHECK_THROW(pdf(boost::math::arcsine_distribution<RealType>(-1, 1), +2), std::domain_error);
+    BOOST_CHECK_THROW(logpdf(boost::math::arcsine_distribution<RealType>(0, 1), -1), std::domain_error);
+    BOOST_CHECK_THROW(logpdf(boost::math::arcsine_distribution<RealType>(-1, 1), +2), std::domain_error);
+    BOOST_CHECK_THROW(quantile(boost::math::arcsine_distribution<RealType>(1, 1), -1), std::domain_error);
+    BOOST_CHECK_THROW(quantile(boost::math::arcsine_distribution<RealType>(1, 1), 2), std::domain_error);
 
     // No longer allow any parameter to be NaN or inf, so all these tests should throw.
     if (std::numeric_limits<RealType>::has_quiet_NaN)
@@ -523,23 +530,23 @@ void test_spots(RealType)
       // Attempt to construct from non-finite parameters should throw.
       RealType nan = std::numeric_limits<RealType>::quiet_NaN();
 #ifndef BOOST_NO_EXCEPTIONS
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(nan), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(1, nan), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(nan, 1), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(nan), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(1, nan), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(nan, 1), std::domain_error);
 #else
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(nan), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(1, nan), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(nan, 1), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(nan), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(1, nan), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(nan, 1), std::domain_error);
 #endif
 
       arcsine_distribution<RealType> w(RealType(-1), RealType(+1));
       // NaN parameters to member functions should throw.
-      BOOST_MATH_CHECK_THROW(pdf(w, +nan), std::domain_error); // x = NaN
-      BOOST_MATH_CHECK_THROW(logpdf(w, +nan), std::domain_error); // x = NaN
-      BOOST_MATH_CHECK_THROW(cdf(w, +nan), std::domain_error); // x = NaN
-      BOOST_MATH_CHECK_THROW(cdf(complement(w, +nan)), std::domain_error); // x = + nan
-      BOOST_MATH_CHECK_THROW(quantile(w, +nan), std::domain_error); // p = + nan
-      BOOST_MATH_CHECK_THROW(quantile(complement(w, +nan)), std::domain_error); // p = + nan
+      BOOST_CHECK_THROW(pdf(w, +nan), std::domain_error); // x = NaN
+      BOOST_CHECK_THROW(logpdf(w, +nan), std::domain_error); // x = NaN
+      BOOST_CHECK_THROW(cdf(w, +nan), std::domain_error); // x = NaN
+      BOOST_CHECK_THROW(cdf(complement(w, +nan)), std::domain_error); // x = + nan
+      BOOST_CHECK_THROW(quantile(w, +nan), std::domain_error); // p = + nan
+      BOOST_CHECK_THROW(quantile(complement(w, +nan)), std::domain_error); // p = + nan
     } // has_quiet_NaN
 
     if (std::numeric_limits<RealType>::has_infinity)
@@ -547,27 +554,27 @@ void test_spots(RealType)
       // Attempt to construct from non-finite should throw.
       RealType inf = std::numeric_limits<RealType>::infinity();
 #ifndef BOOST_NO_EXCEPTIONS
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(inf), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(1, inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(1, inf), std::domain_error);
 #else
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(inf), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(1, inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(1, inf), std::domain_error);
 #endif
       // Infinite parameters to member functions should throw.
       arcsine_distribution<RealType> w(RealType(0), RealType(1));
 #ifndef BOOST_NO_EXCEPTIONS
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(inf), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType> w(1, inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType> w(1, inf), std::domain_error);
 #else
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(inf), std::domain_error);
-      BOOST_MATH_CHECK_THROW(arcsine_distribution<RealType>(1, inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(inf), std::domain_error);
+      BOOST_CHECK_THROW(arcsine_distribution<RealType>(1, inf), std::domain_error);
 #endif
-      BOOST_MATH_CHECK_THROW(pdf(w, +inf), std::domain_error); // x = inf
-      BOOST_MATH_CHECK_THROW(logpdf(w, +inf), std::domain_error); // x = inf
-      BOOST_MATH_CHECK_THROW(cdf(w, +inf), std::domain_error); // x = inf
-      BOOST_MATH_CHECK_THROW(cdf(complement(w, +inf)), std::domain_error); // x = + inf
-      BOOST_MATH_CHECK_THROW(quantile(w, +inf), std::domain_error); // p = + inf
-      BOOST_MATH_CHECK_THROW(quantile(complement(w, +inf)), std::domain_error); // p = + inf
+      BOOST_CHECK_THROW(pdf(w, +inf), std::domain_error); // x = inf
+      BOOST_CHECK_THROW(logpdf(w, +inf), std::domain_error); // x = inf
+      BOOST_CHECK_THROW(cdf(w, +inf), std::domain_error); // x = inf
+      BOOST_CHECK_THROW(cdf(complement(w, +inf)), std::domain_error); // x = + inf
+      BOOST_CHECK_THROW(quantile(w, +inf), std::domain_error); // p = + inf
+      BOOST_CHECK_THROW(quantile(complement(w, +inf)), std::domain_error); // p = + inf
     } // has_infinity
 
     // Error handling checks:
@@ -601,7 +608,7 @@ void test_spots(RealType)
     BOOST_CHECK_EQUAL(kurtosis_excess(as), -1.5); // 3/2
     BOOST_CHECK_EQUAL(support(as).first, 0); //
     BOOST_CHECK_EQUAL(range(as).first, 0); //
-    BOOST_MATH_CHECK_THROW(mode(as), std::domain_error); //  Two modes at x_min and x_max, so throw instead.
+    BOOST_CHECK_THROW(mode(as), std::domain_error); //  Two modes at x_min and x_max, so throw instead.
 
     // (Parameter value, arbitrarily zero, only communicates the floating point type).
     test_spots(0.0F); // Test float.

From 9ed0f2ba52da0eb4a54b418774c7710dad71ceeb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 14:13:02 -0400
Subject: [PATCH 060/399] More SYCL workarounds

---
 test/test_out_of_range.hpp | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/test_out_of_range.hpp b/test/test_out_of_range.hpp
index bed4e48a0f..8b7e723c07 100644
--- a/test/test_out_of_range.hpp
+++ b/test/test_out_of_range.hpp
@@ -8,6 +8,7 @@
 #ifndef BOOST_MATH_TEST_OUT_OF_RANGE_HPP
 #define BOOST_MATH_TEST_OUT_OF_RANGE_HPP
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/next.hpp>
 #include <boost/test/unit_test.hpp>
 
@@ -30,6 +31,11 @@ but does *not* check finite but out-of-range parameters to the constructor
 because these are specific to each distribution.
 */
 
+#if defined(BOOST_CHECK_THROW) && defined(BOOST_MATH_NO_EXCEPTIONS)
+#  undef BOOST_CHECK_THROW
+#  define BOOST_CHECK_THROW(x, y)
+#endif
+
 #ifdef _MSC_VER
 #pragma warning(push)
 #pragma warning(disable:4127)

From b35b4de6ab56353ce9829eecbd355a119f5745c3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 14:16:13 -0400
Subject: [PATCH 061/399] Add cuda files

---
 test/cuda_jamfile                |  31 ++++++++
 test/test_arcsine_cdf_double.cu  | 109 +++++++++++++++++++++++++
 test/test_arcsine_cdf_float.cu   | 109 +++++++++++++++++++++++++
 test/test_arcsine_pdf_double.cu  | 109 +++++++++++++++++++++++++
 test/test_arcsine_pdf_float.cu   | 109 +++++++++++++++++++++++++
 test/test_arcsine_quan_double.cu | 109 +++++++++++++++++++++++++
 test/test_arcsine_quan_float.cu  | 109 +++++++++++++++++++++++++
 test/test_beta_double.cu         | 132 +++++++++++++++++++++++++++++++
 test/test_beta_float.cu          | 130 ++++++++++++++++++++++++++++++
 9 files changed, 947 insertions(+)
 create mode 100644 test/cuda_jamfile
 create mode 100644 test/test_arcsine_cdf_double.cu
 create mode 100644 test/test_arcsine_cdf_float.cu
 create mode 100644 test/test_arcsine_pdf_double.cu
 create mode 100644 test/test_arcsine_pdf_float.cu
 create mode 100644 test/test_arcsine_quan_double.cu
 create mode 100644 test/test_arcsine_quan_float.cu
 create mode 100644 test/test_beta_double.cu
 create mode 100644 test/test_beta_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
new file mode 100644
index 0000000000..f4740a2104
--- /dev/null
+++ b/test/cuda_jamfile
@@ -0,0 +1,31 @@
+# Copyright 2024 Matt Borland
+# Distributed under the Boost Software License, Version 1.0.
+# https://www.boost.org/LICENSE_1_0.txt
+
+import testing ;
+import ../../config/checks/config : requires ;
+
+project : requirements
+    [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
+    ;
+
+# Autodiff Tests
+run test_autodiff_1.cpp ;
+
+# Tools Tests
+run test_polynomial.cpp ;
+
+# Distributions
+run test_arcsine.cpp ;
+run test_arcsine_cdf_double.cu ;
+run test_arcsine_cdf_float.cu ;
+run test_arcsine_pdf_double.cu ;
+run test_arcsine_pdf_float.cu ;
+run test_arcsine_quan_double.cu ;
+run test_arcsine_quan_float.cu ;
+run test_binomial.cpp ;
+
+# Special Functions
+# run test_beta_simple.cpp ;
+run test_beta_double.cu ;
+run test_beta_float.cu ;
\ No newline at end of file
diff --git a/test/test_arcsine_cdf_double.cu b/test/test_arcsine_cdf_double.cu
new file mode 100644
index 0000000000..d6f6f7b357
--- /dev/null
+++ b/test/test_arcsine_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_arcsine_cdf_float.cu b/test/test_arcsine_cdf_float.cu
new file mode 100644
index 0000000000..148b1dffb0
--- /dev/null
+++ b/test/test_arcsine_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_arcsine_pdf_double.cu b/test/test_arcsine_pdf_double.cu
new file mode 100644
index 0000000000..7a73bb34eb
--- /dev/null
+++ b/test/test_arcsine_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_arcsine_pdf_float.cu b/test/test_arcsine_pdf_float.cu
new file mode 100644
index 0000000000..54a11253c5
--- /dev/null
+++ b/test/test_arcsine_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_arcsine_quan_double.cu b/test/test_arcsine_quan_double.cu
new file mode 100644
index 0000000000..31f6eac8a1
--- /dev/null
+++ b/test/test_arcsine_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_arcsine_quan_float.cu b/test/test_arcsine_quan_float.cu
new file mode 100644
index 0000000000..6decb347b0
--- /dev/null
+++ b/test/test_arcsine_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::arcsine_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_beta_double.cu b/test/test_beta_double.cu
new file mode 100644
index 0000000000..cd58601584
--- /dev/null
+++ b/test/test_beta_double.cu
@@ -0,0 +1,132 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type * in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::beta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_beta_float.cu b/test/test_beta_float.cu
new file mode 100644
index 0000000000..c4c078f373
--- /dev/null
+++ b/test/test_beta_float.cu
@@ -0,0 +1,130 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type * in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::beta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+

From 19d0d5bc58fe9cdb5c3cdca50c17ca63714d49df Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 14:25:00 -0400
Subject: [PATCH 062/399] Add compile only cmake testing

---
 .github/workflows/ci.yml | 58 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 58 insertions(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 9ea46c203f..4af5da980a 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -611,3 +611,61 @@ jobs:
         run: |
           cd ../boost-root/__build__
           ctest --output-on-failure --no-tests=error
+  cuda-cmake-test:
+    strategy:
+      fail-fast: false
+
+    runs-on: ubuntu-22.04
+
+    steps:
+      - uses: Jimver/cuda-toolkit@v0.2.16
+        id: cuda-toolkit
+        with:
+          cuda: '12.5.0'
+          method: 'network'
+          sub-packages: '["nvcc"]'
+
+      - name: Output CUDA information
+        run: |
+          echo "Installed cuda version is: ${{steps.cuda-toolkit.outputs.cuda}}"+
+          echo "Cuda install location: ${{steps.cuda-toolkit.outputs.CUDA_PATH}}"
+          nvcc -V
+      - uses: actions/checkout@v4
+
+      - name: Install Packages
+        run: |
+          sudo apt-get install -y cmake make
+      - name: Setup Boost
+        run: |
+          echo GITHUB_REPOSITORY: $GITHUB_REPOSITORY
+          LIBRARY=${GITHUB_REPOSITORY#*/}
+          echo LIBRARY: $LIBRARY
+          echo "LIBRARY=$LIBRARY" >> $GITHUB_ENV
+          echo GITHUB_BASE_REF: $GITHUB_BASE_REF
+          echo GITHUB_REF: $GITHUB_REF
+          REF=${GITHUB_BASE_REF:-$GITHUB_REF}
+          REF=${REF#refs/heads/}
+          echo REF: $REF
+          BOOST_BRANCH=develop && [ "$REF" == "master" ] && BOOST_BRANCH=master || true
+          echo BOOST_BRANCH: $BOOST_BRANCH
+          cd ..
+          git clone -b $BOOST_BRANCH --depth 1 https://github.com/boostorg/boost.git boost-root
+          cd boost-root
+          mkdir -p libs/$LIBRARY
+          cp -r $GITHUB_WORKSPACE/* libs/$LIBRARY
+          git submodule update --init tools/boostdep
+          python3 tools/boostdep/depinst/depinst.py --git_args "--jobs 3" $LIBRARY
+      - name: Configure
+        run: |
+          cd ../boost-root
+          mkdir __build__ && cd __build__
+          cmake -DBOOST_INCLUDE_LIBRARIES=$LIBRARY -DBUILD_TESTING=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc -DBOOST_MATH_ENABLE_CUDA=1 -DCMAKE_CUDA_ARCHITECTURES=70 -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.5 ..
+      - name: Build tests
+        run: |
+          cd ../boost-root/__build__
+          cmake --build . --target tests
+      # Will leave this commented out for now. GHA does not install graphics cards by default
+      #- name: Run tests
+      #  run: |
+      #    cd ../boost-root/__build__
+      #    ctest --output-on-failure --no-tests=error

From d60d5d6e078528ae027f499937e3ddb62d9ce107 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 14:31:28 -0400
Subject: [PATCH 063/399] Add test helper headers

---
 test/cuda_managed_ptr.hpp | 139 ++++++++++++++++++++++++++++++++++++++
 test/stopwatch.hpp        |  39 +++++++++++
 2 files changed, 178 insertions(+)
 create mode 100644 test/cuda_managed_ptr.hpp
 create mode 100644 test/stopwatch.hpp

diff --git a/test/cuda_managed_ptr.hpp b/test/cuda_managed_ptr.hpp
new file mode 100644
index 0000000000..59cabd3f7d
--- /dev/null
+++ b/test/cuda_managed_ptr.hpp
@@ -0,0 +1,139 @@
+
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_MATH_CUDA_MANAGED_PTR_HPP
+#define BOOST_MATH_CUDA_MANAGED_PTR_HPP
+
+#ifdef _MSC_VER
+#pragma once
+#endif
+
+#include <cuda_runtime.h>
+
+class managed_holder_base
+{
+protected:
+   static int count;
+   managed_holder_base() { ++count; }
+   ~managed_holder_base()
+   {
+      if(0 == --count)
+         cudaDeviceSynchronize();
+   }
+};
+
+int managed_holder_base::count = 0;
+
+//
+// Reset the device and exit:
+// cudaDeviceReset causes the driver to clean up all state. While
+// not mandatory in normal operation, it is good practice.  It is also
+// needed to ensure correct operation when the application is being
+// profiled. Calling cudaDeviceReset causes all profile data to be
+// flushed before the application exits.
+//
+// We have a global instance of this class, plus instances for each
+// managed pointer.  Last one out the door switches the lights off.
+//
+class cudaResetter
+{
+   static int count;
+public:
+   cudaResetter() { ++count;  }
+   ~cudaResetter()
+   {
+      if(--count == 0)
+      {
+         cudaError_t err = cudaDeviceReset();
+         if(err != cudaSuccess)
+         {
+            std::cerr << "Failed to deinitialize the device! error=" << cudaGetErrorString(err) << std::endl;
+         }
+      }
+   }
+};
+
+int cudaResetter::count = 0;
+
+cudaResetter global_resetter;
+
+template <class T>
+class cuda_managed_ptr
+{
+   T* data;
+   static const cudaResetter resetter;
+   cuda_managed_ptr(const cuda_managed_ptr&) = delete;
+   cuda_managed_ptr& operator=(cuda_managed_ptr const&) = delete;
+   void free()
+   {
+      if(data)
+      {
+         cudaDeviceSynchronize();
+         cudaError_t err = cudaFree(data);
+         if(err != cudaSuccess)
+         {
+            std::cerr << "Failed to deinitialize the device! error=" << cudaGetErrorString(err) << std::endl;
+         }
+      }
+   }
+public:
+   cuda_managed_ptr() : data(0) {}
+   cuda_managed_ptr(std::size_t n)
+   {
+      cudaError_t err = cudaSuccess;
+      void *ptr;
+      err = cudaMallocManaged(&ptr, n * sizeof(T));
+      if(err != cudaSuccess)
+         throw std::runtime_error(cudaGetErrorString(err));
+      cudaDeviceSynchronize();
+      data = static_cast<T*>(ptr);
+   }
+   cuda_managed_ptr(cuda_managed_ptr&& o)
+   {
+      data = o.data;
+      o.data = 0;
+   }
+   cuda_managed_ptr& operator=(cuda_managed_ptr&& o)
+   {
+      free();
+      data = o.data;
+      o.data = 0;
+      return *this;
+   }
+   ~cuda_managed_ptr()
+   {
+      free();
+   }
+
+   class managed_holder : managed_holder_base
+   {
+      T* pdata;
+   public:
+      managed_holder(T* p) : managed_holder_base(), pdata(p) {}
+      managed_holder(const managed_holder& o) : managed_holder_base(), pdata(o.pdata) {}
+      operator T* () { return pdata; }
+      T& operator[] (std::size_t n) { return pdata[n]; }
+   };
+   class const_managed_holder : managed_holder_base
+   {
+      const T* pdata;
+   public:
+      const_managed_holder(T* p) : managed_holder_base(), pdata(p) {}
+      const_managed_holder(const managed_holder& o) : managed_holder_base(), pdata(o.pdata) {}
+      operator const T* () { return pdata; }
+      const T& operator[] (std::size_t n) { return pdata[n]; }
+   };
+
+   managed_holder get() { return managed_holder(data); }
+   const_managed_holder get()const { return data; }
+   T& operator[](std::size_t n) { return data[n]; }
+   const T& operator[](std::size_t n)const { return data[n]; }
+};
+
+template <class T>
+cudaResetter const cuda_managed_ptr<T>::resetter;
+
+#endif
\ No newline at end of file
diff --git a/test/stopwatch.hpp b/test/stopwatch.hpp
new file mode 100644
index 0000000000..5fe84c3c33
--- /dev/null
+++ b/test/stopwatch.hpp
@@ -0,0 +1,39 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_MATH_CUDA_STOPWATCH_HPP
+#define BOOST_MATH_CUDA_STOPWATCH_HPP
+
+#ifdef _MSC_VER
+#pragma once
+#endif
+
+#include <chrono>
+
+template <class Clock>
+struct stopwatch
+{
+    typedef typename Clock::duration duration;
+    stopwatch()
+    {
+        m_start = Clock::now();
+    }
+    double elapsed()
+    {
+        duration t = Clock::now() - m_start;
+        return std::chrono::duration_cast<std::chrono::duration<double>>(t).count();
+    }
+    void reset()
+    {
+        m_start = Clock::now();
+    }
+
+private:
+    typename Clock::time_point m_start;
+};
+
+typedef stopwatch<std::chrono::high_resolution_clock> watch;
+
+#endif
\ No newline at end of file

From 3bfd85c2cdc15c2188c86823bc4ddd879da7c1e6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 15:29:25 -0400
Subject: [PATCH 064/399] Fix line endings

---
 test/cuda_managed_ptr.hpp | 2 +-
 test/stopwatch.hpp        | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/cuda_managed_ptr.hpp b/test/cuda_managed_ptr.hpp
index 59cabd3f7d..3d0f3e800d 100644
--- a/test/cuda_managed_ptr.hpp
+++ b/test/cuda_managed_ptr.hpp
@@ -136,4 +136,4 @@ class cuda_managed_ptr
 template <class T>
 cudaResetter const cuda_managed_ptr<T>::resetter;
 
-#endif
\ No newline at end of file
+#endif
diff --git a/test/stopwatch.hpp b/test/stopwatch.hpp
index 5fe84c3c33..9f3c60de80 100644
--- a/test/stopwatch.hpp
+++ b/test/stopwatch.hpp
@@ -36,4 +36,4 @@ struct stopwatch
 
 typedef stopwatch<std::chrono::high_resolution_clock> watch;
 
-#endif
\ No newline at end of file
+#endif

From f17946b74bc5b696cf747cb63a1d999c55c2e51a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 15:36:28 -0400
Subject: [PATCH 065/399] Remove duplicate test from compile only battery

---
 test/cuda_jamfile | 1 -
 1 file changed, 1 deletion(-)

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index f4740a2104..67a779f393 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -16,7 +16,6 @@ run test_autodiff_1.cpp ;
 run test_polynomial.cpp ;
 
 # Distributions
-run test_arcsine.cpp ;
 run test_arcsine_cdf_double.cu ;
 run test_arcsine_cdf_float.cu ;
 run test_arcsine_pdf_double.cu ;

From a5ed6bae8daf6b28106c8833ee78fc6e46f78a0d Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Wed, 24 Jul 2024 09:44:18 +0900
Subject: [PATCH 066/399] Fix mapairy test

---
 test/test_mapairy.cpp | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index cfa3a712de..fac7fd01c6 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -774,6 +774,12 @@ void do_test_mapairy_locscale_param() {
     );
     BOOST_CHECK_CLOSE(mode(dist_0_invcbrt18), BOOST_MATH_BIG_CONSTANT(RealType, N, -0.4432284977460014720866292801600737435), tolerance);
 
+    BOOST_CHECK_EQUAL(mean(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(mean(dist_1_3), static_cast<RealType>(1));
+    BOOST_CHECK_EQUAL(mean(dist_0_invcbrt18), static_cast<RealType>(0));
+
+    BOOST_CHECK((boost::math::isinf)(variance(dist_0_1)));
+
     BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.06251243013238748252181151646220197947016365256337e-1), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.97516171847191855609649452292217911972760948598791e-1) / 3, tolerance);
     BOOST_CHECK_CLOSE(pdf(dist_0_invcbrt18, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.29264884227495575949271548513687010027396013858107e-2), tolerance);

From a2d109be27ab0a1e0279bf56a998cdbd0d2f4016 Mon Sep 17 00:00:00 2001
From: tk-yoshimura <yoshimura8192@gmail.com>
Date: Wed, 24 Jul 2024 09:48:53 +0900
Subject: [PATCH 067/399] Fix holtsmark test

---
 test/test_holtsmark.cpp | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index b5e17dacec..03146feb63 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -752,6 +752,11 @@ void do_test_holtsmark_locscale_param() {
     BOOST_CHECK_EQUAL(mode(dist_0_1), static_cast<RealType>(0));
     BOOST_CHECK_EQUAL(mode(dist_1_3), static_cast<RealType>(1));
 
+    BOOST_CHECK_EQUAL(mean(dist_0_1), static_cast<RealType>(0));
+    BOOST_CHECK_EQUAL(mean(dist_1_3), static_cast<RealType>(1));
+
+    BOOST_CHECK((boost::math::isinf)(variance(dist_0_1)));
+
     BOOST_CHECK_CLOSE(pdf(dist_0_1, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.02038159607840130388931544845552929991729709746772e-1), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist_1_3, static_cast<RealType>(1)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.87352751452164445024482162286994868261727837966217e-1) / 3, tolerance);
 

From c061eaffc509411caa1b14706f449465d0bddec0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 09:21:27 -0400
Subject: [PATCH 068/399] Add CUDA cauchy test

---
 test/cuda_jamfile              |   1 +
 test/test_cauchy_cdf_double.cu | 109 +++++++++++++++++++++++++++++++++
 2 files changed, 110 insertions(+)
 create mode 100644 test/test_cauchy_cdf_double.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 67a779f393..c25a77d912 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -23,6 +23,7 @@ run test_arcsine_pdf_float.cu ;
 run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
 run test_binomial.cpp ;
+run test_cauchy_cdf_double.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_cdf_double.cu b/test/test_cauchy_cdf_double.cu
new file mode 100644
index 0000000000..dc99cbe33c
--- /dev/null
+++ b/test/test_cauchy_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 433e30d9d292f6c8137bdccd5f353098ca47a219 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 09:59:03 -0400
Subject: [PATCH 069/399] Add GPU support to distribution common error handling

---
 .../detail/common_error_handling.hpp          | 28 +++++++++++--------
 1 file changed, 17 insertions(+), 11 deletions(-)

diff --git a/include/boost/math/distributions/detail/common_error_handling.hpp b/include/boost/math/distributions/detail/common_error_handling.hpp
index f03f2c49b8..9c62036661 100644
--- a/include/boost/math/distributions/detail/common_error_handling.hpp
+++ b/include/boost/math/distributions/detail/common_error_handling.hpp
@@ -9,6 +9,7 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_COMMON_ERROR_HANDLING_HPP
 #define BOOST_MATH_DISTRIBUTIONS_COMMON_ERROR_HANDLING_HPP
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
 // using boost::math::isfinite;
@@ -23,7 +24,7 @@ namespace boost{ namespace math{ namespace detail
 {
 
 template <class RealType, class Policy>
-inline bool check_probability(const char* function, RealType const& prob, RealType* result, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool check_probability(const char* function, RealType const& prob, RealType* result, const Policy& pol)
 {
    if((prob < 0) || (prob > 1) || !(boost::math::isfinite)(prob))
    {
@@ -36,7 +37,7 @@ inline bool check_probability(const char* function, RealType const& prob, RealTy
 }
 
 template <class RealType, class Policy>
-inline bool check_df(const char* function, RealType const& df, RealType* result, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool check_df(const char* function, RealType const& df, RealType* result, const Policy& pol)
 { //  df > 0 but NOT +infinity allowed.
    if((df <= 0) || !(boost::math::isfinite)(df))
    {
@@ -49,7 +50,7 @@ inline bool check_df(const char* function, RealType const& df, RealType* result,
 }
 
 template <class RealType, class Policy>
-inline bool check_df_gt0_to_inf(const char* function, RealType const& df, RealType* result, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool check_df_gt0_to_inf(const char* function, RealType const& df, RealType* result, const Policy& pol)
 {  // df > 0 or +infinity are allowed.
    if( (df <= 0) || (boost::math::isnan)(df) )
    { // is bad df <= 0 or NaN or -infinity.
@@ -63,7 +64,7 @@ inline bool check_df_gt0_to_inf(const char* function, RealType const& df, RealTy
 
 
 template <class RealType, class Policy>
-inline bool check_scale(
+BOOST_MATH_GPU_ENABLED inline bool check_scale(
       const char* function,
       RealType scale,
       RealType* result,
@@ -80,7 +81,7 @@ inline bool check_scale(
 }
 
 template <class RealType, class Policy>
-inline bool check_location(
+BOOST_MATH_GPU_ENABLED inline bool check_location(
       const char* function,
       RealType location,
       RealType* result,
@@ -97,7 +98,7 @@ inline bool check_location(
 }
 
 template <class RealType, class Policy>
-inline bool check_x(
+BOOST_MATH_GPU_ENABLED inline bool check_x(
       const char* function,
       RealType x,
       RealType* result,
@@ -118,7 +119,7 @@ inline bool check_x(
 } // bool check_x
 
 template <class RealType, class Policy>
-inline bool check_x_not_NaN(
+BOOST_MATH_GPU_ENABLED inline bool check_x_not_NaN(
   const char* function,
   RealType x,
   RealType* result,
@@ -138,7 +139,7 @@ inline bool check_x_not_NaN(
 } // bool check_x_not_NaN
 
 template <class RealType, class Policy>
-inline bool check_x_gt0(
+BOOST_MATH_GPU_ENABLED inline bool check_x_gt0(
       const char* function,
       RealType x,
       RealType* result,
@@ -159,7 +160,7 @@ inline bool check_x_gt0(
 } // bool check_x_gt0
 
 template <class RealType, class Policy>
-inline bool check_positive_x(
+BOOST_MATH_GPU_ENABLED inline bool check_positive_x(
       const char* function,
       RealType x,
       RealType* result,
@@ -179,13 +180,18 @@ inline bool check_positive_x(
 }
 
 template <class RealType, class Policy>
-inline bool check_non_centrality(
+BOOST_MATH_GPU_ENABLED inline bool check_non_centrality(
       const char* function,
       RealType ncp,
       RealType* result,
       const Policy& pol)
 {
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    static const RealType upper_limit = static_cast<RealType>((std::numeric_limits<long long>::max)()) - boost::math::policies::get_max_root_iterations<Policy>();
+   #else
+   constexpr RealType upper_limit = static_cast<RealType>(LONG_LONG_MAX) - boost::math::policies::get_max_root_iterations<Policy>();
+   #endif
+
    if((ncp < 0) || !(boost::math::isfinite)(ncp) || ncp > upper_limit)
    {
       *result = policies::raise_domain_error<RealType>(
@@ -197,7 +203,7 @@ inline bool check_non_centrality(
 }
 
 template <class RealType, class Policy>
-inline bool check_finite(
+BOOST_MATH_GPU_ENABLED inline bool check_finite(
       const char* function,
       RealType x,
       RealType* result,

From 8c6c4e1854f47308027342950f96d1ee9343c5d8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 09:59:21 -0400
Subject: [PATCH 070/399] Add GPU support to cauchy distribution

---
 include/boost/math/distributions/cauchy.hpp | 73 +++++++++++++--------
 1 file changed, 45 insertions(+), 28 deletions(-)

diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index a18f1dc9b1..a1fcb63e5c 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -13,6 +13,7 @@
 #pragma warning(disable : 4127) // conditional expression is constant
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -30,7 +31,7 @@ namespace detail
 {
 
 template <class RealType, class Policy>
-RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealType& x, bool complement)
+BOOST_MATH_GPU_ENABLED RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealType& x, bool complement)
 {
    //
    // This calculates the cdf of the Cauchy distribution and/or its complement.
@@ -54,7 +55,7 @@ RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealTy
    // to get the result.
    //
    BOOST_MATH_STD_USING // for ADL of std functions
-   static const char* function = "boost::math::cdf(cauchy<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(cauchy<%1%>&, %1%)";
    RealType result = 0;
    RealType location = dist.location();
    RealType scale = dist.scale();
@@ -66,6 +67,16 @@ RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealTy
    {
       return result;
    }
+   #ifdef BOOST_MATH_HAS_GPU_SUPPORT
+   if(x > tools::max_value<RealType>())
+   {
+      return static_cast<RealType>((complement) ? 0 : 1);
+   }
+   if(x < -tools::max_value<RealType>())
+   {
+      return static_cast<RealType>((complement) ? 1 : 0);
+   }
+   #else
    if(std::numeric_limits<RealType>::has_infinity && x == std::numeric_limits<RealType>::infinity())
    { // cdf +infinity is unity.
      return static_cast<RealType>((complement) ? 0 : 1);
@@ -74,6 +85,7 @@ RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealTy
    { // cdf -infinity is zero.
      return static_cast<RealType>((complement) ? 1 : 0);
    }
+   #endif
    if(false == detail::check_x(function, x, &result, Policy()))
    { // Catches x == NaN
       return result;
@@ -88,7 +100,7 @@ RealType cdf_imp(const cauchy_distribution<RealType, Policy>& dist, const RealTy
 } // cdf
 
 template <class RealType, class Policy>
-RealType quantile_imp(
+BOOST_MATH_GPU_ENABLED RealType quantile_imp(
       const cauchy_distribution<RealType, Policy>& dist,
       const RealType& p,
       bool complement)
@@ -101,7 +113,7 @@ RealType quantile_imp(
    // mid-point of the distribution.  This is either added or subtracted
    // from the location parameter depending on whether `complement` is true.
    //
-   static const char* function = "boost::math::quantile(cauchy<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(cauchy<%1%>&, %1%)";
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
@@ -151,20 +163,20 @@ class cauchy_distribution
    typedef RealType value_type;
    typedef Policy policy_type;
 
-   cauchy_distribution(RealType l_location = 0, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED cauchy_distribution(RealType l_location = 0, RealType l_scale = 1)
       : m_a(l_location), m_hg(l_scale)
    {
-    static const char* function = "boost::math::cauchy_distribution<%1%>::cauchy_distribution";
+    constexpr auto function = "boost::math::cauchy_distribution<%1%>::cauchy_distribution";
      RealType result;
      detail::check_location(function, l_location, &result, Policy());
      detail::check_scale(function, l_scale, &result, Policy());
    } // cauchy_distribution
 
-   RealType location()const
+   BOOST_MATH_GPU_ENABLED RealType location()const
    {
       return m_a;
    }
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_hg;
    }
@@ -184,13 +196,15 @@ cauchy_distribution(RealType,RealType)->cauchy_distribution<typename boost::math
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const cauchy_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const cauchy_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-  if (std::numeric_limits<RealType>::has_infinity)
+  #ifndef BOOST_MATH_HAS_GPU_SUPPORT
+  BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
   { 
      return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
+  #endif
   { // Can only use max_value.
    using boost::math::tools::max_value;
    return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
@@ -198,14 +212,16 @@ inline const std::pair<RealType, RealType> range(const cauchy_distribution<RealT
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const cauchy_distribution<RealType, Policy>& )
+BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const cauchy_distribution<RealType, Policy>& )
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-  if (std::numeric_limits<RealType>::has_infinity)
+  #ifndef BOOST_MATH_HAS_GPU_SUPPORT
+  BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
   { 
      return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
+  #endif
   { // Can only use max_value.
      using boost::math::tools::max_value;
      return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
@@ -213,19 +229,19 @@ inline const std::pair<RealType, RealType> support(const cauchy_distribution<Rea
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const cauchy_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const cauchy_distribution<RealType, Policy>& dist, const RealType& x)
 {  
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(cauchy<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(cauchy<%1%>&, %1%)";
    RealType result = 0;
    RealType location = dist.location();
    RealType scale = dist.scale();
-   if(false == detail::check_scale("boost::math::pdf(cauchy<%1%>&, %1%)", scale, &result, Policy()))
+   if(false == detail::check_scale(function, scale, &result, Policy()))
    {
       return result;
    }
-   if(false == detail::check_location("boost::math::pdf(cauchy<%1%>&, %1%)", location, &result, Policy()))
+   if(false == detail::check_location(function, location, &result, Policy()))
    {
       return result;
    }
@@ -250,31 +266,31 @@ inline RealType pdf(const cauchy_distribution<RealType, Policy>& dist, const Rea
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const cauchy_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const cauchy_distribution<RealType, Policy>& dist, const RealType& x)
 {
    return detail::cdf_imp(dist, x, false);
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const cauchy_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const cauchy_distribution<RealType, Policy>& dist, const RealType& p)
 {
    return detail::quantile_imp(dist, p, false);
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<cauchy_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<cauchy_distribution<RealType, Policy>, RealType>& c)
 {
    return detail::cdf_imp(c.dist, c.param, true);
 } //  cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<cauchy_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<cauchy_distribution<RealType, Policy>, RealType>& c)
 {
    return detail::quantile_imp(c.dist, c.param, true);
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const cauchy_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const cauchy_distribution<RealType, Policy>&)
 {  // There is no mean:
    typedef typename Policy::assert_undefined_type assert_type;
    static_assert(assert_type::value == 0, "The Cauchy Distribution has no mean");
@@ -287,7 +303,7 @@ inline RealType mean(const cauchy_distribution<RealType, Policy>&)
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const cauchy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no variance:
    typedef typename Policy::assert_undefined_type assert_type;
@@ -301,18 +317,19 @@ inline RealType variance(const cauchy_distribution<RealType, Policy>& /*dist*/)
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const cauchy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const cauchy_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const cauchy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const cauchy_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
+
 template <class RealType, class Policy>
-inline RealType skewness(const cauchy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no skewness:
    typedef typename Policy::assert_undefined_type assert_type;
@@ -326,7 +343,7 @@ inline RealType skewness(const cauchy_distribution<RealType, Policy>& /*dist*/)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const cauchy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no kurtosis:
    typedef typename Policy::assert_undefined_type assert_type;
@@ -340,7 +357,7 @@ inline RealType kurtosis(const cauchy_distribution<RealType, Policy>& /*dist*/)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const cauchy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const cauchy_distribution<RealType, Policy>& /*dist*/)
 {
    // There is no kurtosis excess:
    typedef typename Policy::assert_undefined_type assert_type;
@@ -354,7 +371,7 @@ inline RealType kurtosis_excess(const cauchy_distribution<RealType, Policy>& /*d
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const cauchy_distribution<RealType, Policy> & dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const cauchy_distribution<RealType, Policy> & dist)
 {
    using std::log;
    return log(2*constants::two_pi<RealType>()*dist.scale());

From 5378b2ec1397d3cdcd3723a513fa4516da8f8a29 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:01:23 -0400
Subject: [PATCH 071/399] Add cauchy cdf for floats test

---
 test/cuda_jamfile             |   3 +-
 test/test_cauchy_cdf_float.cu | 109 ++++++++++++++++++++++++++++++++++
 2 files changed, 111 insertions(+), 1 deletion(-)
 create mode 100644 test/test_cauchy_cdf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index c25a77d912..bd2c47fde1 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -24,8 +24,9 @@ run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
 run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
+run test_cauchy_cdf_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
 run test_beta_double.cu ;
-run test_beta_float.cu ;
\ No newline at end of file
+run test_beta_float.cu ;
diff --git a/test/test_cauchy_cdf_float.cu b/test/test_cauchy_cdf_float.cu
new file mode 100644
index 0000000000..dc99cbe33c
--- /dev/null
+++ b/test/test_cauchy_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From c1cf376d912b594a3514ef383fb84e016d4e45fd Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:02:59 -0400
Subject: [PATCH 072/399] Add cauchy pdf double test

---
 test/cuda_jamfile              |   1 +
 test/test_cauchy_pdf_double.cu | 109 +++++++++++++++++++++++++++++++++
 2 files changed, 110 insertions(+)
 create mode 100644 test/test_cauchy_pdf_double.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index bd2c47fde1..ed73b8057c 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -25,6 +25,7 @@ run test_arcsine_quan_float.cu ;
 run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
+run test_cauchy_pdf_double.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_pdf_double.cu b/test/test_cauchy_pdf_double.cu
new file mode 100644
index 0000000000..7a7fe5ba62
--- /dev/null
+++ b/test/test_cauchy_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 1cdfa55b4417ad359219ee4d1d5c1272fb4690d3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:04:05 -0400
Subject: [PATCH 073/399] Add cauchy pdf float test

---
 test/cuda_jamfile             |   1 +
 test/test_cauchy_pdf_float.cu | 109 ++++++++++++++++++++++++++++++++++
 2 files changed, 110 insertions(+)
 create mode 100644 test/test_cauchy_pdf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index ed73b8057c..072f6b5d8f 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -26,6 +26,7 @@ run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;
+run test_cauchy_pdf_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_pdf_float.cu b/test/test_cauchy_pdf_float.cu
new file mode 100644
index 0000000000..5ec3b604b5
--- /dev/null
+++ b/test/test_cauchy_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 72444dee0d137190c30b7be2cbcdbb4cb83c7d79 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:10:07 -0400
Subject: [PATCH 074/399] Add cauchy quantile double test

---
 test/cuda_jamfile               |   1 +
 test/test_cauchy_quan_double.cu | 109 ++++++++++++++++++++++++++++++++
 2 files changed, 110 insertions(+)
 create mode 100644 test/test_cauchy_quan_double.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 072f6b5d8f..86d91a4dda 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -27,6 +27,7 @@ run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;
 run test_cauchy_pdf_float.cu ;
+run test_cauchy_quan_double.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_quan_double.cu b/test/test_cauchy_quan_double.cu
new file mode 100644
index 0000000000..21f4b4ddaa
--- /dev/null
+++ b/test/test_cauchy_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 6029e578942b521ded5ce0e499b17c62f0bd580c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:11:43 -0400
Subject: [PATCH 075/399] Add cauchy quantile float test

---
 test/cuda_jamfile              |   1 +
 test/test_cauchy_quan_float.cu | 109 +++++++++++++++++++++++++++++++++
 2 files changed, 110 insertions(+)
 create mode 100644 test/test_cauchy_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 86d91a4dda..68a944fe8e 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -28,6 +28,7 @@ run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;
 run test_cauchy_pdf_float.cu ;
 run test_cauchy_quan_double.cu ;
+run test_cauchy_quan_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_quan_float.cu b/test/test_cauchy_quan_float.cu
new file mode 100644
index 0000000000..b6bed15207
--- /dev/null
+++ b/test/test_cauchy_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::cauchy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 2179223f88dbd110faf8f73e124871ee429ca3bb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 16:44:46 -0400
Subject: [PATCH 076/399] Add SYCL testing for cauchy dist

---
 test/sycl_jamfile    |  1 +
 test/test_cauchy.cpp | 31 +++++++++++++++----------------
 2 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 679bae0dcf..0476a651c5 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -11,6 +11,7 @@ project : requirements
 
 # Distributions
 run test_arcsine.cpp ;
+run test_cauchy.cpp ;
 
 # Special Functions
 run test_beta_simple.cpp ;
diff --git a/test/test_cauchy.cpp b/test/test_cauchy.cpp
index 096858d845..f5893264a6 100644
--- a/test/test_cauchy.cpp
+++ b/test/test_cauchy.cpp
@@ -18,7 +18,6 @@
 
 // #define BOOST_MATH_ASSERT_UNDEFINED_POLICY false 
 // To compile even if Cauchy mean is used.
-#include <boost/math/tools/test.hpp>
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 #include <boost/math/distributions/cauchy.hpp>
     using boost::math::cauchy_distribution;
@@ -38,11 +37,11 @@ void test_spots(RealType T)
 {
   // Check some bad parameters to construct the distribution,
 #ifndef BOOST_NO_EXCEPTIONS
-  BOOST_MATH_CHECK_THROW(boost::math::cauchy_distribution<RealType> nbad1(0, 0), std::domain_error); // zero scale.
-  BOOST_MATH_CHECK_THROW(boost::math::cauchy_distribution<RealType> nbad1(0, -1), std::domain_error); // negative scale (shape).
+  BOOST_CHECK_THROW(boost::math::cauchy_distribution<RealType> nbad1(0, 0), std::domain_error); // zero scale.
+  BOOST_CHECK_THROW(boost::math::cauchy_distribution<RealType> nbad1(0, -1), std::domain_error); // negative scale (shape).
 #else
-  BOOST_MATH_CHECK_THROW(boost::math::cauchy_distribution<RealType>(0, 0), std::domain_error); // zero scale.
-  BOOST_MATH_CHECK_THROW(boost::math::cauchy_distribution<RealType>(0, -1), std::domain_error); // negative scale (shape).
+  BOOST_CHECK_THROW(boost::math::cauchy_distribution<RealType>(0, 0), std::domain_error); // zero scale.
+  BOOST_CHECK_THROW(boost::math::cauchy_distribution<RealType>(0, -1), std::domain_error); // negative scale (shape).
 #endif
   cauchy_distribution<RealType> C01;
 
@@ -667,35 +666,35 @@ void test_spots(RealType T)
    // To compile even if Cauchy mean is used.
    // See policy reference, mathematically undefined function policies
    //
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    mean(dist),
    //    std::domain_error);
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    variance(dist),
    //    std::domain_error);
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    standard_deviation(dist),
    //    std::domain_error);
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    kurtosis(dist),
    //    std::domain_error);
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    kurtosis_excess(dist),
    //    std::domain_error);
-   //BOOST_MATH_CHECK_THROW(
+   //BOOST_CHECK_THROW(
    //    skewness(dist),
    //    std::domain_error);
 
-   BOOST_MATH_CHECK_THROW(
+   BOOST_CHECK_THROW(
        quantile(dist, RealType(0.0)),
        std::overflow_error);
-   BOOST_MATH_CHECK_THROW(
+   BOOST_CHECK_THROW(
        quantile(dist, RealType(1.0)),
        std::overflow_error);
-   BOOST_MATH_CHECK_THROW(
+   BOOST_CHECK_THROW(
        quantile(complement(dist, RealType(0.0))),
        std::overflow_error);
-   BOOST_MATH_CHECK_THROW(
+   BOOST_CHECK_THROW(
        quantile(complement(dist, RealType(1.0))),
        std::overflow_error);
 
@@ -705,7 +704,7 @@ void test_spots(RealType T)
 
 } // template <class RealType>void test_spots(RealType)
 
-BOOST_AUTO_TEST_CASE( test_main )
+BOOST_AUTO_TEST_CASE(test_main)
 {
   BOOST_MATH_CONTROL_FP;
    // Check that can generate cauchy distribution using the two convenience methods:

From 6aae286335fb16cfa3ebf521159bf9327b469e74 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:46:02 -0400
Subject: [PATCH 077/399] Add cbrt CUDA testing

---
 test/cuda_jamfile        |  2 +
 test/test_cbrt_double.cu | 99 ++++++++++++++++++++++++++++++++++++++++
 test/test_cbrt_float.cu  | 99 ++++++++++++++++++++++++++++++++++++++++
 3 files changed, 200 insertions(+)
 create mode 100644 test/test_cbrt_double.cu
 create mode 100644 test/test_cbrt_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 68a944fe8e..cc2d9d7665 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -34,3 +34,5 @@ run test_cauchy_quan_float.cu ;
 # run test_beta_simple.cpp ;
 run test_beta_double.cu ;
 run test_beta_float.cu ;
+run test_cbrt_double.cu ;
+run test_cbrt_float.cu ;
diff --git a/test/test_cbrt_double.cu b/test/test_cbrt_double.cu
new file mode 100644
index 0000000000..cc2c326850
--- /dev/null
+++ b/test/test_cbrt_double.cu
@@ -0,0 +1,99 @@
+
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cbrt(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cbrt(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cbrt_float.cu b/test/test_cbrt_float.cu
new file mode 100644
index 0000000000..a4e98cce8d
--- /dev/null
+++ b/test/test_cbrt_float.cu
@@ -0,0 +1,99 @@
+
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cbrt(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cbrt(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 7dd8f958da860c2bf9a4523a88e9fb9feec1d173 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 10:59:41 -0400
Subject: [PATCH 078/399] Enable GPU support for cbrt

---
 include/boost/math/special_functions/cbrt.hpp     | 11 ++++++-----
 include/boost/math/special_functions/math_fwd.hpp |  4 ++--
 2 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/include/boost/math/special_functions/cbrt.hpp b/include/boost/math/special_functions/cbrt.hpp
index 77cd5f0aec..2488bb5d46 100644
--- a/include/boost/math/special_functions/cbrt.hpp
+++ b/include/boost/math/special_functions/cbrt.hpp
@@ -10,6 +10,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -38,7 +39,7 @@ struct largest_cbrt_int_type
 };
 
 template <typename T, typename Policy>
-T cbrt_imp(T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T cbrt_imp(T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    //
@@ -51,7 +52,7 @@ T cbrt_imp(T z, const Policy& pol)
    // Expected Error Term:                         -1.231e-006
    // Maximum Relative Change in Control Points:   5.982e-004
    //
-   static const T P[] = { 
+   BOOST_MATH_STATIC const T P[] = { 
       static_cast<T>(0.37568269008611818),
       static_cast<T>(1.3304968705558024),
       static_cast<T>(-1.4897101632445036),
@@ -59,7 +60,7 @@ T cbrt_imp(T z, const Policy& pol)
       static_cast<T>(-0.6398703759826468),
       static_cast<T>(0.13584489959258635),
    };
-   static const T correction[] = {
+   BOOST_MATH_STATIC const T correction[] = {
       static_cast<T>(0.62996052494743658238360530363911),  // 2^-2/3
       static_cast<T>(0.79370052598409973737585281963615),  // 2^-1/3
       static_cast<T>(1),
@@ -154,7 +155,7 @@ T cbrt_imp(T z, const Policy& pol)
 } // namespace detail
 
 template <typename T, typename Policy>
-inline typename tools::promote_args<T>::type cbrt(T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cbrt(T z, const Policy& pol)
 {
    using result_type = typename tools::promote_args<T>::type;
    using value_type = typename policies::evaluation<result_type, Policy>::type;
@@ -162,7 +163,7 @@ inline typename tools::promote_args<T>::type cbrt(T z, const Policy& pol)
 }
 
 template <typename T>
-inline typename tools::promote_args<T>::type cbrt(T z)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cbrt(T z)
 {
    return cbrt(z, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 6119c8e863..3495416f23 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -561,10 +561,10 @@ namespace boost
 
    // cbrt - cube root.
    template <class RT>
-   tools::promote_args_t<RT> cbrt(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> cbrt(RT z);
 
    template <class RT, class Policy>
-   tools::promote_args_t<RT> cbrt(RT z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> cbrt(RT z, const Policy&);
 
    // log1p is log(x + 1)
    template <class T>

From 6cb20fdf3f3deeb9895b2ed90dc784ca996fa7cc Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 16:27:34 -0400
Subject: [PATCH 079/399] Fix inconsistent force inline warnings for ellint 1

---
 .../boost/math/special_functions/ellint_1.hpp | 20 ++++++++++---------
 .../boost/math/special_functions/math_fwd.hpp |  2 ++
 2 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/include/boost/math/special_functions/ellint_1.hpp b/include/boost/math/special_functions/ellint_1.hpp
index dfc1815f7f..f7fbbce40c 100644
--- a/include/boost/math/special_functions/ellint_1.hpp
+++ b/include/boost/math/special_functions/ellint_1.hpp
@@ -1,5 +1,6 @@
 //  Copyright (c) 2006 Xiaogang Zhang
 //  Copyright (c) 2006 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -18,6 +19,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/constants/constants.hpp>
@@ -36,13 +38,13 @@ typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy&
 namespace detail{
 
 template <typename T, typename Policy>
-T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 0> const&);
+BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 0> const&);
 template <typename T, typename Policy>
-T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 1> const&);
+BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 1> const&);
 template <typename T, typename Policy>
-T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&);
+BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&);
 template <typename T, typename Policy>
-T ellint_k_imp(T k, const Policy& pol, T one_minus_k2);
+BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, T one_minus_k2);
 
 // Elliptic integral (Legendre form) of the first kind
 template <typename T, typename Policy>
@@ -760,7 +762,7 @@ BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_cons
 }
 
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_1(T k, const Policy& pol, const std::true_type&)
+typename tools::promote_args<T>::type ellint_1(T k, const Policy& pol, const std::true_type&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -776,7 +778,7 @@ BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_1(T k, const
 }
 
 template <class T1, class T2>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const std::false_type&)
+typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const std::false_type&)
 {
    return boost::math::ellint_1(k, phi, policies::policy<>());
 }
@@ -785,14 +787,14 @@ BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_1(T1 k,
 
 // Complete elliptic integral (Legendre form) of the first kind
 template <typename T>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_1(T k)
+typename tools::promote_args<T>::type ellint_1(T k)
 {
    return ellint_1(k, policies::policy<>());
 }
 
 // Elliptic integral (Legendre form) of the first kind
 template <class T1, class T2, class Policy>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
+typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -800,7 +802,7 @@ BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_1(T1 k,
 }
 
 template <class T1, class T2>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi)
+typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi)
 {
    typedef typename policies::is_policy<T2>::type tag_type;
    return detail::ellint_1(k, phi, tag_type());
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 3495416f23..1199d8ca12 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -4,6 +4,7 @@
 
 // Copyright Paul A. Bristow 2006.
 // Copyright John Maddock 2006.
+// Copyright Matt Borland 2024
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -26,6 +27,7 @@
 #include <vector>
 #include <complex>
 #include <type_traits>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/detail/round_fwd.hpp>
 #include <boost/math/tools/promotion.hpp> // for argument promotion.
 #include <boost/math/policies/policy.hpp>

From 6eeca996b479122de7ac204255cb5f99ccf02a9b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 16:30:15 -0400
Subject: [PATCH 080/399] Fix inconsistent force inline warnings for ellint 2

---
 .../boost/math/special_functions/ellint_2.hpp   | 17 +++++++++--------
 1 file changed, 9 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/special_functions/ellint_2.hpp b/include/boost/math/special_functions/ellint_2.hpp
index b09cdd490e..5e2552ceca 100644
--- a/include/boost/math/special_functions/ellint_2.hpp
+++ b/include/boost/math/special_functions/ellint_2.hpp
@@ -1,5 +1,6 @@
 //  Copyright (c) 2006 Xiaogang Zhang
 //  Copyright (c) 2006 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -38,11 +39,11 @@ typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy&
 namespace detail{
 
 template <typename T, typename Policy>
-T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 0>&);
+BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 0>&);
 template <typename T, typename Policy>
-T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 1>&);
+BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 1>&);
 template <typename T, typename Policy>
-T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 2>&);
+BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 2>&);
 
 // Elliptic integral (Legendre form) of the second kind
 template <typename T, typename Policy>
@@ -701,7 +702,7 @@ BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, std::integral_cons
 }
 
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_2(T k, const Policy& pol, const std::true_type&)
+typename tools::promote_args<T>::type ellint_2(T k, const Policy& pol, const std::true_type&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -714,7 +715,7 @@ BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_2(T k, const
 
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const std::false_type&)
+typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const std::false_type&)
 {
    return boost::math::ellint_2(k, phi, policies::policy<>());
 }
@@ -723,21 +724,21 @@ BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_2(T1 k,
 
 // Complete elliptic integral (Legendre form) of the second kind
 template <typename T>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T>::type ellint_2(T k)
+typename tools::promote_args<T>::type ellint_2(T k)
 {
    return ellint_2(k, policies::policy<>());
 }
 
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi)
+typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi)
 {
    typedef typename policies::is_policy<T2>::type tag_type;
    return detail::ellint_2(k, phi, tag_type());
 }
 
 template <class T1, class T2, class Policy>
-BOOST_MATH_FORCEINLINE typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
+typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;

From 405e13847b7788c71ffb314861d7f64fa63f3b12 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 23 Jul 2024 16:50:16 -0400
Subject: [PATCH 081/399] Add SYCL testing for cbrt

---
 include_private/boost/math/tools/test.hpp | 5 ++++-
 test/handle_test_result.hpp               | 2 +-
 test/sycl_jamfile                         | 1 +
 test/test_cbrt.cpp                        | 3 +++
 test/test_cbrt.hpp                        | 4 +++-
 5 files changed, 12 insertions(+), 3 deletions(-)

diff --git a/include_private/boost/math/tools/test.hpp b/include_private/boost/math/tools/test.hpp
index 10f6143e2b..8f4db18c15 100644
--- a/include_private/boost/math/tools/test.hpp
+++ b/include_private/boost/math/tools/test.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -253,6 +254,7 @@ test_result<Real> test_hetero(const A& a, F1 test_func, F2 expect_func)
    return result;
 }
 
+#ifndef BOOST_MATH_NO_EXCEPTIONS
 template <class Val, class Exception>
 void test_check_throw(Val, Exception)
 {
@@ -293,6 +295,7 @@ void test_check_throw(Val v, boost::math::rounding_error const*)
       BOOST_CHECK((v == boost::math::tools::max_value<Val>()) || (v == -boost::math::tools::max_value<Val>()));
    }
 }
+#endif
 
 } // namespace tools
 } // namespace math
@@ -303,7 +306,7 @@ void test_check_throw(Val v, boost::math::rounding_error const*)
   // exception-free testing support, ideally we'd only define this in our tests,
   // but to keep things simple we really need it somewhere that's always included:
   //
-#ifdef BOOST_NO_EXCEPTIONS
+#ifdef BOOST_MATH_NO_EXCEPTIONS
 #  define BOOST_MATH_CHECK_THROW(x, ExceptionType) boost::math::tools::test_check_throw(x, static_cast<ExceptionType const*>(nullptr));
 #else
 #  define BOOST_MATH_CHECK_THROW(x, y) BOOST_CHECK_THROW(x, y)
diff --git a/test/handle_test_result.hpp b/test/handle_test_result.hpp
index e909d64583..66bfe557b1 100644
--- a/test/handle_test_result.hpp
+++ b/test/handle_test_result.hpp
@@ -6,8 +6,8 @@
 #ifndef BOOST_MATH_HANDLE_TEST_RESULT
 #define BOOST_MATH_HANDLE_TEST_RESULT
 
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/regex.hpp>
 #include <boost/test/test_tools.hpp>
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 0476a651c5..ec49dad3e7 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -15,3 +15,4 @@ run test_cauchy.cpp ;
 
 # Special Functions
 run test_beta_simple.cpp ;
+run test_cbrt.cpp ;
diff --git a/test/test_cbrt.cpp b/test/test_cbrt.cpp
index 8b36a765d0..6abb9bd885 100644
--- a/test/test_cbrt.cpp
+++ b/test/test_cbrt.cpp
@@ -9,7 +9,10 @@
 #  pragma warning (disable : 4224)
 #endif
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp> // include /libs/math/src/
+#endif
+
 #include "test_cbrt.hpp"
 
 #include <boost/math/special_functions/cbrt.hpp> // Added to avoid link failure missing cbrt variants.
diff --git a/test/test_cbrt.hpp b/test/test_cbrt.hpp
index f606a58407..77e4aed516 100644
--- a/test/test_cbrt.hpp
+++ b/test/test_cbrt.hpp
@@ -1,5 +1,6 @@
 // Copyright John Maddock 2006.
 // Copyright Paul A. Bristow 2007, 2009
+// Copyright Matt Borland 2024
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -9,7 +10,6 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -93,7 +93,9 @@ void test_cbrt(T, const char* name)
    }
    BOOST_IF_CONSTEXPR(std::numeric_limits<T>::has_quiet_NaN)
    {
+      #ifndef BOOST_MATH_NO_EXCEPTIONS
       BOOST_CHECK_THROW(boost::math::cbrt(std::numeric_limits<T>::quiet_NaN()), std::domain_error);
+      #endif
    }
 
 }

From 59616f8600490dd26bcf5a7d8544c3894d05ebf5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 09:26:03 -0400
Subject: [PATCH 082/399] Add changesign testing

---
 test/cuda_jamfile              |   2 +
 test/test_changesign_double.cu | 111 +++++++++++++++++++++++++++++++++
 test/test_changesign_float.cu  | 111 +++++++++++++++++++++++++++++++++
 3 files changed, 224 insertions(+)
 create mode 100644 test/test_changesign_double.cu
 create mode 100644 test/test_changesign_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index cc2d9d7665..2494853a90 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -36,3 +36,5 @@ run test_beta_double.cu ;
 run test_beta_float.cu ;
 run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
+run test_changesign_double.cu ;
+run test_changesign_float.cu ;
diff --git a/test/test_changesign_double.cu b/test/test_changesign_double.cu
new file mode 100644
index 0000000000..bfb2ade1e2
--- /dev/null
+++ b/test/test_changesign_double.cu
@@ -0,0 +1,111 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/sign.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::changesign(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+        switch(i % 55)
+        {
+        case 1:
+           h_A[i] = 0;
+           break;
+        case 2:
+           h_A[i] = std::numeric_limits<float_type>::infinity();
+           break;
+        case 3:
+           h_A[i] = -std::numeric_limits<float_type>::infinity();
+           break;
+        }
+        if(i % 1)
+           h_A[i] = -h_A[i];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::changesign(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (h_C[i] != results[i])
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_changesign_float.cu b/test/test_changesign_float.cu
new file mode 100644
index 0000000000..d7e1764bdf
--- /dev/null
+++ b/test/test_changesign_float.cu
@@ -0,0 +1,111 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/sign.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::changesign(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+        switch(i % 55)
+        {
+        case 1:
+           h_A[i] = 0;
+           break;
+        case 2:
+           h_A[i] = std::numeric_limits<float_type>::infinity();
+           break;
+        case 3:
+           h_A[i] = -std::numeric_limits<float_type>::infinity();
+           break;
+        }
+        if(i % 1)
+           h_A[i] = -h_A[i];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::changesign(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (h_C[i] != results[i])
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From bc523045738709cf4a5b87385593be0c737bdeb9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 09:49:19 -0400
Subject: [PATCH 083/399] Make sign manipulation functions GPU compatible

---
 .../special_functions/detail/fp_traits.hpp    | 65 ++++++++++---------
 .../boost/math/special_functions/math_fwd.hpp | 10 +--
 include/boost/math/special_functions/sign.hpp | 23 ++++---
 3 files changed, 53 insertions(+), 45 deletions(-)

diff --git a/include/boost/math/special_functions/detail/fp_traits.hpp b/include/boost/math/special_functions/detail/fp_traits.hpp
index 2947a32a21..015ea9cd35 100644
--- a/include/boost/math/special_functions/detail/fp_traits.hpp
+++ b/include/boost/math/special_functions/detail/fp_traits.hpp
@@ -4,6 +4,7 @@
 #define BOOST_MATH_FP_TRAITS_HPP
 
 // Copyright (c) 2006 Johan Rade
+// Copyright (c) 2024 Matt Borland
 
 // Distributed under the Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -24,6 +25,7 @@ With these techniques, the code could be simplified.
 #include <cstdint>
 #include <limits>
 #include <type_traits>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/is_standalone.hpp>
 #include <boost/math/tools/assert.hpp>
 
@@ -202,14 +204,14 @@ template<> struct fp_traits_non_native<float, single_precision>
 {
     typedef ieee_copy_all_bits_tag method;
 
-    static constexpr uint32_t sign        = 0x80000000u;
-    static constexpr uint32_t exponent    = 0x7f800000;
-    static constexpr uint32_t flag        = 0x00000000;
-    static constexpr uint32_t significand = 0x007fffff;
+    BOOST_MATH_STATIC constexpr uint32_t sign        = 0x80000000u;
+    BOOST_MATH_STATIC constexpr uint32_t exponent    = 0x7f800000;
+    BOOST_MATH_STATIC constexpr uint32_t flag        = 0x00000000;
+    BOOST_MATH_STATIC constexpr uint32_t significand = 0x007fffff;
 
     typedef uint32_t bits;
-    static void get_bits(float x, uint32_t& a) { std::memcpy(&a, &x, 4); }
-    static void set_bits(float& x, uint32_t a) { std::memcpy(&x, &a, 4); }
+    BOOST_MATH_GPU_ENABLED static void get_bits(float x, uint32_t& a) { std::memcpy(&a, &x, 4); }
+    BOOST_MATH_GPU_ENABLED static void set_bits(float& x, uint32_t a) { std::memcpy(&x, &a, 4); }
 };
 
 // ieee_tag version, double (64 bits) ----------------------------------------------
@@ -250,15 +252,15 @@ template<> struct fp_traits_non_native<double, double_precision>
 {
     typedef ieee_copy_all_bits_tag method;
 
-    static constexpr uint64_t sign     = static_cast<uint64_t>(0x80000000u) << 32;
-    static constexpr uint64_t exponent = static_cast<uint64_t>(0x7ff00000) << 32;
-    static constexpr uint64_t flag     = 0;
-    static constexpr uint64_t significand
+    BOOST_MATH_STATIC constexpr uint64_t sign     = static_cast<uint64_t>(0x80000000u) << 32;
+    BOOST_MATH_STATIC constexpr uint64_t exponent = static_cast<uint64_t>(0x7ff00000) << 32;
+    BOOST_MATH_STATIC constexpr uint64_t flag     = 0;
+    BOOST_MATH_STATIC constexpr uint64_t significand
         = (static_cast<uint64_t>(0x000fffff) << 32) + static_cast<uint64_t>(0xffffffffu);
 
     typedef uint64_t bits;
-    static void get_bits(double x, uint64_t& a) { std::memcpy(&a, &x, 8); }
-    static void set_bits(double& x, uint64_t a) { std::memcpy(&x, &a, 8); }
+    BOOST_MATH_GPU_ENABLED static void get_bits(double x, uint64_t& a) { std::memcpy(&a, &x, 8); }
+    BOOST_MATH_GPU_ENABLED static void set_bits(double& x, uint64_t a) { std::memcpy(&x, &a, 8); }
 };
 
 #endif
@@ -330,10 +332,10 @@ struct fp_traits_non_native<long double, extended_double_precision>
 {
     typedef ieee_copy_leading_bits_tag method;
 
-    static constexpr uint32_t sign        = 0x80000000u;
-    static constexpr uint32_t exponent    = 0x7fff0000;
-    static constexpr uint32_t flag        = 0x00008000;
-    static constexpr uint32_t significand = 0x00007fff;
+    BOOST_MATH_STATIC constexpr uint32_t sign        = 0x80000000u;
+    BOOST_MATH_STATIC constexpr uint32_t exponent    = 0x7fff0000;
+    BOOST_MATH_STATIC constexpr uint32_t flag        = 0x00008000;
+    BOOST_MATH_STATIC constexpr uint32_t significand = 0x00007fff;
 
     typedef uint32_t bits;
 
@@ -381,10 +383,10 @@ struct fp_traits_non_native<long double, extended_double_precision>
 {
     typedef ieee_copy_leading_bits_tag method;
 
-    static constexpr uint32_t sign        = 0x80000000u;
-    static constexpr uint32_t exponent    = 0x7ff00000;
-    static constexpr uint32_t flag        = 0x00000000;
-    static constexpr uint32_t significand = 0x000fffff;
+    BOOST_MATH_STATIC constexpr uint32_t sign        = 0x80000000u;
+    BOOST_MATH_STATIC constexpr uint32_t exponent    = 0x7ff00000;
+    BOOST_MATH_STATIC constexpr uint32_t flag        = 0x00000000;
+    BOOST_MATH_STATIC constexpr uint32_t significand = 0x000fffff;
 
     typedef uint32_t bits;
 
@@ -399,7 +401,7 @@ struct fp_traits_non_native<long double, extended_double_precision>
     }
 
 private:
-    static constexpr int offset_ = BOOST_MATH_ENDIAN_BIG_BYTE ? 0 : 12;
+    BOOST_MATH_STATIC constexpr int offset_ = BOOST_MATH_ENDIAN_BIG_BYTE ? 0 : 12;
 };
 
 
@@ -419,10 +421,10 @@ struct fp_traits_non_native<long double, extended_double_precision>
 {
     typedef ieee_copy_leading_bits_tag method;
 
-    static constexpr uint32_t sign        = 0x80000000u;
-    static constexpr uint32_t exponent    = 0x7fff0000;
-    static constexpr uint32_t flag        = 0x00008000;
-    static constexpr uint32_t significand = 0x00007fff;
+    BOOST_MATH_STATIC constexpr uint32_t sign        = 0x80000000u;
+    BOOST_MATH_STATIC constexpr uint32_t exponent    = 0x7fff0000;
+    BOOST_MATH_STATIC constexpr uint32_t flag        = 0x00008000;
+    BOOST_MATH_STATIC constexpr uint32_t significand = 0x00007fff;
 
     // copy 1st, 2nd, 5th and 6th byte. 3rd and 4th byte are padding.
 
@@ -455,10 +457,10 @@ struct fp_traits_non_native<long double, extended_double_precision>
 {
     typedef ieee_copy_leading_bits_tag method;
 
-    static constexpr uint32_t sign        = 0x80000000u;
-    static constexpr uint32_t exponent    = 0x7fff0000;
-    static constexpr uint32_t flag        = 0x00000000;
-    static constexpr uint32_t significand = 0x0000ffff;
+    BOOST_MATH_STATIC constexpr uint32_t sign        = 0x80000000u;
+    BOOST_MATH_STATIC constexpr uint32_t exponent    = 0x7fff0000;
+    BOOST_MATH_STATIC constexpr uint32_t flag        = 0x00000000;
+    BOOST_MATH_STATIC constexpr uint32_t significand = 0x0000ffff;
 
     typedef uint32_t bits;
 
@@ -473,7 +475,7 @@ struct fp_traits_non_native<long double, extended_double_precision>
     }
 
 private:
-    static constexpr int offset_ = BOOST_MATH_ENDIAN_BIG_BYTE ? 0 : 12;
+    BOOST_MATH_STATIC constexpr int offset_ = BOOST_MATH_ENDIAN_BIG_BYTE ? 0 : 12;
 };
 
 #endif
@@ -553,7 +555,8 @@ struct select_native<long double>
    && !defined(BOOST_MATH_DISABLE_STD_FPCLASSIFY)\
    && !defined(__INTEL_COMPILER)\
    && !defined(sun)\
-   && !defined(__VXWORKS__)
+   && !defined(__VXWORKS__)\
+   && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
 #  define BOOST_MATH_USE_STD_FPCLASSIFY
 #endif
 
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 1199d8ca12..b6fa2abf90 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -885,16 +885,18 @@ namespace boost
    bool isnormal BOOST_NO_MACRO_EXPAND(T t);
 
    template<class T>
-   int signbit BOOST_NO_MACRO_EXPAND(T x);
+   BOOST_MATH_GPU_ENABLED int signbit BOOST_NO_MACRO_EXPAND(T x);
 
    template <class T>
-   int sign BOOST_NO_MACRO_EXPAND(const T& z);
+   BOOST_MATH_GPU_ENABLED int sign BOOST_NO_MACRO_EXPAND(const T& z);
 
    template <class T, class U>
-   typename tools::promote_args_permissive<T, U>::type copysign BOOST_NO_MACRO_EXPAND(const T& x, const U& y);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args_permissive<T, U>::type 
+   copysign BOOST_NO_MACRO_EXPAND(const T& x, const U& y);
 
    template <class T>
-   typename tools::promote_args_permissive<T>::type changesign BOOST_NO_MACRO_EXPAND(const T& z);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args_permissive<T>::type 
+   changesign BOOST_NO_MACRO_EXPAND(const T& z);
 
    // Exponential integrals:
    namespace detail{
diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index 8f9fc4793a..cd7fdfb2ab 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -1,6 +1,7 @@
 //  (C) Copyright John Maddock 2006.
 //  (C) Copyright Johan Rade 2006.
 //  (C) Copyright Paul A. Bristow 2011 (added changesign).
+//  (C) Copyright Matt Borland 2024
 
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
@@ -35,13 +36,13 @@ namespace detail {
     // signed zero or NaN.
 
     template<class T>
-    inline int signbit_impl(T x, generic_tag<true> const&)
+    BOOST_MATH_GPU_ENABLED inline int signbit_impl(T x, generic_tag<true> const&)
     {
         return x < 0;
     }
 
     template<class T> 
-    inline int signbit_impl(T x, generic_tag<false> const&)
+    BOOST_MATH_GPU_ENABLED inline int signbit_impl(T x, generic_tag<false> const&)
     {
         return x < 0;
     }
@@ -91,13 +92,13 @@ namespace detail {
     // signed zero or NaN.
 
     template<class T>
-    inline T (changesign_impl)(T x, generic_tag<true> const&)
+    BOOST_MATH_GPU_ENABLED inline T (changesign_impl)(T x, generic_tag<true> const&)
     {
         return -x;
     }
 
     template<class T>
-    inline T (changesign_impl)(T x, generic_tag<false> const&)
+    BOOST_MATH_GPU_ENABLED inline T (changesign_impl)(T x, generic_tag<false> const&)
     {
         return -x;
     }
@@ -124,7 +125,7 @@ namespace detail {
 #endif
 
     template<class T>
-    inline T changesign_impl(T x, ieee_copy_all_bits_tag const&)
+    BOOST_MATH_GPU_ENABLED inline T changesign_impl(T x, ieee_copy_all_bits_tag const&)
     {
         typedef typename fp_traits<T>::sign_change_type traits;
 
@@ -136,7 +137,7 @@ namespace detail {
     }
 
     template<class T>
-    inline T (changesign_impl)(T x, ieee_copy_leading_bits_tag const&)
+    BOOST_MATH_GPU_ENABLED inline T (changesign_impl)(T x, ieee_copy_leading_bits_tag const&)
     {
         typedef typename fp_traits<T>::sign_change_type traits;
 
@@ -150,7 +151,8 @@ namespace detail {
 
 }   // namespace detail
 
-template<class T> int (signbit)(T x)
+template<class T> 
+BOOST_MATH_GPU_ENABLED int (signbit)(T x)
 { 
    typedef typename detail::fp_traits<T>::type traits;
    typedef typename traits::method method;
@@ -160,12 +162,13 @@ template<class T> int (signbit)(T x)
 }
 
 template <class T>
-inline int sign BOOST_NO_MACRO_EXPAND(const T& z)
+BOOST_MATH_GPU_ENABLED inline int sign BOOST_NO_MACRO_EXPAND(const T& z)
 {
    return (z == 0) ? 0 : (boost::math::signbit)(z) ? -1 : 1;
 }
 
-template <class T> typename tools::promote_args_permissive<T>::type (changesign)(const T& x)
+template <class T> 
+BOOST_MATH_GPU_ENABLED typename tools::promote_args_permissive<T>::type (changesign)(const T& x)
 { //!< \brief return unchanged binary pattern of x, except for change of sign bit. 
    typedef typename detail::fp_traits<T>::sign_change_type traits;
    typedef typename traits::method method;
@@ -176,7 +179,7 @@ template <class T> typename tools::promote_args_permissive<T>::type (changesign)
 }
 
 template <class T, class U>
-inline typename tools::promote_args_permissive<T, U>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args_permissive<T, U>::type 
    copysign BOOST_NO_MACRO_EXPAND(const T& x, const U& y)
 {
    BOOST_MATH_STD_USING

From 922024f93866d921bf196a19d17fbe3a11d4840e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 09:52:19 -0400
Subject: [PATCH 084/399] Disable real concept tests for SYCL

---
 include/boost/math/tools/config.hpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 63057e47f3..9109811e53 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -701,6 +701,7 @@ namespace boost{ namespace math{
 
 // spir64 does not support long double
 #  define BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+#  define BOOST_MATH_NO_REAL_CONCEPT_TESTS
 
 #  undef BOOST_MATH_FORCEINLINE
 #  define BOOST_MATH_FORCEINLINE inline

From 2dbbdcb823135f6c5fe29f973433a0c53bb8e689 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 09:52:34 -0400
Subject: [PATCH 085/399] Add sign manipulation tests for sycl

---
 test/sycl_jamfile  | 1 +
 test/test_sign.cpp | 5 ++++-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index ec49dad3e7..9656ee7a70 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -16,3 +16,4 @@ run test_cauchy.cpp ;
 # Special Functions
 run test_beta_simple.cpp ;
 run test_cbrt.cpp ;
+run test_sign.cpp ;
diff --git a/test/test_sign.cpp b/test/test_sign.cpp
index 864d2dd121..530a60d503 100644
--- a/test/test_sign.cpp
+++ b/test/test_sign.cpp
@@ -1,5 +1,6 @@
-#define BOOST_TEST_MAIN// Copyright John Maddock 2008
+// Copyright John Maddock 2008
 //  (C) Copyright Paul A. Bristow 2011 (added tests for changesign)
+// Copyright Matt Borland 2024
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -147,7 +148,9 @@ BOOST_AUTO_TEST_CASE( test_main )
    test_spots(0.0, "double"); // Test double. OK at decdigits 7, tolerance = 1e07 %
    // long double support for the sign functions is considered "core" so we always test it
    // even when long double support is turned off via BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
    test_spots(0.0L, "long double"); // Test long double.
+#endif
 #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
    test_spots(boost::math::concepts::real_concept(0), "real_concept"); // Test real_concept.
 #endif

From ed4b8fde9834fb9ccbe69039f24488bdfa3c9853 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:35:59 -0400
Subject: [PATCH 086/399] Change ignore error handling for GPUS

---
 .../boost/math/distributions/detail/common_error_handling.hpp | 1 +
 include/boost/math/policies/error_handling.hpp                | 4 ++++
 2 files changed, 5 insertions(+)

diff --git a/include/boost/math/distributions/detail/common_error_handling.hpp b/include/boost/math/distributions/detail/common_error_handling.hpp
index 9c62036661..9922396d5f 100644
--- a/include/boost/math/distributions/detail/common_error_handling.hpp
+++ b/include/boost/math/distributions/detail/common_error_handling.hpp
@@ -1,5 +1,6 @@
 // Copyright John Maddock 2006, 2007.
 // Copyright Paul A. Bristow 2006, 2007, 2012.
+// Copyright Matt Borland 2024
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 1329dba10b..985bdff22b 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -598,7 +598,11 @@ BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
    static_assert(std::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
+   #else
+   return val > 0 ? static_cast<TargetType>(1) : -static_cast<TargetType>(1);
+   #endif
 }
 
 template <class T, class TargetType>

From 0cee1e8b6d79ddd65da4ac88eba7dc3226da999a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:36:16 -0400
Subject: [PATCH 087/399] Apply SYCL default policy to CUDA as well

---
 include/boost/math/policies/policy.hpp | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index a819a4cb6b..f12837a2a6 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -45,13 +45,6 @@ namespace policies{
 #  ifndef BOOST_MATH_PROMOTE_DOUBLE_POLICY
 #     define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
 #  endif
-#endif
-
-//
-// Refined support for sycl since it does not support errno
-//
-
-#ifdef BOOST_MATH_ENABLE_SYCL
 #  ifndef BOOST_MATH_DOMAIN_ERROR_POLICY
 #    define BOOST_MATH_DOMAIN_ERROR_POLICY ignore_error
 #  endif

From 530296e5605dba961e68d22a2d970030a9716360 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:36:36 -0400
Subject: [PATCH 088/399] Fix GPU safe functions and add macro for local static
 variables

---
 include/boost/math/tools/config.hpp | 19 +++++++++++++------
 1 file changed, 13 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 9109811e53..c03f6170a8 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -734,15 +734,15 @@ BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_min(const T& a, const T& b) { return
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { return a > b ? a : b; }
 
-#define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b);
-#define BOOST_MATH_GPU_SAFE_MIN(a, b) gpu_safe_min(a, b);
-#define BOOST_MATH_GPU_SAFE_MAX(a, b) gpu_safe_max(a, b);
+#define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b)
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) gpu_safe_min(a, b)
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) gpu_safe_max(a, b)
 
 #else
 
-#define BOOST_MATH_GPU_SAFE_SWAP(a, b) std::swap(a, b);
-#define BOOST_MATH_GPU_SAFE_MIN(a, b) (std::min)(a, b);
-#define BOOST_MATH_GPU_SAFE_MAX(a, b) (std::max)(a, b);
+#define BOOST_MATH_GPU_SAFE_SWAP(a, b) std::swap(a, b)
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) (std::min)(a, b)
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) (std::max)(a, b)
 
 #endif
 
@@ -752,13 +752,20 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_STATIC_CONSTEXPR inline constexpr
 #  define BOOST_MATH_STATIC static
+#  ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#    define BOOST_MATH_STATIC_LOCAL_VARIABLE static
+#  else
+#    define BOOST_MATH_STATIC_LOCAL_VARIABLE
+#  endif
 #else
 #  ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #    define BOOST_MATH_STATIC_CONSTEXPR static constexpr
 #    define BOOST_MATH_STATIC static
+#    define BOOST_MATH_STATIC_LOCAL_VARIABLE
 #  else
 #    define BOOST_MATH_STATIC_CONSTEXPR constexpr
 #    define BOOST_MATH_STATIC constexpr
+#    define BOOST_MATH_STATIC_LOCAL_VARIABLE static
 #  endif
 #endif
 

From 7991d0bb3293fde1523c65fc6105f39a32a02128 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:37:01 -0400
Subject: [PATCH 089/399] Make trunc GPU compatible

---
 .../special_functions/detail/round_fwd.hpp    | 17 ++++---
 .../boost/math/special_functions/math_fwd.hpp |  8 +--
 .../boost/math/special_functions/trunc.hpp    | 50 ++++++++++---------
 3 files changed, 40 insertions(+), 35 deletions(-)

diff --git a/include/boost/math/special_functions/detail/round_fwd.hpp b/include/boost/math/special_functions/detail/round_fwd.hpp
index c58459e36d..679e01c4db 100644
--- a/include/boost/math/special_functions/detail/round_fwd.hpp
+++ b/include/boost/math/special_functions/detail/round_fwd.hpp
@@ -1,4 +1,5 @@
 // Copyright John Maddock 2008.
+// Copyright Matt Borland 2024
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -21,21 +22,21 @@ namespace boost
    { 
 
    template <class T, class Policy>
-   typename tools::promote_args<T>::type trunc(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type trunc(const T& v, const Policy& pol);
    template <class T>
-   typename tools::promote_args<T>::type trunc(const T& v);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type trunc(const T& v);
    template <class T, class Policy>
-   int itrunc(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED int itrunc(const T& v, const Policy& pol);
    template <class T>
-   int itrunc(const T& v);
+   BOOST_MATH_GPU_ENABLED int itrunc(const T& v);
    template <class T, class Policy>
-   long ltrunc(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED long ltrunc(const T& v, const Policy& pol);
    template <class T>
-   long ltrunc(const T& v);
+   BOOST_MATH_GPU_ENABLED long ltrunc(const T& v);
    template <class T, class Policy>
-   long long lltrunc(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED long long lltrunc(const T& v, const Policy& pol);
    template <class T>
-   long long lltrunc(const T& v);
+   BOOST_MATH_GPU_ENABLED long long lltrunc(const T& v);
    template <class T, class Policy>
    typename tools::promote_args<T>::type round(const T& v, const Policy& pol);
    template <class T>
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index b6fa2abf90..57775e6272 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -1198,7 +1198,7 @@ namespace boost
    inline T modf(const T& v, long long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <class T>\
-   inline long long lltrunc(const T& v){ using boost::math::lltrunc; return lltrunc(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v){ using boost::math::lltrunc; return lltrunc(v, Policy()); }\
    \
    template <class T>\
    inline long long llround(const T& v){ using boost::math::llround; return llround(v, Policy()); }\
@@ -1607,13 +1607,13 @@ template <class OutputIterator, class T>\
    inline long lround(const T& v){ using boost::math::lround; return lround(v, Policy()); }\
    \
    template <class T>\
-   inline T trunc(const T& v){ using boost::math::trunc; return trunc(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T trunc(const T& v){ using boost::math::trunc; return trunc(v, Policy()); }\
    \
    template <class T>\
-   inline int itrunc(const T& v){ using boost::math::itrunc; return itrunc(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline int itrunc(const T& v){ using boost::math::itrunc; return itrunc(v, Policy()); }\
    \
    template <class T>\
-   inline long ltrunc(const T& v){ using boost::math::ltrunc; return ltrunc(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline long ltrunc(const T& v){ using boost::math::ltrunc; return ltrunc(v, Policy()); }\
    \
    template <class T>\
    inline T modf(const T& v, T* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
diff --git a/include/boost/math/special_functions/trunc.hpp b/include/boost/math/special_functions/trunc.hpp
index a084de560b..4288225f16 100644
--- a/include/boost/math/special_functions/trunc.hpp
+++ b/include/boost/math/special_functions/trunc.hpp
@@ -27,7 +27,7 @@
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-inline tools::promote_args_t<T> trunc(const T& v, const Policy& pol, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> trunc(const T& v, const Policy& pol, const std::false_type&)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
@@ -39,20 +39,21 @@ inline tools::promote_args_t<T> trunc(const T& v, const Policy& pol, const std::
 }
 
 template <class T, class Policy>
-inline tools::promote_args_t<T> trunc(const T& v, const Policy&, const std::true_type&)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> trunc(const T& v, const Policy&, const std::true_type&)
 {
    return v;
 }
 
-}
+} // Namespace detail
 
 template <class T, class Policy>
-inline tools::promote_args_t<T> trunc(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> trunc(const T& v, const Policy& pol)
 {
    return detail::trunc(v, pol, std::integral_constant<bool, detail::is_integer_for_rounding<T>::value>());
 }
+
 template <class T>
-inline tools::promote_args_t<T> trunc(const T& v)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> trunc(const T& v)
 {
    return trunc(v, policies::policy<>());
 }
@@ -70,13 +71,13 @@ inline tools::promote_args_t<T> trunc(const T& v)
 // https://stackoverflow.com/questions/27442885/syntax-error-with-stdnumeric-limitsmax
 //
 template <class T, class Policy>
-inline int itrunc(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline int itrunc(const T& v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
    result_type r = boost::math::trunc(v, pol);
 
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -100,7 +101,7 @@ inline int itrunc(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<int>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<int>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -110,20 +111,21 @@ inline int itrunc(const T& v, const Policy& pol)
 
    return static_cast<int>(r);
 }
+
 template <class T>
-inline int itrunc(const T& v)
+BOOST_MATH_GPU_ENABLED inline int itrunc(const T& v)
 {
    return itrunc(v, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline long ltrunc(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline long ltrunc(const T& v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
    result_type r = boost::math::trunc(v, pol);
 
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -147,7 +149,7 @@ inline long ltrunc(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -157,20 +159,21 @@ inline long ltrunc(const T& v, const Policy& pol)
 
    return static_cast<long>(r);
 }
+
 template <class T>
-inline long ltrunc(const T& v)
+BOOST_MATH_GPU_ENABLED inline long ltrunc(const T& v)
 {
    return ltrunc(v, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline long long lltrunc(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
    result_type r = boost::math::trunc(v, pol);
 
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -194,7 +197,7 @@ inline long long lltrunc(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long long>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long long>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -204,21 +207,22 @@ inline long long lltrunc(const T& v, const Policy& pol)
 
    return static_cast<long long>(r);
 }
+
 template <class T>
-inline long long lltrunc(const T& v)
+BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v)
 {
    return lltrunc(v, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<std::is_constructible<int, T>::value, int>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<int, T>::value, int>::type
    iconvert(const T& v, const Policy&)
 {
    return static_cast<int>(v);
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<!std::is_constructible<int, T>::value, int>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<int, T>::value, int>::type
    iconvert(const T& v, const Policy& pol)
 {
    using boost::math::itrunc;
@@ -226,14 +230,14 @@ inline typename std::enable_if<!std::is_constructible<int, T>::value, int>::type
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<std::is_constructible<long, T>::value, long>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<long, T>::value, long>::type
    lconvert(const T& v, const Policy&)
 {
    return static_cast<long>(v);
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<!std::is_constructible<long, T>::value, long>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<long, T>::value, long>::type
    lconvert(const T& v, const Policy& pol)
 {
    using boost::math::ltrunc;
@@ -241,14 +245,14 @@ inline typename std::enable_if<!std::is_constructible<long, T>::value, long>::ty
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<std::is_constructible<long long, T>::value, long long>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<long long, T>::value, long long>::type
    llconvertert(const T& v, const Policy&)
 {
    return static_cast<long long>(v);
 }
 
 template <class T, class Policy>
-inline typename std::enable_if<!std::is_constructible<long long, T>::value, long long>::type
+BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<long long, T>::value, long long>::type
    llconvertert(const T& v, const Policy& pol)
 {
    using boost::math::lltrunc;

From 227e2adf43673f0e34e15507f6843ab5ae03da98 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:37:19 -0400
Subject: [PATCH 090/399] Add trunc cuda testing

---
 test/cuda_jamfile         |  2 +
 test/test_trunc_double.cu | 97 +++++++++++++++++++++++++++++++++++++++
 test/test_trunc_float.cu  | 97 +++++++++++++++++++++++++++++++++++++++
 3 files changed, 196 insertions(+)
 create mode 100644 test/test_trunc_double.cu
 create mode 100644 test/test_trunc_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 2494853a90..a350e037e8 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,3 +38,5 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_trunc_double.cu ;
+run test_trunc_float.cu ;
diff --git a/test/test_trunc_double.cu b/test/test_trunc_double.cu
new file mode 100644
index 0000000000..5a2d7b622b
--- /dev/null
+++ b/test/test_trunc_double.cu
@@ -0,0 +1,97 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::trunc(in[i]) + boost::math::itrunc(in[i]) + boost::math::ltrunc(in[i]) + boost::math::lltrunc(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::trunc(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_trunc_float.cu b/test/test_trunc_float.cu
new file mode 100644
index 0000000000..d6fe4d3525
--- /dev/null
+++ b/test/test_trunc_float.cu
@@ -0,0 +1,97 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::trunc(in[i]) + boost::math::itrunc(in[i]) + boost::math::ltrunc(in[i]) + boost::math::lltrunc(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::trunc(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 41b828e98531152f7e938ee1d289cc8591158eb6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:58:20 -0400
Subject: [PATCH 091/399] Add GPU support to round

---
 .../special_functions/detail/round_fwd.hpp    | 16 +++++-----
 .../boost/math/special_functions/math_fwd.hpp |  8 ++---
 .../boost/math/special_functions/round.hpp    | 30 +++++++++----------
 3 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/include/boost/math/special_functions/detail/round_fwd.hpp b/include/boost/math/special_functions/detail/round_fwd.hpp
index 679e01c4db..06674e48fd 100644
--- a/include/boost/math/special_functions/detail/round_fwd.hpp
+++ b/include/boost/math/special_functions/detail/round_fwd.hpp
@@ -38,21 +38,21 @@ namespace boost
    template <class T>
    BOOST_MATH_GPU_ENABLED long long lltrunc(const T& v);
    template <class T, class Policy>
-   typename tools::promote_args<T>::type round(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type round(const T& v, const Policy& pol);
    template <class T>
-   typename tools::promote_args<T>::type round(const T& v);
+   BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type round(const T& v);
    template <class T, class Policy>
-   int iround(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED int iround(const T& v, const Policy& pol);
    template <class T>
-   int iround(const T& v);
+   BOOST_MATH_GPU_ENABLED int iround(const T& v);
    template <class T, class Policy>
-   long lround(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED long lround(const T& v, const Policy& pol);
    template <class T>
-   long lround(const T& v);
+   BOOST_MATH_GPU_ENABLED long lround(const T& v);
    template <class T, class Policy>
-   long long llround(const T& v, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED long long llround(const T& v, const Policy& pol);
    template <class T>
-   long long llround(const T& v);
+   BOOST_MATH_GPU_ENABLED long long llround(const T& v);
    template <class T, class Policy>
    T modf(const T& v, T* ipart, const Policy& pol);
    template <class T>
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 57775e6272..81b07c43e7 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -1201,7 +1201,7 @@ namespace boost
    BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v){ using boost::math::lltrunc; return lltrunc(v, Policy()); }\
    \
    template <class T>\
-   inline long long llround(const T& v){ using boost::math::llround; return llround(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline long long llround(const T& v){ using boost::math::llround; return llround(v, Policy()); }\
 
 #  define BOOST_MATH_DETAIL_11_FUNC(Policy)\
    template <class T, class U, class V>\
@@ -1598,13 +1598,13 @@ template <class OutputIterator, class T>\
    inline boost::math::tools::promote_args_t<T> zeta(T s){ return boost::math::zeta(s, Policy()); }\
    \
    template <class T>\
-   inline T round(const T& v){ using boost::math::round; return round(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T round(const T& v){ using boost::math::round; return round(v, Policy()); }\
    \
    template <class T>\
-   inline int iround(const T& v){ using boost::math::iround; return iround(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline int iround(const T& v){ using boost::math::iround; return iround(v, Policy()); }\
    \
    template <class T>\
-   inline long lround(const T& v){ using boost::math::lround; return lround(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline long lround(const T& v){ using boost::math::lround; return lround(v, Policy()); }\
    \
    template <class T>\
    BOOST_MATH_GPU_ENABLED inline T trunc(const T& v){ using boost::math::trunc; return trunc(v, Policy()); }\
diff --git a/include/boost/math/special_functions/round.hpp b/include/boost/math/special_functions/round.hpp
index e74acba85b..3df0145b62 100644
--- a/include/boost/math/special_functions/round.hpp
+++ b/include/boost/math/special_functions/round.hpp
@@ -30,7 +30,7 @@ namespace boost{ namespace math{
 namespace detail{
 
 template <class T, class Policy>
-inline tools::promote_args_t<T> round(const T& v, const Policy& pol, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> round(const T& v, const Policy& pol, const std::false_type&)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
@@ -65,7 +65,7 @@ inline tools::promote_args_t<T> round(const T& v, const Policy& pol, const std::
    }
 }
 template <class T, class Policy>
-inline tools::promote_args_t<T> round(const T& v, const Policy&, const std::true_type&)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> round(const T& v, const Policy&, const std::true_type&)
 {
    return v;
 }
@@ -73,12 +73,12 @@ inline tools::promote_args_t<T> round(const T& v, const Policy&, const std::true
 } // namespace detail
 
 template <class T, class Policy>
-inline tools::promote_args_t<T> round(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> round(const T& v, const Policy& pol)
 {
    return detail::round(v, pol, std::integral_constant<bool, detail::is_integer_for_rounding<T>::value>());
 }
 template <class T>
-inline tools::promote_args_t<T> round(const T& v)
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> round(const T& v)
 {
    return round(v, policies::policy<>());
 }
@@ -103,7 +103,7 @@ inline int iround(const T& v, const Policy& pol)
 
    result_type r = boost::math::round(v, pol);
 
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -127,7 +127,7 @@ inline int iround(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<int>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<int>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -138,20 +138,20 @@ inline int iround(const T& v, const Policy& pol)
    return static_cast<int>(r);
 }
 template <class T>
-inline int iround(const T& v)
+BOOST_MATH_GPU_ENABLED inline int iround(const T& v)
 {
    return iround(v, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline long lround(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline long lround(const T& v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    using result_type = tools::promote_args_t<T>;
 
    result_type r = boost::math::round(v, pol);
    
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -175,7 +175,7 @@ inline long lround(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -186,20 +186,20 @@ inline long lround(const T& v, const Policy& pol)
    return static_cast<long>(r);
 }
 template <class T>
-inline long lround(const T& v)
+BOOST_MATH_GPU_ENABLED inline long lround(const T& v)
 {
    return lround(v, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline long long llround(const T& v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline long long llround(const T& v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    using result_type = boost::math::tools::promote_args_t<T>;
 
    result_type r = boost::math::round(v, pol);
 
-   #ifdef BOOST_MATH_HAS_CONSTEXPR_LDEXP
+   #if defined(BOOST_MATH_HAS_CONSTEXPR_LDEXP) && !defined(BOOST_MATH_HAS_GPU_SUPPORT)
    if constexpr (std::is_arithmetic_v<result_type>
                  #ifdef BOOST_MATH_FLOAT128_TYPE
                  && !std::is_same_v<BOOST_MATH_FLOAT128_TYPE, result_type>
@@ -223,7 +223,7 @@ inline long long llround(const T& v, const Policy& pol)
       }
    }
    #else
-   static const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long long>::digits);
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const result_type max_val = ldexp(static_cast<result_type>(1), std::numeric_limits<long long>::digits);
 
    if (r >= max_val || r < -max_val)
    {
@@ -234,7 +234,7 @@ inline long long llround(const T& v, const Policy& pol)
    return static_cast<long long>(r);
 }
 template <class T>
-inline long long llround(const T& v)
+BOOST_MATH_GPU_ENABLED inline long long llround(const T& v)
 {
    return llround(v, policies::policy<>());
 }

From 54e76b6336951401c4c801cc7b60020ddf5c5c3a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 13:58:31 -0400
Subject: [PATCH 092/399] Add CUDA round testing

---
 test/cuda_jamfile         |  2 +
 test/test_round_double.cu | 98 +++++++++++++++++++++++++++++++++++++++
 test/test_round_float.cu  | 98 +++++++++++++++++++++++++++++++++++++++
 3 files changed, 198 insertions(+)
 create mode 100644 test/test_round_double.cu
 create mode 100644 test/test_round_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index a350e037e8..098721120c 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,5 +38,7 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_round_double.cu ;
+run test_round_float.cu ;
 run test_trunc_double.cu ;
 run test_trunc_float.cu ;
diff --git a/test/test_round_double.cu b/test/test_round_double.cu
new file mode 100644
index 0000000000..3dae4342d2
--- /dev/null
+++ b/test/test_round_double.cu
@@ -0,0 +1,98 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/round.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::round(in[i]) + boost::math::iround(in[i]) + boost::math::lround(in[i]) + boost::math::llround(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::round(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
+
diff --git a/test/test_round_float.cu b/test/test_round_float.cu
new file mode 100644
index 0000000000..45dd14c03a
--- /dev/null
+++ b/test/test_round_float.cu
@@ -0,0 +1,98 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/round.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::round(in[i]) + boost::math::iround(in[i]) + boost::math::lround(in[i]) + boost::math::llround(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::round(h_A[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
+

From 4036b23a5e9c8bf80571af8b8a23d9b75bd25b8c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 14:11:18 -0400
Subject: [PATCH 093/399] Add round testing

---
 test/sycl_jamfile   | 1 +
 test/test_round.cpp | 7 ++++++-
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 9656ee7a70..3993e9ef60 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -17,3 +17,4 @@ run test_cauchy.cpp ;
 run test_beta_simple.cpp ;
 run test_cbrt.cpp ;
 run test_sign.cpp ;
+run test_round.cpp ;
diff --git a/test/test_round.cpp b/test/test_round.cpp
index 95ff4d234e..e363efd565 100644
--- a/test/test_round.cpp
+++ b/test/test_round.cpp
@@ -3,12 +3,15 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp>
+#endif
 
 #include <boost/math/concepts/real_concept.hpp>
 #define BOOST_TEST_MAIN
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/test/unit_test.hpp>
-#include <boost/math/tools/test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/round.hpp>
 #include <boost/math/special_functions/next.hpp>
@@ -222,6 +225,7 @@ void test_round(T, const char* name )
    //
    // Finish off by testing the error handlers:
    //
+   #ifndef BOOST_MATH_NO_EXCEPTIONS
    BOOST_MATH_CHECK_THROW(iround(static_cast<T>(1e20)), boost::math::rounding_error);
    BOOST_MATH_CHECK_THROW(iround(static_cast<T>(-1e20)), boost::math::rounding_error);
    BOOST_MATH_CHECK_THROW(lround(static_cast<T>(1e20)), boost::math::rounding_error);
@@ -314,6 +318,7 @@ void test_round(T, const char* name )
       BOOST_MATH_CHECK_THROW(llround(static_cast<T>((std::numeric_limits<boost::long_long_type>::min)()) - 1), boost::math::rounding_error);
    }
 #endif
+   #endif
    //
    // try non-throwing error handlers:
    //

From 75170902caa60039703c2716d6f37f8759a67265 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 14:11:38 -0400
Subject: [PATCH 094/399] Improve return value of ignore error policy

---
 .../boost/math/policies/error_handling.hpp    | 45 ++++++++++++++++++-
 1 file changed, 44 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 985bdff22b..36ec8d9d6d 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -601,7 +601,50 @@ BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(
    #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
    #else
-   return val > 0 ? static_cast<TargetType>(1) : -static_cast<TargetType>(1);
+   BOOST_IF_CONSTEXPR (std::is_same<TargetType, short>::value)
+   {
+      return val > 0 ? SHRT_MAX : SHRT_MIN;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, int>::value)
+   {
+      return val > 0 ? INT_MAX : INT_MIN;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, long>::value)
+   {
+      return val > 0 ? LONG_MAX : LONG_MIN;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, long long>::value)
+   {
+      return val > 0 ? LLONG_MAX : LLONG_MIN;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned short>::value)
+   {
+      return val > 0 ? USHRT_MAX : static_cast<unsigned short>(0U);
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned>::value)
+   {
+      return val > 0 ? UINT_MAX : 0U;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned long>::value)
+   {
+      return val > 0 ? ULONG_MAX : 0UL;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned long long>::value)
+   {
+      return val > 0 ? ULLONG_MAX : 0ULL;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, float>::value)
+   {
+      return val > 0 ? FLT_MAX : -FLT_MAX;
+   }
+   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, double>::value)
+   {
+      return val > 0 ? DBL_MAX : -DBL_MAX;
+   }
+   else
+   {
+      return val > 0 ? static_cast<TargetType>(-1) : static_cast<TargetType>(1);
+   }
    #endif
 }
 

From 8281c366d19258c471c96c728fc654481abd44d3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 15:05:34 -0400
Subject: [PATCH 095/399] Mark modf for GPU usage

---
 .../math/special_functions/detail/round_fwd.hpp | 16 ++++++++--------
 .../boost/math/special_functions/math_fwd.hpp   |  8 ++++----
 include/boost/math/special_functions/modf.hpp   | 17 +++++++++--------
 3 files changed, 21 insertions(+), 20 deletions(-)

diff --git a/include/boost/math/special_functions/detail/round_fwd.hpp b/include/boost/math/special_functions/detail/round_fwd.hpp
index 06674e48fd..7d69f8b9c5 100644
--- a/include/boost/math/special_functions/detail/round_fwd.hpp
+++ b/include/boost/math/special_functions/detail/round_fwd.hpp
@@ -54,21 +54,21 @@ namespace boost
    template <class T>
    BOOST_MATH_GPU_ENABLED long long llround(const T& v);
    template <class T, class Policy>
-   T modf(const T& v, T* ipart, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, T* ipart, const Policy& pol);
    template <class T>
-   T modf(const T& v, T* ipart);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, T* ipart);
    template <class T, class Policy>
-   T modf(const T& v, int* ipart, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, int* ipart, const Policy& pol);
    template <class T>
-   T modf(const T& v, int* ipart);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, int* ipart);
    template <class T, class Policy>
-   T modf(const T& v, long* ipart, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, long* ipart, const Policy& pol);
    template <class T>
-   T modf(const T& v, long* ipart);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, long* ipart);
    template <class T, class Policy>
-   T modf(const T& v, long long* ipart, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, long long* ipart, const Policy& pol);
    template <class T>
-   T modf(const T& v, long long* ipart);
+   BOOST_MATH_GPU_ENABLED T modf(const T& v, long long* ipart);
    }
 }
 
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 81b07c43e7..7122d2670b 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -1195,7 +1195,7 @@ namespace boost
 #define BOOST_MATH_DETAIL_LL_FUNC(Policy)\
    \
    template <class T>\
-   inline T modf(const T& v, long long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <class T>\
    BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v){ using boost::math::lltrunc; return lltrunc(v, Policy()); }\
@@ -1616,13 +1616,13 @@ template <class OutputIterator, class T>\
    BOOST_MATH_GPU_ENABLED inline long ltrunc(const T& v){ using boost::math::ltrunc; return ltrunc(v, Policy()); }\
    \
    template <class T>\
-   inline T modf(const T& v, T* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T modf(const T& v, T* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <class T>\
-   inline T modf(const T& v, int* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T modf(const T& v, int* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <class T>\
-   inline T modf(const T& v, long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <int N, class T>\
    inline boost::math::tools::promote_args_t<T> pow(T v){ return boost::math::pow<N>(v, Policy()); }\
diff --git a/include/boost/math/special_functions/modf.hpp b/include/boost/math/special_functions/modf.hpp
index 75e6be9f46..e08945dca5 100644
--- a/include/boost/math/special_functions/modf.hpp
+++ b/include/boost/math/special_functions/modf.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2007.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -17,49 +18,49 @@
 namespace boost{ namespace math{
 
 template <class T, class Policy>
-inline T modf(const T& v, T* ipart, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, T* ipart, const Policy& pol)
 {
    *ipart = trunc(v, pol);
    return v - *ipart;
 }
 template <class T>
-inline T modf(const T& v, T* ipart)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, T* ipart)
 {
    return modf(v, ipart, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline T modf(const T& v, int* ipart, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, int* ipart, const Policy& pol)
 {
    *ipart = itrunc(v, pol);
    return v - *ipart;
 }
 template <class T>
-inline T modf(const T& v, int* ipart)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, int* ipart)
 {
    return modf(v, ipart, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline T modf(const T& v, long* ipart, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long* ipart, const Policy& pol)
 {
    *ipart = ltrunc(v, pol);
    return v - *ipart;
 }
 template <class T>
-inline T modf(const T& v, long* ipart)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long* ipart)
 {
    return modf(v, ipart, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline T modf(const T& v, long long* ipart, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long long* ipart, const Policy& pol)
 {
    *ipart = lltrunc(v, pol);
    return v - *ipart;
 }
 template <class T>
-inline T modf(const T& v, long long* ipart)
+BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long long* ipart)
 {
    return modf(v, ipart, policies::policy<>());
 }

From 2b3023856bedb944cac7500616c3b0f868784735 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 15:05:43 -0400
Subject: [PATCH 096/399] Add modf cuda testing

---
 test/cuda_jamfile        |   2 +
 test/test_modf_double.cu | 105 +++++++++++++++++++++++++++++++++++++++
 test/test_modf_float.cu  | 105 +++++++++++++++++++++++++++++++++++++++
 3 files changed, 212 insertions(+)
 create mode 100644 test/test_modf_double.cu
 create mode 100644 test/test_modf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 098721120c..834883b2e6 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,6 +38,8 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_modf_double.cu ;
+run test_modf_float.cu ;
 run test_round_double.cu ;
 run test_round_float.cu ;
 run test_trunc_double.cu ;
diff --git a/test/test_modf_double.cu b/test/test_modf_double.cu
new file mode 100644
index 0000000000..06e65c1063
--- /dev/null
+++ b/test/test_modf_double.cu
@@ -0,0 +1,105 @@
+
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/modf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    float_type fract;
+    int i_part;
+    long l_part;
+    long long ll_part;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::modf(in[i], &fract) + boost::math::modf(in[i], &i_part) + boost::math::modf(in[i], &l_part) + boost::math::modf(in[i], &ll_part);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type fract;
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::modf(h_A[i], &fract));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
+
diff --git a/test/test_modf_float.cu b/test/test_modf_float.cu
new file mode 100644
index 0000000000..06e65c1063
--- /dev/null
+++ b/test/test_modf_float.cu
@@ -0,0 +1,105 @@
+
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/modf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    float_type fract;
+    int i_part;
+    long l_part;
+    long long ll_part;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::modf(in[i], &fract) + boost::math::modf(in[i], &i_part) + boost::math::modf(in[i], &l_part) + boost::math::modf(in[i], &ll_part);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector addition of " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> h_A(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> h_C(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        h_A[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(h_A.get(), h_C.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type fract;
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(4 * boost::math::modf(h_A[i], &fract));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(h_C[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
+

From 5fdbcbb86360cc6f72c3f051eba3d1e8473ea17f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 16:14:42 -0400
Subject: [PATCH 097/399] Add markers for GPU expm1

---
 include/boost/math/special_functions/expm1.hpp    | 7 ++++---
 include/boost/math/special_functions/math_fwd.hpp | 6 +++---
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/special_functions/expm1.hpp b/include/boost/math/special_functions/expm1.hpp
index eec6356031..a5af573cd2 100644
--- a/include/boost/math/special_functions/expm1.hpp
+++ b/include/boost/math/special_functions/expm1.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -294,18 +295,18 @@ inline typename tools::promote_args<T>::type expm1(T x, const Policy& /* pol */)
 
 #if defined(BOOST_HAS_EXPM1) && !(defined(__osf__) && defined(__DECCXX_VER))
 #  ifdef BOOST_MATH_USE_C99
-inline float expm1(float x, const policies::policy<>&){ return ::expm1f(x); }
+BOOST_MATH_GPU_ENABLED inline float expm1(float x, const policies::policy<>&){ return ::expm1f(x); }
 #     ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
 inline long double expm1(long double x, const policies::policy<>&){ return ::expm1l(x); }
 #     endif
 #  else
 inline float expm1(float x, const policies::policy<>&){ return static_cast<float>(::expm1(x)); }
 #  endif
-inline double expm1(double x, const policies::policy<>&){ return ::expm1(x); }
+BOOST_MATH_GPU_ENABLED inline double expm1(double x, const policies::policy<>&){ return ::expm1(x); }
 #endif
 
 template <class T>
-inline typename tools::promote_args<T>::type expm1(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type expm1(T x)
 {
    return expm1(x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 7122d2670b..e2ac58e850 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -584,10 +584,10 @@ namespace boost
 
    // Exp (x) minus 1 functions.
    template <class T>
-   tools::promote_args_t<T> expm1(T);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> expm1(T);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> expm1(T, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> expm1(T, const Policy&);
 
    // Power - 1
    template <class T1, class T2>
@@ -1477,7 +1477,7 @@ namespace boost
    inline boost::math::tools::promote_args_t<T> log1pmx(T x){ return boost::math::log1pmx(x, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> expm1(T x){ return boost::math::expm1(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> expm1(T x){ return boost::math::expm1(x, Policy()); }\
 \
    template <class T1, class T2>\
    inline boost::math::tools::promote_args_t<T1, T2> \

From 202b29016bcd09a8d8fadac358158d1624dccc15 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 16:14:51 -0400
Subject: [PATCH 098/399] Add expm1 CUDA testing

---
 test/cuda_jamfile         |   2 +
 test/test_expm1_double.cu | 100 ++++++++++++++++++++++++++++++++++++++
 test/test_expm1_float.cu  | 100 ++++++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_expm1_double.cu
 create mode 100644 test/test_expm1_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 834883b2e6..1adeeed3af 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,6 +38,8 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_expm1_double.cu ;
+run test_expm1_float.cu ;
 run test_modf_double.cu ;
 run test_modf_float.cu ;
 run test_round_double.cu ;
diff --git a/test/test_expm1_double.cu b/test/test_expm1_double.cu
new file mode 100644
index 0000000000..cfed7d840d
--- /dev/null
+++ b/test/test_expm1_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::expm1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::expm1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_expm1_float.cu b/test/test_expm1_float.cu
new file mode 100644
index 0000000000..3d439b8872
--- /dev/null
+++ b/test/test_expm1_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::expm1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::expm1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 80a766abd784a63c01a81be7001b3df998bef544 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 24 Jul 2024 16:21:26 -0400
Subject: [PATCH 099/399] Add trivial expm1 test for SYCL functionality

---
 test/sycl_jamfile          |  1 +
 test/test_expm1_simple.cpp | 32 ++++++++++++++++++++++++++++++++
 2 files changed, 33 insertions(+)
 create mode 100644 test/test_expm1_simple.cpp

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 3993e9ef60..e8bd12f8ca 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -18,3 +18,4 @@ run test_beta_simple.cpp ;
 run test_cbrt.cpp ;
 run test_sign.cpp ;
 run test_round.cpp ;
+run test_expm1_simple.cpp;
diff --git a/test/test_expm1_simple.cpp b/test/test_expm1_simple.cpp
new file mode 100644
index 0000000000..00513ea409
--- /dev/null
+++ b/test/test_expm1_simple.cpp
@@ -0,0 +1,32 @@
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <random>
+#include <cmath>
+#include <boost/math/special_functions/expm1.hpp>
+#include "math_unit_test.hpp"
+
+constexpr int N = 50000;
+
+template <typename T>
+void test()
+{
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<T> dist(0, 0.01);
+
+    for (int n = 0; n < N; ++n)
+    {
+        const T value (dist(rng));
+        CHECK_ULP_CLOSE(std::expm1(value), boost::math::expm1(value), 10);
+    }
+}
+
+int main()
+{
+    test<float>();
+    test<double>();
+
+    return boost::math::test::report_errors();
+}

From 7b0caf58c9df62e6696263bfb8d19a20ec1a5f0a Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Thu, 25 Jul 2024 13:21:00 +0100
Subject: [PATCH 100/399] Hook up testing of mapairy/holtsmark/saspoint5
 distributions.

---
 .../boost/math/distributions/holtsmark.hpp    |  5 ++--
 include/boost/math/distributions/mapairy.hpp  |  3 ++-
 test/Jamfile.v2                               |  6 +++++
 .../compile_test/dist_holtsmark_incl_test.cpp | 26 +++++++++++++++++++
 test/compile_test/dist_mapairy_incl_test.cpp  | 26 +++++++++++++++++++
 .../compile_test/dist_saspoint5_incl_test.cpp | 26 +++++++++++++++++++
 test/test_holtsmark.cpp                       | 14 +++++-----
 test/test_mapairy.cpp                         | 14 +++++-----
 test/test_saspoint5.cpp                       | 14 +++++-----
 9 files changed, 110 insertions(+), 24 deletions(-)
 create mode 100644 test/compile_test/dist_holtsmark_incl_test.cpp
 create mode 100644 test/compile_test/dist_mapairy_incl_test.cpp
 create mode 100644 test/compile_test/dist_saspoint5_incl_test.cpp

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index d53a2ac701..a6613a81ba 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -18,6 +18,7 @@
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
+#include <boost/math/special_functions/cbrt.hpp>
 #include <utility>
 #include <cmath>
 
@@ -687,7 +688,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 1) {
-        RealType t = x - 0.5;
+        RealType t = x - 0.5f;
 
         // Rational Approximation
         // Maximum Relative Error: 1.6265e-18
@@ -884,7 +885,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+        RealType t = static_cast<RealType>(isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
 
         // Rational Approximation
         // Maximum Relative Error: 4.2897e-18
diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index 481db570f6..a67e5310aa 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -18,6 +18,7 @@
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
+#include <boost/math/special_functions/cbrt.hpp>
 #include <utility>
 #include <cmath>
 
@@ -1287,7 +1288,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+        RealType t = static_cast<RealType>(isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
 
         // Rational Approximation
         // Maximum Relative Error: 6.2709e-17
diff --git a/test/Jamfile.v2 b/test/Jamfile.v2
index 67fb25163c..85ddf38f9b 100644
--- a/test/Jamfile.v2
+++ b/test/Jamfile.v2
@@ -558,6 +558,9 @@ test-suite special_fun :
 test-suite distribution_tests :
    [ run test_arcsine.cpp pch ../../test/build//boost_unit_test_framework  ]
    [ run test_landau.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
+   [ run test_saspoint5.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
+   [ run test_holtsmark.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
+   [ run test_mapairy.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
    [ run test_bernoulli.cpp ../../test/build//boost_unit_test_framework  ]
    [ run test_beta_dist.cpp ../../test/build//boost_unit_test_framework  ]
    [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
@@ -1382,6 +1385,9 @@ test-suite concepts :
    [ run  compile_test/dist_hyperexponential_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_hypergeo_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_landau_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
+   [ run  compile_test/dist_mapairy_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
+   [ run  compile_test/dist_holtsmark_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
+   [ run  compile_test/dist_saspoint5_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_laplace_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_logistic_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
    [ run  compile_test/dist_lognormal_incl_test.cpp compile_test_main : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ]  ]
diff --git a/test/compile_test/dist_holtsmark_incl_test.cpp b/test/compile_test/dist_holtsmark_incl_test.cpp
new file mode 100644
index 0000000000..f90bbb9f07
--- /dev/null
+++ b/test/compile_test/dist_holtsmark_incl_test.cpp
@@ -0,0 +1,26 @@
+//  Copyright John Maddock 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// Basic sanity check that header <boost/math/distributions/landau.hpp>
+// #includes all the files that it needs to.
+//
+#define BOOST_MATH_ASSERT_UNDEFINED_POLICY false
+#include <boost/math/distributions/holtsmark.hpp>
+//
+// Note this header includes no other headers, this is
+// important if this test is to be meaningful:
+//
+#include "test_compile_result.hpp"
+
+void compile_and_link_test()
+{
+   TEST_DIST_FUNC(holtsmark)
+}
+
+template class boost::math::holtsmark_distribution<float, boost::math::policies::policy<> >;
+template class boost::math::holtsmark_distribution<double, boost::math::policies::policy<> >;
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+template class boost::math::holtsmark_distribution<long double, boost::math::policies::policy<> >;
+#endif
diff --git a/test/compile_test/dist_mapairy_incl_test.cpp b/test/compile_test/dist_mapairy_incl_test.cpp
new file mode 100644
index 0000000000..7b953711dd
--- /dev/null
+++ b/test/compile_test/dist_mapairy_incl_test.cpp
@@ -0,0 +1,26 @@
+//  Copyright John Maddock 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// Basic sanity check that header <boost/math/distributions/landau.hpp>
+// #includes all the files that it needs to.
+//
+#define BOOST_MATH_ASSERT_UNDEFINED_POLICY false
+#include <boost/math/distributions/mapairy.hpp>
+//
+// Note this header includes no other headers, this is
+// important if this test is to be meaningful:
+//
+#include "test_compile_result.hpp"
+
+void compile_and_link_test()
+{
+   TEST_DIST_FUNC(mapairy)
+}
+
+template class boost::math::mapairy_distribution<float, boost::math::policies::policy<> >;
+template class boost::math::mapairy_distribution<double, boost::math::policies::policy<> >;
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+template class boost::math::mapairy_distribution<long double, boost::math::policies::policy<> >;
+#endif
diff --git a/test/compile_test/dist_saspoint5_incl_test.cpp b/test/compile_test/dist_saspoint5_incl_test.cpp
new file mode 100644
index 0000000000..e48d3691df
--- /dev/null
+++ b/test/compile_test/dist_saspoint5_incl_test.cpp
@@ -0,0 +1,26 @@
+//  Copyright John Maddock 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+// Basic sanity check that header <boost/math/distributions/landau.hpp>
+// #includes all the files that it needs to.
+//
+#define BOOST_MATH_ASSERT_UNDEFINED_POLICY false
+#include <boost/math/distributions/saspoint5.hpp>
+//
+// Note this header includes no other headers, this is
+// important if this test is to be meaningful:
+//
+#include "test_compile_result.hpp"
+
+void compile_and_link_test()
+{
+   TEST_DIST_FUNC(saspoint5)
+}
+
+template class boost::math::saspoint5_distribution<float, boost::math::policies::policy<> >;
+template class boost::math::saspoint5_distribution<double, boost::math::policies::policy<> >;
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+template class boost::math::saspoint5_distribution<long double, boost::math::policies::policy<> >;
+#endif
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index 03146feb63..35307ef6af 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -776,7 +776,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_pdf_std64)
 {
     do_test_holtsmark_pdf<std::float64_t, 53>();
 }
@@ -793,7 +793,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_cdf_std64)
 {
     do_test_holtsmark_cdf<std::float64_t, 53>();
 }
@@ -810,7 +810,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_ccdf_std64)
 {
     do_test_holtsmark_ccdf<std::float64_t, 53>();
 }
@@ -827,7 +827,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_std64)
 {
     do_test_holtsmark_quantile_nearzero<std::float64_t, 53>();
 }
@@ -844,7 +844,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_std64)
 {
     do_test_holtsmark_quantile_lower<std::float64_t, 53>();
 }
@@ -861,7 +861,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_std64)
 {
     do_test_holtsmark_quantile_upper<std::float64_t, 53>();
 }
@@ -878,7 +878,7 @@ BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
+BOOST_AUTO_TEST_CASE(holtsmark_locscale_std64)
 {
     do_test_holtsmark_locscale_param<std::float64_t, 53>();
 }
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index fac7fd01c6..2dcd1cfdaf 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -803,7 +803,7 @@ BOOST_AUTO_TEST_CASE(mapairy_pdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_pdf_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_pdf_std64)
 {
     do_test_mapairy_pdf<std::float64_t, 53>();
 }
@@ -820,7 +820,7 @@ BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_cdf_std64)
 {
     do_test_mapairy_cdf<std::float64_t, 53>();
 }
@@ -837,7 +837,7 @@ BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_ccdf_std64)
 {
     do_test_mapairy_ccdf<std::float64_t, 53>();
 }
@@ -854,7 +854,7 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_std64)
 {
     do_test_mapairy_quantile_nearzero<std::float64_t, 53>();
 }
@@ -871,7 +871,7 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_std64)
 {
     do_test_mapairy_quantile_lower<std::float64_t, 53>();
 }
@@ -888,7 +888,7 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_std64)
 {
     do_test_mapairy_quantile_upper<std::float64_t, 53>();
 }
@@ -905,7 +905,7 @@ BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
+BOOST_AUTO_TEST_CASE(mapairy_locscale_std64)
 {
     do_test_mapairy_locscale_param<std::float64_t, 53>();
 }
diff --git a/test/test_saspoint5.cpp b/test/test_saspoint5.cpp
index 281cad8e25..c734ecde7e 100644
--- a/test/test_saspoint5.cpp
+++ b/test/test_saspoint5.cpp
@@ -854,7 +854,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_pdf_std64)
 {
     do_test_saspoint5_pdf<std::float64_t, 53>();
 }
@@ -871,7 +871,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_cdf_std64)
 {
     do_test_saspoint5_cdf<std::float64_t, 53>();
 }
@@ -888,7 +888,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_ccdf_std64)
 {
     do_test_saspoint5_ccdf<std::float64_t, 53>();
 }
@@ -905,7 +905,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_std64)
 {
     do_test_saspoint5_quantile_nearzero<std::float64_t, 53>();
 }
@@ -922,7 +922,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_std64)
 {
     do_test_saspoint5_quantile_lower<std::float64_t, 53>();
 }
@@ -939,7 +939,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_std64)
 {
     do_test_saspoint5_quantile_upper<std::float64_t, 53>();
 }
@@ -956,7 +956,7 @@ BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
 }
 
 #ifdef __STDCPP_FLOAT64_T__
-BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
+BOOST_AUTO_TEST_CASE(saspoint5_locscale_std64)
 {
     do_test_saspoint5_locscale_param<std::float64_t, 53>();
 }

From 493626c9a30098f4e6dfa344357c7034ae3cf95e Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Thu, 25 Jul 2024 19:03:50 +0100
Subject: [PATCH 101/399] Integrate concept checks for
 mapairy/holtsmark/saspoint5.

---
 include/boost/math/distributions.hpp           |  3 +++
 include/boost/math/distributions/fwd.hpp       | 12 ++++++++++++
 include/boost/math/distributions/holtsmark.hpp |  8 ++++----
 include/boost/math/distributions/mapairy.hpp   |  8 ++++----
 test/compile_test/instantiate.hpp              |  9 +++++++++
 5 files changed, 32 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/distributions.hpp b/include/boost/math/distributions.hpp
index e7789319b4..0834db870a 100644
--- a/include/boost/math/distributions.hpp
+++ b/include/boost/math/distributions.hpp
@@ -24,6 +24,7 @@
 #include <boost/math/distributions/fisher_f.hpp>
 #include <boost/math/distributions/gamma.hpp>
 #include <boost/math/distributions/geometric.hpp>
+#include <boost/math/distributions/holtsmark.hpp>
 #include <boost/math/distributions/hyperexponential.hpp>
 #include <boost/math/distributions/hypergeometric.hpp>
 #include <boost/math/distributions/inverse_chi_squared.hpp>
@@ -34,6 +35,7 @@
 #include <boost/math/distributions/laplace.hpp>
 #include <boost/math/distributions/logistic.hpp>
 #include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/distributions/mapairy.hpp>
 #include <boost/math/distributions/negative_binomial.hpp>
 #include <boost/math/distributions/non_central_chi_squared.hpp>
 #include <boost/math/distributions/non_central_beta.hpp>
@@ -43,6 +45,7 @@
 #include <boost/math/distributions/pareto.hpp>
 #include <boost/math/distributions/poisson.hpp>
 #include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/distributions/saspoint5.hpp>
 #include <boost/math/distributions/skew_normal.hpp>
 #include <boost/math/distributions/students_t.hpp>
 #include <boost/math/distributions/triangular.hpp>
diff --git a/include/boost/math/distributions/fwd.hpp b/include/boost/math/distributions/fwd.hpp
index 72ac24335a..ccb3c0cd1b 100644
--- a/include/boost/math/distributions/fwd.hpp
+++ b/include/boost/math/distributions/fwd.hpp
@@ -69,6 +69,15 @@ class kolmogorov_smirnov_distribution;
 template <class RealType, class Policy>
 class landau_distribution;
 
+template <class RealType, class Policy>
+class mapairy_distribution;
+
+template <class RealType, class Policy>
+class holtsmark_distribution;
+
+template <class RealType, class Policy>
+class saspoint5_distribution;
+
 template <class RealType, class Policy>
 class laplace_distribution;
 
@@ -140,6 +149,9 @@ class weibull_distribution;
    typedef boost::math::inverse_gaussian_distribution<Type, Policy> inverse_gaussian;\
    typedef boost::math::inverse_gamma_distribution<Type, Policy> inverse_gamma;\
    typedef boost::math::landau_distribution<Type, Policy> landau;\
+   typedef boost::math::mapairy_distribution<Type, Policy> mapairy;\
+   typedef boost::math::holtsmark_distribution<Type, Policy> holtsmark;\
+   typedef boost::math::saspoint5_distribution<Type, Policy> saspoint5;\
    typedef boost::math::laplace_distribution<Type, Policy> laplace;\
    typedef boost::math::logistic_distribution<Type, Policy> logistic;\
    typedef boost::math::lognormal_distribution<Type, Policy> lognormal;\
diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index a6613a81ba..86240e4007 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -885,7 +885,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = static_cast<RealType>(isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
+        RealType t = static_cast<RealType>((boost::math::isnormal)(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
 
         // Rational Approximation
         // Maximum Relative Error: 4.2897e-18
@@ -1253,7 +1253,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+        RealType t = (boost::math::isnormal)(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
 
         // Rational Approximation
         // Maximum Relative Error: 5.4677e-35
@@ -1597,7 +1597,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         RealType p_square = p * p;
 
-        if (isnormal(p_square)) {
+        if ((boost::math::isnormal)(p_square)) {
             result = 1 / (cbrt(p_square) * c);
         }
         else if (p > 0) {
@@ -2181,7 +2181,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         RealType p_square = p * p;
 
-        if (isnormal(p_square)) {
+        if ((boost::math::isnormal)(p_square)) {
             result = 1 / (cbrt(p_square) * c);
         }
         else if (p > 0) {
diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index a67e5310aa..53517a641e 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -1288,7 +1288,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = static_cast<RealType>(isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
+        RealType t = static_cast<RealType>((boost::math::isnormal)(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3));
 
         // Rational Approximation
         // Maximum Relative Error: 6.2709e-17
@@ -1598,7 +1598,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
     }
     else {
         RealType x_cube = x * x * x;
-        RealType t = isnormal(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
+        RealType t = (boost::math::isnormal)(x_cube) ? 1 / sqrt(x_cube) : 1 / pow(sqrt(x), 3);
 
         // Rational Approximation
         // Maximum Relative Error: 3.5865e-37
@@ -3373,7 +3373,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
     else {
         RealType p_square = p * p;
 
-        if (isnormal(p_square)) {
+        if ((boost::math::isnormal)(p_square)) {
             result = 1 / cbrt(p_square * constants::two_pi<RealType>());
         }
         else if (p > 0) {
@@ -3764,7 +3764,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
     else {
         RealType p_square = p * p;
 
-        if (isnormal(p_square)) {
+        if ((boost::math::isnormal)(p_square)) {
             result = 1 / cbrt(p_square * constants::two_pi<RealType>());
         }
         else if (p > 0) {
diff --git a/test/compile_test/instantiate.hpp b/test/compile_test/instantiate.hpp
index 7b78e25be8..85c85f785d 100644
--- a/test/compile_test/instantiate.hpp
+++ b/test/compile_test/instantiate.hpp
@@ -86,6 +86,15 @@ void instantiate_for_fixed_precision_only(RealType, const std::true_type&)
    function_requires<DistributionConcept<landau_distribution<RealType> > >();
    function_requires<DistributionConcept<landau_distribution<RealType, test_policy> > >();
    function_requires<DistributionConcept<dist_test::landau > >();
+   function_requires<DistributionConcept<mapairy_distribution<RealType> > >();
+   function_requires<DistributionConcept<mapairy_distribution<RealType, test_policy> > >();
+   function_requires<DistributionConcept<dist_test::mapairy > >();
+   function_requires<DistributionConcept<holtsmark_distribution<RealType> > >();
+   function_requires<DistributionConcept<holtsmark_distribution<RealType, test_policy> > >();
+   function_requires<DistributionConcept<dist_test::holtsmark> >();
+   function_requires<DistributionConcept<saspoint5_distribution<RealType> > >();
+   function_requires<DistributionConcept<saspoint5_distribution<RealType, test_policy> > >();
+   function_requires<DistributionConcept<dist_test::saspoint5> >();
 #endif
 #endif
 }

From 1e7958da380b00186194f1c1d7c888d60029b92f Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Thu, 25 Jul 2024 19:15:39 +0100
Subject: [PATCH 102/399] Add holtsmark/mapairy/saspoint5 to doc build.

---
 doc/distributions/dist_reference.qbk | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/doc/distributions/dist_reference.qbk b/doc/distributions/dist_reference.qbk
index 75e4d5759c..2dd06bcb8b 100644
--- a/doc/distributions/dist_reference.qbk
+++ b/doc/distributions/dist_reference.qbk
@@ -16,6 +16,7 @@
 [include fisher.qbk]
 [include gamma.qbk]
 [include geometric.qbk]
+[include holtsmark.qbk]
 [include hyperexponential.qbk]
 [include hypergeometric.qbk]
 [include inverse_chi_squared.qbk]
@@ -26,6 +27,7 @@
 [include laplace.qbk]
 [include logistic.qbk]
 [include lognormal.qbk]
+[include mapairy.qbk]
 [include negative_binomial.qbk]
 [include nc_beta.qbk]
 [include nc_chi_squared.qbk]
@@ -35,6 +37,7 @@
 [include pareto.qbk]
 [include poisson.qbk]
 [include rayleigh.qbk]
+[include saspoint5.qbk]
 [include skew_normal.qbk]
 [include students_t.qbk]
 [include triangular.qbk]

From fda6d99f8175418008c1654f6fce0bb0617c7d42 Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Fri, 26 Jul 2024 12:14:29 +0100
Subject: [PATCH 103/399] Mark up tables for coverage. Otherwise all the false
 positives take our coverage rates waaaaay down low.

---
 .../boost/math/distributions/holtsmark.hpp    |  90 ++++++---
 include/boost/math/distributions/landau.hpp   | 174 ++++++++++++------
 include/boost/math/distributions/mapairy.hpp  | 165 +++++++++++------
 .../boost/math/distributions/saspoint5.hpp    |  99 ++++++----
 4 files changed, 352 insertions(+), 176 deletions(-)

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index 86240e4007..2649663bdf 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -267,6 +267,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 4.5215e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87352751452164445024482162286994868262e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07622509000285763173795736744991173600e-2),
@@ -300,7 +301,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.15390928968620849348804301589542546367e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.96186359077726620124148756657971390386e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 2) {
@@ -308,6 +309,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.3996e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02038159607840130388931544845552929992e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85240836242909590376775233472494840074e-2),
@@ -341,7 +343,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63024381269503801668229632579505279520e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00967434338725770754103109040982001783e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -349,6 +351,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.6834e-35
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45396231261375200568114750897618690566e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.83107635287140466760500899510899613385e-3),
@@ -387,7 +390,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.55722115663529425797132143276461872035e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18236697046568703899375072798708359035e-10),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -395,6 +398,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.6207e-35
+        // LCOV_EXCL_START
         static const RealType P[20] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36729417918039395222067998266923903488e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05780369334958736210688756060527042344e-2),
@@ -438,7 +442,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76514314007336173875469200193103772775e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.63785420481380041892410849615596985103e-13),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -446,6 +450,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.8882e-35
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90649774685568282389553481307707005425e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70151946710788532273869130544473159961e-3),
@@ -484,7 +489,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69782249847887916810010605635064672269e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85875986197737611300062229945990879767e-18),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -492,6 +497,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.7988e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07231582988207590928480356376941073734e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35574911514921623999866392865480652576e-4),
@@ -526,7 +532,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.37798740524930029176790562876868493344e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29920082153439260734550295626576101192e-22),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -534,6 +540,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.9688e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25741312407933720816582583160953651639e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04434146174674791036848306058526901384e-6),
@@ -567,7 +574,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16321386033703806802403099255708972015e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.90892719803158002834365234646982537288e-25),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -575,6 +582,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.0545e-39
+        // LCOV_EXCL_START
         static const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99206710301074508454959544950786401357e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.75243304700875633383991614142545185173e0),
@@ -594,7 +602,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.36948968143124830402744607365089118030e4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13781639547150826385071482161074041168e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
     }
 
@@ -916,6 +924,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.5) {
         // Rational Approximation
         // Maximum Relative Error: 8.6635e-36
+       // LCOV_EXCL_START
         static const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.48548242430636907136192799540229598637e-1),
@@ -944,7 +953,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60933466092746543579699079418115420013e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92780739162611243933581782562159603862e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 1) {
@@ -952,6 +961,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 7.1235e-35
+        // LCOV_EXCL_START
         static const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60595773518728397925852903878144761766e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46999595154527091473427440379143006753e-1),
@@ -980,7 +990,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.06528824060244313614177859412028348352e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.13914667697998291289987140319652513139e-7),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 2) {
@@ -988,6 +998,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.7659e-38
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43657975600729535499895880792984203140e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.37090874182351552816526775008685285108e-2),
@@ -1022,7 +1033,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.96312716130620326771080033656930839768e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45496951385730104726429368791951742738e-10),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -1030,6 +1041,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.9091e-35
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05039829654829170780787685299556996311e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28948022754388615368533934448107849329e-2),
@@ -1068,7 +1080,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.04398743651684916010743222115099630062e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47852251142917253705233519146081069006e-10),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -1076,6 +1088,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.2255e-36
+        // LCOV_EXCL_START
         static const RealType P[20] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05754562114095147060025732340404111260e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29082907781747007723015304584383528212e-2),
@@ -1119,7 +1132,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.59098698207309055890188845050700901852e-12),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28146456709550379493162440280752828165e-14),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -1127,6 +1140,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.0174e-36
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47408470248235665279366712356669210597e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32149712567170349164953101675315481096e-2),
@@ -1164,7 +1178,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58079984178724940266882149462170567147e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19997796316046571607659704855966005180e-17),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -1172,6 +1186,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 4.5109e-36
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19610991747326725339429696634365932643e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74646611039453235739153286141429338461e-3),
@@ -1207,7 +1222,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28088047429043940293455906253037445768e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.01213369826105495256520034997664473667e-22),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -1215,6 +1230,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.2707e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11172037056341396583040940446061501972e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09383362521204903801686281772843962372e-4),
@@ -1248,7 +1264,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.85369976595753971532524294793778805089e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28948021485210224442871255909409155592e-25),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -1257,6 +1273,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.4677e-35
+        // LCOV_EXCL_START
         static const RealType P[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.48481268366645066801385595379873318648e0),
@@ -1274,7 +1291,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48350179543067311398059386524702440002e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.18873206560757944356169500452181141647e3),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
     }
 
@@ -1624,6 +1641,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         if (u < 0.5) {
             // Rational Approximation
             // Maximum Relative Error: 1.7987e-35
+           // LCOV_EXCL_START
             static const RealType P[14] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.59789769759815031687162026655576575384e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23247138049619855169890925442523844619e0),
@@ -1655,7 +1673,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.70190278641952708999014435335172772138e-5),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.11562497711461468804693130702653542297e-7),
             };
-
+            // LCOV_EXCL_STOP
             result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
@@ -1663,6 +1681,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 2.5554e-35
+            // LCOV_EXCL_START
             static const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63490994331899195346399558699533994243e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68682839419340144322747963938810505658e-1),
@@ -1692,7 +1711,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95409975934011596023165394669416595582e-6),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84312112139729518216217161835365265801e-7),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
         }
     }
@@ -1702,6 +1721,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         if (u < 0.5) {
             // Rational Approximation
             // Maximum Relative Error: 1.0297e-35
+            // LCOV_EXCL_START
             static const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84521387984759060262188972210005114936e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70837834325236202821328032137877091515e-1),
@@ -1730,7 +1750,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90504597668186854963746384968119788469e-6),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45195198322028676384075318222338781298e-7),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
@@ -1738,6 +1758,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 1.3688e-35
+            // LCOV_EXCL_START
             static const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34418795581931891732555950599385666106e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.13006013029934051875748102515422669897e-1),
@@ -1766,7 +1787,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.14604868719110256415222454908306045416e-8),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.32724040071094913191419223901752642417e-8),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
         }
     }
@@ -1775,6 +1796,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 6.6020e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46943301497773318715008398224877079279e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.85403413700924949902626248891615772650e-2),
@@ -1809,7 +1831,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19871610873353691152255428262732390602e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42468017918888155246438948321084323623e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -5) {
@@ -1818,6 +1840,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         if (u < 0.5) {
             // Rational Approximation
             // Maximum Relative Error: 5.0596e-35
+            // LCOV_EXCL_START
             static const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25344469980677353573160570139298422046e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41915371584999983192100443156935649063e-1),
@@ -1846,7 +1869,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.21425779911599424040614866482614099753e-7),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.00972806247654369646317764344373036462e-8),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * cbrt(p * p));
         }
         else {
@@ -1854,6 +1877,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 8.3743e-35
+            // LCOV_EXCL_START
             static const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08071367192424306005939751362206079160e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94625900993512461462097316785202943274e-1),
@@ -1882,7 +1906,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41526208021076709058374666903111908743e-5),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.08505866202670144225100385141263360218e-6),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
         }
     }
@@ -1891,6 +1915,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 2.4734e-35
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92042979500197776619414802317216082414e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94742044285563829335663810275331541585e-2),
@@ -1926,7 +1951,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58899179756014192338509671769986887613e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06916561094749601736592488829778059190e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -8) {
@@ -1934,6 +1959,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 1.1570e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.68520435599726860132888599110871216319e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.01076105507184082206031922185510102322e-1),
@@ -1974,7 +2000,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75479484339716254784610505187249810386e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39990051830081888581639577552526319577e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -16) {
@@ -1982,6 +2008,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 1.1362e-35
+        // LCOV_EXCL_START
         static const RealType P[22] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48432718168951398420402661878962745094e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55946442453078865766668586202885528338e-1),
@@ -2029,7 +2056,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43557805626692790539354751731913075096e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91326410956582998375100191562832969140e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -32) {
@@ -2037,6 +2064,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 9.1729e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41419813138786928653984591611599949126e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94225020281693988785012368481961427155e-1),
@@ -2077,7 +2105,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71135001552136641449927514544850663366e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98449056954034104266783180068258117013e-22),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -64) {
@@ -2085,6 +2113,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 1.8330e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392032051575981622151194498090952488e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32651097995974052731414709779952524875e-1),
@@ -2126,7 +2155,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88686274782816858372719510890126716148e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07336140055510452905474533727353308321e-25),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -128) {
@@ -2134,6 +2163,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 5.9085e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392031627647840832213878541731833340e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48256908849985263191468999842405689327e-1),
@@ -2173,7 +2203,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28628462422858134962149154420358876352e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48108558735886480279744474396456699335e-21),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else {
diff --git a/include/boost/math/distributions/landau.hpp b/include/boost/math/distributions/landau.hpp
index e84c95e4a3..8dff2041dd 100644
--- a/include/boost/math/distributions/landau.hpp
+++ b/include/boost/math/distributions/landau.hpp
@@ -349,6 +349,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 7.4629e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62240126375351657025589608183516471315e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94698530837122818345222883832757839888e-1),
@@ -380,7 +381,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09711221791106684926377106608027279057e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91302186546138009232520527964387543006e-6),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 2) {
@@ -388,6 +389,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.6684e-38
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63531240868022603475813051802104652763e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17803013130262393286657457221415701909e-1),
@@ -418,7 +420,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.84456961344035545134425261150891935402e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46462389440125559723382692664970874255e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -426,6 +428,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.3397e-35
+        // LCOV_EXCL_START
         static const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55242261334771588093967856464157010584e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48866040463435403672044647455806606078e-1),
@@ -456,7 +459,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.58127838888839012133236453180928291822e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64781659622256824499981528095809140284e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -464,6 +467,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 8.0238e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83643820409470770350079809236512802618e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02996762669868036727057860510914079553e-2),
@@ -495,7 +499,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20632869761578411246344533841556350518e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99438347491752820345051091574883391217e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -503,6 +507,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 3.2541e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12656323880287532946687856443190592955e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31374972240605659239154788518240221417e-3),
@@ -535,7 +540,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10345359368438386945407402887625511801e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55225829972215033873365516486524181445e-17),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -543,6 +548,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 4.1276e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83847488747490686627461184914507143000e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61220392257287638364190361688188696363e-4),
@@ -575,7 +581,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13281535580097407374477446521496074453e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27187882784316306216858933778750811182e-21),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -583,6 +589,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.8458e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85767880395157523314894776472286059373e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07684379950498990874449661385130414967e-4),
@@ -614,7 +621,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06007644624654848502783947087038305433e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.01246784499782934986619755015082182398e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(x) < 8) {
@@ -622,6 +629,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.6634e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78613480244945294594505480426643613242e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07362312709864018864207848733814857157e-1),
@@ -652,7 +660,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78025987104169227624653323808131280009e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93164997733174955208299290433803918816e-13),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
     }
     else if (ilogb(x) < 16) {
@@ -660,6 +668,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.1919e-36
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51438485661317103069553924870169052838e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.29652867028564588922931020456447362877e-1),
@@ -701,7 +710,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.03397072601182597002547703682673198965e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.52666999314026491934445577764441483687e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
     }
     else if (ilogb(x) < 32) {
@@ -709,6 +718,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.2411e-36
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36745544906925230101752563433306496000e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73688900814770369626527563956988302379e-1),
@@ -749,7 +759,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.43015110519230289924122344324563890953e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21788819753161690674882271896091269356e-24),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
     }
     else if (ilogb(x) < 64) {
@@ -757,6 +767,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.0348e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619776379492082323649724050601750141e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29818158612993476124594583743266388964e-1),
@@ -798,7 +809,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13592988790740273103099465658198617078e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.64942281110142621080966631872844557766e-26),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
     }
     else if (ilogb(x) < 128) {
@@ -806,6 +817,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 4.3963e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344984274685280416528592e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72417390936686577479751162141499390532e-1),
@@ -846,7 +858,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.68804852250549346018535616711418533423e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51600033199082754845231795160728350588e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x * x);
     }
     else {
@@ -1007,6 +1019,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.2803e-36
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21762208692280384264052188465103527015e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07121154108880017947709737976750200391e0),
@@ -1042,7 +1055,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99801949382703479169010768105376163814e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09234481837537672361990844588166022791e-5),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x >= -2) {
@@ -1050,6 +1063,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.8590e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.50763682207511020788551990942118742910e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35160148798611192350830963080055471564e-2),
@@ -1092,7 +1106,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43575882043846146581825453522967678538e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.06683418138599962787868832158681391673e-5),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -1106,6 +1120,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 7.0019e-35
+            // LCOV_EXCL_START
             static const RealType P[18] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31126317567898819464557840628449107915e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31008645911415314700225107327351636697e-1),
@@ -1144,7 +1159,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13900582194674129200395213522524183495e-8),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92590979457175565666605415984496551246e-9),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -6.875) {
@@ -1152,6 +1167,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 6.4095e-35
+            // LCOV_EXCL_START
             static const RealType P[18] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26864481454444278645937156746132802908e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35052316263030534355724898036735352905e0),
@@ -1192,7 +1208,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23201118234279642321630988607491208515e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43185798646451225275728735761433082676e-13),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else {
@@ -1588,6 +1604,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 2.6472e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34761298487625202628055609797763667089e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67589195401255255724121983550745957195e0),
@@ -1619,7 +1636,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86326948577818727263376488455223120476e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53867591038308710930446815360572461884e-7),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 2) {
@@ -1627,6 +1644,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.2387e-36
+        // LCOV_EXCL_START
         static const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22133240358047652363270514524313049653e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35860518549481281929441026718420080571e-1),
@@ -1655,7 +1673,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76323449710934127736624596886862488066e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21524231900555452527639738371019517044e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -1663,6 +1681,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.2281e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95892137955791216377776422765473500279e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65957634570689820998348206103212047458e-1),
@@ -1693,7 +1712,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.94457070577990681786301801930765271001e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80986568964737305842778359322566801845e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -1701,6 +1720,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 5.3269e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73159318667565938775602634998889798568e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95149372103869634275319490207451722385e-1),
@@ -1732,7 +1752,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.14578198844767847381800490360878776998e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.25951924258762195043744665124187621023e-13),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -1740,6 +1760,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 4.8719e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.90469147411748292410422813492550092930e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20196598836093298098360769875443462143e-2),
@@ -1772,7 +1793,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72943283576264035508862984899450025895e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77791087299927741360821362607419036797e-18),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -1780,6 +1801,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 5.3269e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35157264931262089761621934621402648954e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51407493866635569361305338029611888082e-2),
@@ -1811,7 +1833,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.04202174160401885595563150562438901685e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82104711207466136473754349696286794448e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -1819,6 +1841,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.0937e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11253031965493064317003259449214452745e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66886306590939856622089350675801752704e-3),
@@ -1850,7 +1873,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.93147765040455324545205202900563337981e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07370974123835247210519262324524537634e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(x) < 8) {
@@ -1858,6 +1881,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 3.1671e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60754766433212615408805486898847664740e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.76143516602438873568296501921670869526e-1),
@@ -1888,7 +1912,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10819003833429876218381886615930538464e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75674945131892236663189757353419870796e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
     }
     else if (ilogb(x) < 16) {
@@ -1896,6 +1920,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.8517e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44802371584831601817146389426921705500e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.32962058761590152378007743852342151897e-1),
@@ -1936,7 +1961,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18166403020940538730241286150437447698e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47995312365747437038996228794650773820e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
     }
     else if (ilogb(x) < 32) {
@@ -1944,6 +1969,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.5315e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36685748306554972131586673701426039950e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75892450098649456865500477195142009984e-1),
@@ -1983,7 +2009,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.23730041323226753771240724078738146658e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60115971929371066362271909482282503973e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
     }
     else if (ilogb(x) < 64) {
@@ -1991,6 +2017,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.0538e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619774420718062663274858007687066488e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30268560944740805268408378762250557522e-1),
@@ -2032,7 +2059,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.16715818685246698314459625236675887448e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.77987471623502330881961633434056523159e-26),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
     }
     else if (ilogb(x) < 128) {
@@ -2040,6 +2067,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.2309e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344040890134127619524371e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72522424358877592972375801826826390634e-1),
@@ -2080,7 +2108,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69538874529209016624246362786229032706e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52796320119313458991885552944744518437e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * x);
     }
     else {
@@ -2244,6 +2272,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.2055e-36
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61609610406317335842332400044553397267e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74152295981095898203847178356629061821e-1),
@@ -2279,7 +2308,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72080705566714681586449384371609107346e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76433504120625478720883079263866245392e-6),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x >= -2) {
@@ -2287,6 +2316,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.4133e-36
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07114056489178077422539043012078031613e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18006784954579394004360967455655021959e-3),
@@ -2329,7 +2359,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00697535360590561244468004025972321465e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23883308105457761862174623664449205327e-6),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -2343,6 +2373,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 9.2619e-35
+            // LCOV_EXCL_START
             static const RealType P[19] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71658823632747235572391863987803415545e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20402452680758356732340074285765302037e-1),
@@ -2383,7 +2414,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39138685106442954199109662617641745618e-9),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.83317957765031605023198891326325990178e-10),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -6.875) {
@@ -2391,6 +2422,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 4.9208e-35
+            // LCOV_EXCL_START
             static const RealType P[20] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97500903816385095134217223320239082420e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02058997410109156148729828665298333233e0),
@@ -2434,7 +2466,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07996042577029996321821937863373306901e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53576500935979732855511826033727522138e-13),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else {
@@ -2856,6 +2888,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 2.5723e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74557416577759248536854968412794870581e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.04379368253541440583870397314012269006e0),
@@ -2885,7 +2918,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29121822170912306719250697890270750964e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56489746112937744052098794310386515793e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
@@ -2893,6 +2926,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 6.1583e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.17764764050720242897742634974454113395e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.80044093802431965072543552425830082205e0),
@@ -2923,7 +2957,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.52472388998113562780767055981852228229e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.01428305018551686265238906201345171425e0),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
@@ -2931,6 +2965,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 1.3135e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160121458e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.05813204052660740589813216397258899528e1),
@@ -2965,7 +3000,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.26616234097287315007047356261933409072e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24686019847093806280148917466062407447e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4) {
@@ -2973,6 +3008,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 2.0498e-35
+        // LCOV_EXCL_START
         static const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160155093e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.77585398076895266354686007069850894777e0),
@@ -2999,7 +3035,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88173142080572819772032615169461689904e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07756799117728455728056041053803769069e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -8) {
@@ -3007,6 +3043,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.7643e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16727296241754547290632950718657117630e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97822895738734630842909028778257589627e0),
@@ -3039,7 +3076,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38087376350052845654180435966624948994e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34945081364333330292720602508979680233e-16),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -16) {
@@ -3047,6 +3084,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.4987e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78348038398799867332294266481364810762e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42913983922316889357725662957488617770e0),
@@ -3079,7 +3117,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31680570822471881148008283775281806658e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61638868324981393463928986484698110415e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -32) {
@@ -3087,6 +3125,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.4643e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.32474749499506228416012679106564727824e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.11125026189437033131539969177846635890e-1),
@@ -3119,7 +3158,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08670633989984379551412930443791478495e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96869107941293302786688580824755244599e-24),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -64) {
@@ -3127,6 +3166,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.2783e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.82318656228158372073367735499501003484e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.46261040951642110189344545942990712460e-1),
@@ -3159,7 +3199,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94530899348454778842122895096072361105e-24),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36452993460830805591166007621343447892e-28),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -128) {
@@ -3167,6 +3207,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.0123e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.29700011190686230364493911161520668302e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.16175031776740080906111179721128106011e-1),
@@ -3199,7 +3240,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.64683991040772975824276994623053932566e-28),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81924597500766743545654858597960153152e-32),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -256) {
@@ -3207,6 +3248,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.7624e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.75666995985336007747791649448887723610e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78960399079208663111712385988217075907e-1),
@@ -3239,7 +3281,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11059307697054035905630311480256015939e-31),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36363494270701950295678466437393953964e-36),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -512) {
@@ -3247,6 +3289,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.5621e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.20826069989721596260510558511263035942e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.97440158261228371765435988840257904642e-2),
@@ -3279,7 +3322,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66384334839761400228111118435077786644e-35),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02877806111195383689496741738320318348e-40),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -1024) {
@@ -3287,6 +3330,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.4128e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.65527239540648657446629479052874029563e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.49609214609793557370425343404734771058e-2),
@@ -3319,7 +3363,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.41571947895162847564926590304679876888e-39),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.84682590163505511580949151048092123923e-44),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -2048) {
@@ -3327,6 +3371,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.3064e-35
+        //LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.09971143249822249471944441552701756051e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.00154235169065403254826962372636417554e-2),
@@ -3359,7 +3404,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55089353084326800338273098565932598679e-42),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.85408276119483460035366338145310798737e-48),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4096) {
@@ -3367,6 +3412,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.2337e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.54271778755494231572464179212263718102e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62737121212473668543011440432166267791e-2),
@@ -3399,7 +3445,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76046592638280288324495546006105696670e-46),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.09378739037162732758860377477607829024e-52),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -8192) {
@@ -3407,6 +3453,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.1864e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.98493298246627952401490656857159302716e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.76990949843357898517869703626917264559e-3),
@@ -3439,7 +3486,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.13947437500822384369637881437951570653e-50),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.61766557173110449434575883392084129710e-56),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -16384) {
@@ -3447,6 +3494,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.1568e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.42671464308364892089984144203590292562e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.70165333325375920690660683988390032004e-3),
@@ -3479,7 +3527,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22499308298315468568520585583666049073e-53),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04877018522402283597555167651619229959e-59),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -3740,6 +3788,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.4465e-35
+        // LCOV_EXCL_START
         static const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.08338732735341567163440035550389989556e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27245731792290848390848202647311435023e0),
@@ -3765,7 +3814,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32647058691746306769699006355256099134e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.59208938705683333141038012302171324544e0),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.375) {
@@ -3773,6 +3822,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.1929e-35
+        // LCOV_EXCL_START
         static const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31348919222343858173602105619413801018e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02800226274700443079521563669609776285e0),
@@ -3798,7 +3848,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.93964809733838306198746831833843897743e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53948309965401603055162465663290204205e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
@@ -3806,6 +3856,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 3.2765e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55081568282045925871949387822806890848e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21080883686702131458668798583937913025e1),
@@ -3836,7 +3887,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36592279898578127130605391750428961301e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18495624730372864715421146607185990918e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
@@ -3844,6 +3895,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.8007e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68160868054034088524891526884683014057e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85165791469635551063850795991424359350e2),
@@ -3877,7 +3929,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.76034827722473399290702590414091767416e4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94027684838690965214346010602354223752e3),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4) {
@@ -3885,6 +3937,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 6.1905e-36
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.10201085067542610656114408605853786551e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04725580445598482170291458376577106746e-1),
@@ -3915,7 +3968,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65919857481420519138294080418011981524e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31466713452016682217190521435479677133e-10),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else if (ilogb(p) >= -8) {
@@ -3923,6 +3976,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 8.5157e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06147398566773479301585022897491054494e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06137881154706023038556659418303323027e0),
@@ -3963,7 +4017,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19708585422668069396821478975324123588e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40406059898292960948942525697075698413e-15),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else if (ilogb(p) >= -16) {
@@ -3971,6 +4025,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 7.6812e-36
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48209596014908270566135466727658374314e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02026332003132864886056710532156370366e-1),
@@ -4011,7 +4066,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.65309560070040982176772709693008187384e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42817828965851841104270899392956866435e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else if (ilogb(p) >= -32) {
@@ -4019,6 +4074,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 2.8388e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36719010559816175149447242695581604280e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14714772485724956396126176973339095223e-1),
@@ -4059,7 +4115,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08041298058041360645934320138765284054e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.91893114159827950553463154758337724676e-24),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else if (ilogb(p) >= -64) {
@@ -4067,6 +4123,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.8746e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619775525705288697351261475419832625e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29882145587771350744255724773409752285e-1),
@@ -4108,7 +4165,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14570923483883184645242764315877865073e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.69599603258626408321886443187629340033e-26),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else if (ilogb(p) >= -128) {
@@ -4116,6 +4173,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 3.9915e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344576326594951209529606e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72456363182667891167613558295097711432e-1),
@@ -4156,7 +4214,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.69337661543585547694652989893297703060e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53684359865963395505791671817598669527e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * p);
     }
     else {
diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index 53517a641e..f5f88486ef 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -259,6 +259,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 7.8308e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97516171847191855609649452292217911973e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17531822787252717270400174744562144891e-1),
@@ -289,7 +290,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27513004715414297729539702862351044344e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54510493017251997793679126704007098265e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 2) {
@@ -297,6 +298,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.0723e-35
+        // LCOV_EXCL_START
         static const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06251243013238748252181151646220197947e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92438638323563234519452281479338921158e-2),
@@ -326,7 +328,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97296173230649275943984471731360073540e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48943057909563158917114503727080517958e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -334,6 +336,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 4.0903e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.33842514891989443409465171800884519331e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53264053296761245408991932692426094424e-2),
@@ -366,7 +369,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90325380271096603676911761784650800378e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.36933359079566550212098911224675011839e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -374,6 +377,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 6.5015e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58950538583133457383574346194006716984e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25447644411503971725638816502617490834e-2),
@@ -410,7 +414,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15444386779802728200716489787161419304e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02452666470008756043350040893761339083e-16),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -418,6 +422,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.0995e-35
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22517551525042172427941302520759668293e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86576974828476461442549217748945498966e-3),
@@ -454,7 +459,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35681579117696161282979297336282783473e-16),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92944288060269290125987728528698476197e-18),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -462,6 +467,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.0937e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82527663232857270992129793621400616909e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41696401156754081476312871174198295322e-4),
@@ -496,7 +502,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78213669817351488671519066803835958715e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75492332026736176991870807903277324902e-22),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -504,6 +510,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.5856e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03264853379349880038687006045193401399e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79539964604630527636184900467871907171e-5),
@@ -537,7 +544,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43792928765659831045040802615903432044e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.79856365207259871336606847582889916798e-25),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -545,6 +552,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.5081e-36
+        // LCOV_EXCL_START
         static const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98413420602149016909919089901572802714e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30303835860684077803651094768293625633e-1),
@@ -564,7 +572,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20093079283917759611690534481918040882e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82564796242972192725215815897475246715e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
     }
 
@@ -755,6 +763,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 5.2870e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76859868856746781256050397658493368372e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13037642242224438972685982606987140111e-1),
@@ -786,7 +795,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.43625211359756249232841566256877823039e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33207781577559817130740123609636060998e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x >= -2) {
@@ -794,6 +803,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 1.1977e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14483832832989822788477500521594411868e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75657192307644021285091474845448102656e-1),
@@ -826,7 +836,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71646204381423826495116781730719271111e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30359141441663007574346497273327240071e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -837,6 +847,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 5.4547e-35
+            // LCOV_EXCL_START
             static const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74308494787955998605105974174143750745e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.56767876568276519015214709629156760546e-1),
@@ -871,7 +882,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58728676819719406366664644282113323077e-7),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72685000369623096389026353785111272994e-9),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -8) {
@@ -879,6 +890,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 1.8813e-35
+            // LCOV_EXCL_START
             static const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67391547707456587286086623414017962238e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.69944730920904699720804320295067934914e-1),
@@ -913,7 +925,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42340212199922656577943251139931264313e-9),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.75700556749505163188370496864513941614e-11),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -16) {
@@ -921,6 +933,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 3.7501e-35
+            // LCOV_EXCL_START
             static const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66153901932100301337118653561328446399e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52542079386371212946566450189144670788e-1),
@@ -951,7 +964,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.24233005893817070145949404296998119469e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.89735152971223120087721392400123727326e-12),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -32) {
@@ -959,6 +972,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 9.2696e-36
+            // LCOV_EXCL_START
             static const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65985830928929730672052407058361701971e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80409998734303497641108024806388734755e-1),
@@ -986,7 +1000,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87471345773127482399498877510153906820e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92954174836731254818376396170511443820e-12),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -64) {
@@ -994,6 +1008,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 2.3524e-35
+            // LCOV_EXCL_START
             static const RealType P[10] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65964563346442080104568381680822923977e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.77958685324702990033291591478515962894e-2),
@@ -1017,7 +1032,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68948879514200831687856703804327184420e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07366525547027105672618224029122809899e-12),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else {
@@ -1320,6 +1335,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 4.7720e-37
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33333333333333333333333333333333333333e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38519736580901276671338330967060054188e-1),
@@ -1350,7 +1366,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13919959493955187399856105325181806876e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30960533107704070411766556906543316310e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 2) {
@@ -1358,6 +1374,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.6297e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84196970581015939887507434989936103587e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23864910443500344832158256856064580005e-1),
@@ -1387,7 +1404,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37981396630189761210639158952200945512e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55820444854396304928946970937054949160e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -1395,6 +1412,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.8103e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07409273397524124098315500450332255837e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98373054365213259465522536994638631699e-2),
@@ -1427,7 +1445,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62479830409039340826066305367893543134e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22039803134898937546371285610102850458e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -1435,6 +1453,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 7.5930e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70720199535228802537946089633331273434e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85220706158476482443562698303252970927e-2),
@@ -1469,7 +1488,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82464168044335183356132979380360583444e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40073718480172265670072434562833527076e-17),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -1477,6 +1496,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 7.3609e-35
+        // LCOV_EXCL_START
         static const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74847564444513000450056174922427854591e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56842503159303803254436983444304764079e-2),
@@ -1512,7 +1532,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35452907177197742692545044913125982311e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23587924912460218189929226092439805175e-17),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -1520,6 +1540,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 9.7192e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.22684103170563193014558918295924551173e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55222688816852408105912768186300290291e-3),
@@ -1553,7 +1574,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08200002287534174751275097848899176785e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15305756373406702253187385797525419287e-21),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -1561,6 +1582,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 9.7799e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20357145727036120652264700679701054983e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95712324967981162396595365933255312698e-4),
@@ -1593,7 +1615,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.08681155203261739689727004641345513984e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.28282024196484688479115133027874255367e-30),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -1602,6 +1624,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.5865e-37
+        // LCOV_EXCL_START
         static const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12426566605292130233061857505057433291e-1),
@@ -1621,7 +1644,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51642534474780515366628648516673270623e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05977615003758056284424652420774587813e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
     }
 
@@ -1816,6 +1839,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 1.0688e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23238998449671083670041452413316011920e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.14900991369455846775267187236501987891e-1),
@@ -1847,7 +1871,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02436961569668743353755318268149636644e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.50130875023154569442119099173406269991e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x >= -2) {
@@ -1855,6 +1879,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 5.1815e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62598955251978523174755901843430986522e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08127698872954954678270473317137288772e-1),
@@ -1887,7 +1912,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70594730517167328271953424328890849790e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30162314557860623869079601905904538470e-9),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -1898,6 +1923,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 6.4678e-36
+            // LCOV_EXCL_START
             static const RealType P[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.31806744221966404520449104514474066823e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50292887071777664663197915067642779665e0),
@@ -1934,7 +1960,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64077137545614380065714904794220228239e-8),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08139724991616322332901357866680220241e-10),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -8) {
@@ -1942,6 +1968,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 3.5975e-36
+            // LCOV_EXCL_START
             static const RealType P[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10294551528734705945662709421382590676e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26135857114883288617323671166863478751e0),
@@ -1978,7 +2005,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.29174652982710100418474261697035968379e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31746082236506935340972706820707017875e-12),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -16) {
@@ -1986,6 +2013,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 2.6792e-35
+            // LCOV_EXCL_START
             static const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18246847255744057280356900905660312795e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77955886026107125189834586992142580148e0),
@@ -2019,7 +2047,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.72759238269315282789451836388878919387e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79966603543593799412565926418879689461e-12),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -32) {
@@ -2027,6 +2055,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 2.1744e-36
+            // LCOV_EXCL_START
             static const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19497306481411168355692832231058399132e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.15593166681833539521403250736661720488e-1),
@@ -2055,7 +2084,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08288201960155447241423587030002372229e-11),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.29720612489952110448407063201146274502e-14),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else if (x >= -64) {
@@ -2063,6 +2092,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 3.4699e-36
+            // LCOV_EXCL_START
             static const RealType P[10] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19659414007358083585943280640656311534e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36969140730640253987817932335415532846e-1),
@@ -2087,7 +2117,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35999937789324222934257460080153249173e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91435929481043135336094426837156247599e-14),
             };
-
+            // LCOV_EXCL_STOP
             result = s * tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
         }
         else {
@@ -2510,6 +2540,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 4.2901e-35
+        // LCOV_EXCL_START
         static const RealType P[10] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.48344198262277235851026749871350753173e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18249834490570496537675012473572546187e0),
@@ -2535,7 +2566,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.37863084758381651884340710544840951679e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46880981703613838666108664771931239970e0),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.375) {
@@ -2543,6 +2574,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.8433e-36
+        // LCOV_EXCL_START
         static const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.17326074020471664204142312429732771661e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23412560010002723970559712941124583385e0),
@@ -2568,7 +2600,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.37210093190088984630526671624779422232e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06793750951779308425209267821815264457e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
@@ -2576,6 +2608,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 5.9072e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63281240925531315038207673147576291783e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72733898245766165408685147762489513406e1),
@@ -2606,7 +2639,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76156378002782668186592725145930755636e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.70446647862725980215630194019740606935e0),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
@@ -2614,6 +2647,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 9.9092e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467019660e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16991481696416567893311341049825218287e1),
@@ -2648,7 +2682,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.07234815204245866330282860014624832711e4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21353269292094971546479026200435095695e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4) {
@@ -2656,6 +2690,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.9653e-35
+        // LCOV_EXCL_START
         static const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467025793e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.94718878144788678915739777385667044494e0),
@@ -2682,7 +2717,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09877166004503937701692216421704042881e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01544823753120969225271131241177003165e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -8) {
@@ -2690,6 +2725,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 6.7872e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.59822399410385083283727681965013517187e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.30676107401101401386206170152508285083e0),
@@ -2723,7 +2759,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40356170422999016176996652783329671363e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.31127037096552892520323998665757802862e-16),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -16) {
@@ -2731,6 +2767,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 7.6679e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.67354365380697578246790709817724831418e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.98681625368564496421038758088088788795e0),
@@ -2764,7 +2801,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.91577723105757841509716090936343311518e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13824283239122976911704652025193325941e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -32) {
@@ -2772,6 +2809,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 8.6323e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.92187819510636694694450607724165689649e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97763858433958798529675258052376253402e0),
@@ -2805,7 +2843,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83472702205100162081157644960354192597e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07575352729625387198150555665307193572e-24),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -64) {
@@ -2813,6 +2851,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 9.8799e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.41443550638291131009585191506467028820e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.27887396494095561461365753577189254063e0),
@@ -2846,7 +2885,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28225402720788909349967839966304553864e-24),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.22313199865592821923485268860178384308e-28),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -128) {
@@ -2854,6 +2893,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.1548e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.23500806363233607692361021471929016922e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16747938711332885952564885548768072606e-1),
@@ -2887,7 +2927,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00900961462911160554915139090711911885e-27),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65825716532665817972751320034032284421e-32),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -256) {
@@ -2895,6 +2935,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.3756e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.04845570631944023525776899386112795330e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.18146685146173151383718092529868406030e-1),
@@ -2928,7 +2969,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39845313960416564778273486179935754019e-31),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14538443937605324316706211070799970095e-35),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -512) {
@@ -2936,6 +2977,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.6639e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32865827226175697711590794217590458484e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27551166309670994513910580518431041518e-1),
@@ -2969,7 +3011,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74218645918961186861014420578277888513e-35),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36897549168687040570349702061165281706e-39),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -1024) {
@@ -2977,6 +3019,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.0360e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.67937186583822375017526293948703697225e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.06681764321003187068904973985967908140e-1),
@@ -3010,7 +3053,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38232043389918216652459244727737381677e-38),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64599465785019268214108345671361994702e-43),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -2048) {
@@ -3018,6 +3061,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.5130e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.11959316095291435774375635827672517008e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.30292575371366023255165927527306483022e-1),
@@ -3051,7 +3095,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34142897042941614778352280692901008538e-42),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98791658647635156162347063765388728959e-47),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4096) {
@@ -3059,6 +3103,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.1220e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.67307564006689676593687414536012112755e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.21005690250741024744367516466433711478e-2),
@@ -3092,7 +3137,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10247886333916820534393624270217678968e-46),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40899321122058714028548211810431871877e-51),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -8192) {
@@ -3100,6 +3145,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.8974e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.36960987939726803544369406181770745475e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.17239311695985070524235502979761682692e-2),
@@ -3133,7 +3179,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96933863894082533505471662180541379922e-49),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92661972206232945959915223259585457082e-55),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -16384) {
@@ -3141,6 +3187,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 4.8819e-35
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.24662793339079714510108682543625432532e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25841960642102016210295419419373971750e-2),
@@ -3174,7 +3221,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79448544326289688123648457587797649323e-53),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.56179793347045575604935927245529360950e-59),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -3399,6 +3446,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Absolute Error: 4.0835e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.00474815142578902619056852805926666121e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56422290947427848191079775267512708223e0),
@@ -3428,7 +3476,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.11941093895004369510720986032269722254e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.51487618026728514833542002963603231101e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.25) {
@@ -3436,6 +3484,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Absolute Error: 5.7633e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81512108276093787175849069715334402323e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24417080443497141096829831516758083481e0),
@@ -3467,7 +3516,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.17969051793607842221356465819951568080e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82773308760283383020168853159163391394e2),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (p >= 0.125) {
@@ -3475,6 +3524,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Absolute Error: 2.1140e-36
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70276979914029738186601698003670175907e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63126762626382548478172664328434577553e1),
@@ -3510,7 +3560,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.22682822001329636071591164177026394518e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.09781406768816062486819491582960840983e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (ilogb(p) >= -4) {
@@ -3518,6 +3568,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.1409e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25692449785074345466504245009175450649e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75679137667345136118441108839649360362e-1),
@@ -3550,7 +3601,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15454119109586223908613596754794988609e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55273685376557721039847456564342945576e-10),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -8) {
@@ -3558,6 +3609,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.2521e-35
+        // LCOV_EXCL_START
         static const RealType P[23] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07341098045260497471001948654506267614e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16518383383878659278973043343250842753e-1),
@@ -3608,7 +3660,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41278271853370874105923461404291742454e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95100373579692323015092323646110838623e-15),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -16) {
@@ -3616,6 +3668,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.0703e-35
+        // LCOV_EXCL_START
         static const RealType P[21] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41774626094491452462664949805613444094e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96383089261273022706449773421031102175e-1),
@@ -3661,7 +3714,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74309280855806399632683315923592902203e-16),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58097100528573186098159133443927182780e-18),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -32) {
@@ -3669,6 +3722,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.4124e-35
+        // LCOV_EXCL_START
         static const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926067826974814669251179264786585885e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21141529920003643675474888047093566280e-1),
@@ -3710,7 +3764,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.20285566539355859922818448335043495666e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71782855576364068752705740544460766362e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else if (ilogb(p) >= -64) {
@@ -3718,6 +3772,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.1680e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926070139289008206183757488364846894e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78434820569480998586988738136492447574e-1),
@@ -3758,7 +3813,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70989324903345102377898775620363767855e-16),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.47067260145014475572799216996976703615e-18),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else {
diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
index 597421af83..f21f52d9a2 100644
--- a/include/boost/math/distributions/saspoint5.hpp
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -341,6 +341,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.0625) {
         // Rational Approximation
         // Maximum Relative Error: 8.8841e-35
+        // LCOV_EXCL_START
         static const RealType P[27] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581343075535053490057448138e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.57459506929453385798277946154823008327e2),
@@ -400,7 +401,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.58032845332990262754766784625271262271e37),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.50461648438613634025964361513066059697e36),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 0.125) {
@@ -408,6 +409,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.4585e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46416716200748206779925127900698754119e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41771273526123373239570033672829787791e1),
@@ -439,7 +441,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63379428046258653791600947328520263412e8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14558538557562267533922961110917101850e8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.25) {
@@ -447,6 +449,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.9278e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35668401768623200524372663239480799018e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30066509937988171489091367354416214000e1),
@@ -478,7 +481,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53513095899009948733175317927025056561e6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69130675750530663088963759279778748696e5),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.5) {
@@ -486,6 +489,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.9378e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95645445681747568731488283573032414811e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.83246437763964151893665752064650172391e0),
@@ -518,7 +522,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91061555870569579915258835459255406575e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43045229010040855016672246098687100063e1),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 1) {
@@ -526,6 +530,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.4363e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70762401725206223811383500786268939645e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19353011456197635663058525904929358535e0),
@@ -558,7 +563,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.01852843874982199859775136086676841910e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.14767043526088185802569803397824432028e-3),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 2) {
@@ -566,6 +571,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.1244e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.61071469126041183247373313827161939454e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35837460186564880289965856498718321896e-1),
@@ -597,7 +603,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.09333568224541559157192543410988474886e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.59947287428695057506683902409023760438e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -605,6 +611,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 8.1110e-35
+        // LCOV_EXCL_START
         static const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91428580496513429479068747515164587814e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69015019070193436467106672180804948494e-2),
@@ -636,7 +643,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60041713691072903334637560080298818163e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77381528950794767694352468734042252745e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -644,6 +651,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.5228e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65057384221262866484014802392420311075e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92801687242885330588201777283015178448e-2),
@@ -675,7 +683,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.39524198476052364627683067034422502163e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18666081063885228839052386515073873844e-13),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -683,6 +691,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.6732e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60044810497290557552736366450372523266e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27034183360438185616541260923634443241e-3),
@@ -715,7 +724,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85519293212465087373898447546710143008e-16),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.96728437809303144188312623363453475831e-19),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -723,6 +732,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.0113e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54339461777955741686401041938275102207e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17747085249877439037826121862689145081e-4),
@@ -755,7 +765,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23639219622240634094606955067799349447e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63446235885036169537726818244420509024e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -763,6 +773,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.7056e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55085695067883584460317653567009454037e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52919532248638251721278667010429548877e-4),
@@ -795,7 +806,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06487673393164724939989217811068656932e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47121057452822097779067717258050172115e-27),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -803,6 +814,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 7.1032e-36
+        // LCOV_EXCL_START
         static const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82846732476244747063962056024672844211e-2),
@@ -824,7 +836,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.17497990182339853998751740288392648984e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53420609011698705803549938558385779137e-6),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t / x;
     }
 
@@ -1155,6 +1167,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.125) {
         // Rational Approximation
         // Maximum Relative Error: 6.9340e-35
+        // LCOV_EXCL_START
         static const RealType P[30] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25520067710293108163697513129883130648e2),
@@ -1220,7 +1233,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10591353097667671736865938428051885499e35),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26980708896893794012677171239610721832e33),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, x) / tools::evaluate_polynomial(Q, x);
     }
     else if (x < 0.25) {
@@ -1228,6 +1241,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.6106e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31887921568009055676985827521151969069e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62791448964529380666250180886203090183e1),
@@ -1259,7 +1273,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.02083431572388097955901208994308271581e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30401057171447074343957754855656724141e4),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 0.5) {
@@ -1267,6 +1281,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.1519e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87119665000174806422420129219814467874e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.60769554551148293079169764245570645155e0),
@@ -1298,7 +1313,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.06384106042490712972156545051459068443e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27614406724572981099586665536543423891e0),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 1) {
@@ -1306,6 +1321,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 7.1196e-37
+        // LCOV_EXCL_START
         static const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31309550000758082761278726632760756847e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07242222531117199094690544171275415854e0),
@@ -1339,7 +1355,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62522294286034117189844614005500278984e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18342889744790118595835138444372660676e-3),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 2) {
@@ -1347,6 +1363,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.5605e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71280312689343266367958859259591541365e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49628636612698702680819948707479820292e0),
@@ -1379,7 +1396,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31888539972217875242352157306613891243e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85633766164682554126992822326956560433e-8),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 4) {
@@ -1387,6 +1404,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.1494e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13928162275383718405630406427822960090e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90742307267701162395764574873947997211e-1),
@@ -1419,7 +1437,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.19146442700994823924806249608315505708e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59879298772002950043508762057850408213e-12),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 8) {
@@ -1427,6 +1445,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.9710e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63772802979087199762340235165979751298e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31941534705372320785274994658709390116e-1),
@@ -1459,7 +1478,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.10009654621246392691126133176423833259e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.48070591106986983088640496621926852293e-16),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 16) {
@@ -1467,6 +1486,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.2049e-36
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22610122564874286614786819620499101143e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.30352481858382230273216195795534959290e-2),
@@ -1499,7 +1519,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.80392324086028812772385536034034039168e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34254502871215949266781048808984963366e-20),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 32) {
@@ -1507,6 +1527,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.7434e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03056141356415128156562790092782153630e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15331583242023443256381237551843296356e-2),
@@ -1539,7 +1560,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79013190225240505774959477465594797961e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.46536966503325413797061462062918707370e-24),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else if (x < 64) {
@@ -1547,6 +1568,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.0402e-35
+        // LCOV_EXCL_START
         static const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57333571766941514095434647381791040479e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15416685251021339933358981066948923001e-2),
@@ -1579,7 +1601,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.77217411888267832243050973915295217582e-24),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.67397425207383164084527830512920206074e-28),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
@@ -1587,6 +1609,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.2612e-35
+        // LCOV_EXCL_START
         static const RealType P[9] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33908701314796522684603310107061150444e-1),
@@ -1607,7 +1630,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02913299057943756875992272236063124608e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37824426836648736125759177846682556245e-5),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t) * t;
     }
 
@@ -1978,6 +2001,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         if (u < 0.125) {
             // Rational Approximation
             // Maximum Relative Error: 2.5675e-36
+            // LCOV_EXCL_START
             static const RealType P[31] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36099130643975133156293056139850872219e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03940482189350763127508703926866548690e1),
@@ -2045,7 +2069,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96635220211386288597285960837372073054e33),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23849744128418288892902205619933047730e32),
             };
-
+            // LCOV_EXCL_STOP
             result = u * tools::evaluate_polynomial(P, u) / (tools::evaluate_polynomial(Q, u) * (p * p));
         }
         else if (u < 0.25) {
@@ -2053,6 +2077,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 9.0663e-36
+            // LCOV_EXCL_START
             static const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46698650748920243663487731226111319705e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.39021286045890143123252180276484388346e-1),
@@ -2083,7 +2108,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83958740186543542804045767758191509433e3),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.26637084978098507405883170227585648985e2),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else if (u < 0.5) {
@@ -2091,6 +2116,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 7.1265e-35
+            // LCOV_EXCL_START
             static const RealType P[14] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69627866689346442965083437425920959525e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.28948812330446670380449765578224539665e-1),
@@ -2122,7 +2148,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.43813483967503071358907030110791934870e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.21327682641358836049127780506729428797e-1),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
         else {
@@ -2130,6 +2156,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 2.7048e-37
+            // LCOV_EXCL_START
             static const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79518653373241051262822702930040975338e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62230291299220868262265687829866364204e-1),
@@ -2164,7 +2191,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13088455793478303045390386135591069087e-3),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.18220605549460262119565543089703387122e-5),
             };
-
+            // LCOV_EXCL_STOP
             result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
         }
     }
@@ -2173,6 +2200,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 3.8969e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.02395484493329839255216366819344305871e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02703992140456336967688958960484716694e-1),
@@ -2212,7 +2240,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44620973323561344735660659502096499899e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84398925760354259350870730551452956164e-11),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else if (ilogb(p) >= -8) {
@@ -2220,6 +2248,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.0176e-35
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39293493266195566603513288406748830312e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75724665658983779947977436518056682748e-1),
@@ -2258,7 +2287,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50841502849442327828534131901583916707e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19165038770000448560339443014882434202e-15),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else if (ilogb(p) >= -16) {
@@ -2266,6 +2295,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.1682e-36
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57911660613037766795694241662819364797e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28799302413396670477035614399187456630e-1),
@@ -2304,7 +2334,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45570688568663643410924100311054014175e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23959804461200982866930072222355142173e-19),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else if (ilogb(p) >= -32) {
@@ -2312,6 +2342,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 6.2158e-37
+        // LCOV_EXCL_START
         static const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59150086070234561732507586188017224084e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80849532387385837583114307010320459997e-2),
@@ -2350,7 +2381,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.40555520515542383952495965093730818381e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.51084407433793180162386990118245623958e-23),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else if (ilogb(p) >= -64) {
@@ -2358,6 +2389,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 9.8515e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943017783040087729009335921759322e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.35955784629344586058432079844665517425e-2),
@@ -2398,7 +2430,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.81435584873372180820418114652670864136e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62145023253666168339801687459484937001e-25),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else if (ilogb(p) >= -128) {
@@ -2406,6 +2438,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 2.2157e-35
+        // LCOV_EXCL_START
         static const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943091895335751628149866310390641e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.91164927854420277537616294413463565970e-2),
@@ -2445,7 +2478,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28628462422858135083238952377446358986e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48108558735886480298604270981393793162e-21),
         };
-
+        // LCOV_EXCL_STOP
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * (p * p));
     }
     else {

From 86daac38f52c16e31a20cefc1d2a21209b518c82 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 09:55:44 -0400
Subject: [PATCH 104/399] Add markers for log1p

---
 include/boost/math/special_functions/log1p.hpp    | 4 ++--
 include/boost/math/special_functions/math_fwd.hpp | 8 ++++----
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/special_functions/log1p.hpp b/include/boost/math/special_functions/log1p.hpp
index fc7308eb67..8fb379fe46 100644
--- a/include/boost/math/special_functions/log1p.hpp
+++ b/include/boost/math/special_functions/log1p.hpp
@@ -433,7 +433,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x)
 // Compute log(1+x)-x:
 //
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    log1pmx(T x, const Policy& pol)
 {
    typedef typename tools::promote_args<T>::type result_type;
@@ -465,7 +465,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type log1pmx(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1pmx(T x)
 {
    return log1pmx(x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index e2ac58e850..fe61a420e9 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -577,10 +577,10 @@ namespace boost
 
    // log1pmx is log(x + 1) - x
    template <class T>
-   tools::promote_args_t<T> log1pmx(T);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> log1pmx(T);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> log1pmx(T, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> log1pmx(T, const Policy&);
 
    // Exp (x) minus 1 functions.
    template <class T>
@@ -1471,10 +1471,10 @@ namespace boost
    inline boost::math::tools::promote_args_t<RT> cbrt(RT z){ return boost::math::cbrt(z, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> log1p(T x){ return boost::math::log1p(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> log1p(T x){ return boost::math::log1p(x, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> log1pmx(T x){ return boost::math::log1pmx(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> log1pmx(T x){ return boost::math::log1pmx(x, Policy()); }\
 \
    template <class T>\
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> expm1(T x){ return boost::math::expm1(x, Policy()); }\

From 2f2372b7cb2f3e3b05d92846082b9e62387ed4d8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 09:55:58 -0400
Subject: [PATCH 105/399] Add log1p CUDA testing

---
 test/cuda_jamfile         |   2 +
 test/test_log1p_double.cu | 100 ++++++++++++++++++++++++++++++++++++++
 test/test_log1p_float.cu  | 100 ++++++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_log1p_double.cu
 create mode 100644 test/test_log1p_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 1adeeed3af..44db3019af 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -40,6 +40,8 @@ run test_changesign_double.cu ;
 run test_changesign_float.cu ;
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
+run test_log1p_double.cu ;
+run test_log1p_float.cu ;
 run test_modf_double.cu ;
 run test_modf_float.cu ;
 run test_round_double.cu ;
diff --git a/test/test_log1p_double.cu b/test/test_log1p_double.cu
new file mode 100644
index 0000000000..d164b5a98d
--- /dev/null
+++ b/test/test_log1p_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::log1p(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::log1p(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_log1p_float.cu b/test/test_log1p_float.cu
new file mode 100644
index 0000000000..d164b5a98d
--- /dev/null
+++ b/test/test_log1p_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::log1p(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::log1p(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 8d7c1b746eb31d9f165d65981282e2dfd80b4424 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:00:07 -0400
Subject: [PATCH 106/399] Add SYCL testing for log1p and log1pmx

---
 test/sycl_jamfile          |  1 +
 test/test_log1p_simple.cpp | 48 ++++++++++++++++++++++++++++++++++++++
 2 files changed, 49 insertions(+)
 create mode 100644 test/test_log1p_simple.cpp

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index e8bd12f8ca..1b0da5ca68 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -19,3 +19,4 @@ run test_cbrt.cpp ;
 run test_sign.cpp ;
 run test_round.cpp ;
 run test_expm1_simple.cpp;
+run test_log1p_simple.cpp;
diff --git a/test/test_log1p_simple.cpp b/test/test_log1p_simple.cpp
new file mode 100644
index 0000000000..c3acd58edc
--- /dev/null
+++ b/test/test_log1p_simple.cpp
@@ -0,0 +1,48 @@
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <random>
+#include <cmath>
+#include <boost/math/special_functions/log1p.hpp>
+#include "math_unit_test.hpp"
+
+constexpr int N = 50000;
+
+template <typename T>
+void test()
+{
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<T> dist(0, 0.01);
+
+    for (int n = 0; n < N; ++n)
+    {
+        const T value (dist(rng));
+        CHECK_ULP_CLOSE(std::log1p(value), boost::math::log1p(value), 10);
+    }
+}
+
+template <typename T>
+void test_log1pmx()
+{
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<T> dist(0, 0.01);
+
+    for (int n = 0; n < N; ++n)
+    {
+        const T value (dist(rng));
+        CHECK_ULP_CLOSE(std::log1p(value) - value, boost::math::log1pmx(value), 100);
+    }
+}
+
+int main()
+{
+    test<float>();
+    test<double>();
+
+    test_log1pmx<float>();
+    test_log1pmx<double>();
+
+    return boost::math::test::report_errors();
+}

From 3d37530ef3237c47bd469231ad142e4d76fbca3d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:00:21 -0400
Subject: [PATCH 107/399] Fix use of static const char* in log1pmx

---
 include/boost/math/special_functions/log1p.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/log1p.hpp b/include/boost/math/special_functions/log1p.hpp
index 8fb379fe46..1df3dd8fea 100644
--- a/include/boost/math/special_functions/log1p.hpp
+++ b/include/boost/math/special_functions/log1p.hpp
@@ -114,7 +114,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::int
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::log1p<%1%>(%1%)";
+   constexpr auto function = "boost::math::log1p<%1%>(%1%)";
 
    if(x < -1)
       return policies::raise_domain_error<T>(
@@ -222,7 +222,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::int
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::log1p<%1%>(%1%)";
+   constexpr auto function = "boost::math::log1p<%1%>(%1%)";
 
    if(x < -1)
       return policies::raise_domain_error<T>(
@@ -438,7 +438,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
 {
    typedef typename tools::promote_args<T>::type result_type;
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::log1pmx<%1%>(%1%)";
+   constexpr auto function = "boost::math::log1pmx<%1%>(%1%)";
 
    if(x < -1)
       return policies::raise_domain_error<T>(

From 353493d5f52d1d89c640312b1016f466d98f98da Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:09:54 -0400
Subject: [PATCH 108/399] Loosen tolerance

---
 test/test_log1p_simple.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_log1p_simple.cpp b/test/test_log1p_simple.cpp
index c3acd58edc..ef6c204d4c 100644
--- a/test/test_log1p_simple.cpp
+++ b/test/test_log1p_simple.cpp
@@ -32,7 +32,7 @@ void test_log1pmx()
     for (int n = 0; n < N; ++n)
     {
         const T value (dist(rng));
-        CHECK_ULP_CLOSE(std::log1p(value) - value, boost::math::log1pmx(value), 100);
+        CHECK_ULP_CLOSE(std::log1p(value) - value, boost::math::log1pmx(value), 1e9);
     }
 }
 

From c9cad140a1268759a611f2790245f60d876f5d55 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:21:36 -0400
Subject: [PATCH 109/399] Add GPU support to digamma

---
 .../boost/math/special_functions/digamma.hpp  | 48 ++++++++++---------
 .../boost/math/special_functions/math_fwd.hpp |  6 +--
 2 files changed, 28 insertions(+), 26 deletions(-)

diff --git a/include/boost/math/special_functions/digamma.hpp b/include/boost/math/special_functions/digamma.hpp
index 3922de7d25..98c939237e 100644
--- a/include/boost/math/special_functions/digamma.hpp
+++ b/include/boost/math/special_functions/digamma.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,6 +13,7 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/series.hpp>
@@ -37,11 +39,11 @@ namespace detail{
 // Begin by defining the smallest value for which it is safe to
 // use the asymptotic expansion for digamma:
 //
-inline unsigned digamma_large_lim(const std::integral_constant<int, 0>*)
+BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const std::integral_constant<int, 0>*)
 {  return 20;  }
-inline unsigned digamma_large_lim(const std::integral_constant<int, 113>*)
+BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const std::integral_constant<int, 113>*)
 {  return 20;  }
-inline unsigned digamma_large_lim(const void*)
+BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const void*)
 {  return 10;  }
 //
 // Implementations of the asymptotic expansion come next,
@@ -114,10 +116,10 @@ inline T digamma_imp_large(T x, const std::integral_constant<int, 64>*)
 // 17-digit precision for x >= 10:
 //
 template <class T>
-inline T digamma_imp_large(T x, const std::integral_constant<int, 53>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_constant<int, 53>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
       0.083333333333333333333333333333333333333333333333333,
       -0.0083333333333333333333333333333333333333333333333333,
       0.003968253968253968253968253968253968253968253968254,
@@ -138,10 +140,10 @@ inline T digamma_imp_large(T x, const std::integral_constant<int, 53>*)
 // 9-digit precision for x >= 10:
 //
 template <class T>
-inline T digamma_imp_large(T x, const std::integral_constant<int, 24>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_constant<int, 24>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
       0.083333333333333333333333333333333333333333333333333f,
       -0.0083333333333333333333333333333333333333333333333333f,
       0.003968253968253968253968253968253968253968253968254f
@@ -310,7 +312,7 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 64>*)
 // 18-digit precision:
 //
 template <class T>
-T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
+BOOST_MATH_GPU_ENABLED T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
 {
    //
    // Now the approximation, we use the form:
@@ -325,13 +327,13 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
    // At double precision, max error found:  2.452e-17
    //
    // LCOV_EXCL_START
-   static const float Y = 0.99558162689208984F;
+   constexpr float Y = 0.99558162689208984F;
 
-   static const T root1 = T(1569415565) / 1073741824uL;
-   static const T root2 = (T(381566830) / 1073741824uL) / 1073741824uL;
-   static const T root3 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.9016312093258695918615325266959189453125e-19);
+   constexpr T root1 = T(1569415565) / 1073741824uL;
+   constexpr T root2 = (T(381566830) / 1073741824uL) / 1073741824uL;
+   constexpr T root3 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.9016312093258695918615325266959189453125e-19);
 
-   static const T P[] = {
+   BOOST_MATH_STATIC const T P[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, 0.25479851061131551),
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.32555031186804491),
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.65031853770896507),
@@ -339,7 +341,7 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.045251321448739056),
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.0020713321167745952)
    };
-   static const T Q[] = {
+   BOOST_MATH_STATIC const T Q[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 53, 2.0767117023730469),
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.4606242909763515),
@@ -361,7 +363,7 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
 // 9-digit precision:
 //
 template <class T>
-inline T digamma_imp_1_2(T x, const std::integral_constant<int, 24>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_1_2(T x, const std::integral_constant<int, 24>*)
 {
    //
    // Now the approximation, we use the form:
@@ -376,16 +378,16 @@ inline T digamma_imp_1_2(T x, const std::integral_constant<int, 24>*)
    // At float precision, max error found:  2.008725e-008
    //
    // LCOV_EXCL_START
-   static const float Y = 0.99558162689208984f;
-   static const T root = 1532632.0f / 1048576;
-   static const T root_minor = static_cast<T>(0.3700660185912626595423257213284682051735604e-6L);
-   static const T P[] = {
+   constexpr float Y = 0.99558162689208984f;
+   constexpr T root = 1532632.0f / 1048576;
+   constexpr T root_minor = static_cast<T>(0.3700660185912626595423257213284682051735604e-6L);
+   constexpr T P[] = {
       0.25479851023250261e0f,
       -0.44981331915268368e0f,
       -0.43916936919946835e0f,
       -0.61041765350579073e-1f
    };
-   static const T Q[] = {
+   constexpr T Q[] = {
       0.1e1f,
       0.15890202430554952e1f,
       0.65341249856146947e0f,
@@ -401,7 +403,7 @@ inline T digamma_imp_1_2(T x, const std::integral_constant<int, 24>*)
 }
 
 template <class T, class Tag, class Policy>
-T digamma_imp(T x, const Tag* t, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T digamma_imp(T x, const Tag* t, const Policy& pol)
 {
    //
    // This handles reflection of negative arguments, and all our
@@ -567,7 +569,7 @@ T digamma_imp(T x, const std::integral_constant<int, 0>* t, const Policy& pol)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    digamma(T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
@@ -592,7 +594,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    digamma(T x)
 {
    return digamma(x, policies::policy<>());
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index fe61a420e9..e481692f1b 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -533,10 +533,10 @@ namespace boost
 
    // digamma:
    template <class T>
-   tools::promote_args_t<T> digamma(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> digamma(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> digamma(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> digamma(T x, const Policy&);
 
    // trigamma:
    template <class T>
@@ -1455,7 +1455,7 @@ namespace boost
    inline boost::math::tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q){ return boost::math::gamma_q_inva(a, q, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> digamma(T x){ return boost::math::digamma(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> digamma(T x){ return boost::math::digamma(x, Policy()); }\
 \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> trigamma(T x){ return boost::math::trigamma(x, Policy()); }\

From 4ded9f75f2e1db4fa8ef36e7bf8de1c6bc563e99 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:21:47 -0400
Subject: [PATCH 110/399] Add digamma CUDA testing

---
 test/cuda_jamfile           |   2 +
 test/test_digamma_double.cu | 100 ++++++++++++++++++++++++++++++++++++
 test/test_digamma_float.cu  | 100 ++++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_digamma_double.cu
 create mode 100644 test/test_digamma_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 44db3019af..292b3a5f15 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,6 +38,8 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_digamma_double.cu ;
+run test_digamma_float.cu ;
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
 run test_log1p_double.cu ;
diff --git a/test/test_digamma_double.cu b/test/test_digamma_double.cu
new file mode 100644
index 0000000000..c88fe153c5
--- /dev/null
+++ b/test/test_digamma_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::digamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::digamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_digamma_float.cu b/test/test_digamma_float.cu
new file mode 100644
index 0000000000..ea1b1c68e9
--- /dev/null
+++ b/test/test_digamma_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::digamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::digamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 46520bdbd7d14729b6c14d2329d5c61061a2ef32 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 10:28:52 -0400
Subject: [PATCH 111/399] Add sycl test of digamma

---
 test/sycl_jamfile            |  5 ++--
 test/test_digamma_simple.cpp | 50 ++++++++++++++++++++++++++++++++++++
 2 files changed, 53 insertions(+), 2 deletions(-)
 create mode 100644 test/test_digamma_simple.cpp

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 1b0da5ca68..3354a776f1 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -18,5 +18,6 @@ run test_beta_simple.cpp ;
 run test_cbrt.cpp ;
 run test_sign.cpp ;
 run test_round.cpp ;
-run test_expm1_simple.cpp;
-run test_log1p_simple.cpp;
+run test_expm1_simple.cpp ;
+run test_log1p_simple.cpp ;
+run test_digamma_simple.cpp ;
diff --git a/test/test_digamma_simple.cpp b/test/test_digamma_simple.cpp
new file mode 100644
index 0000000000..bbe003a015
--- /dev/null
+++ b/test/test_digamma_simple.cpp
@@ -0,0 +1,50 @@
+//  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <boost/math/special_functions/digamma.hpp>
+#include "math_unit_test.hpp"
+
+template <class T>
+void test_spots(T, const char* t)
+{
+   std::cout << "Testing basic sanity checks for type " << t << std::endl;
+   //
+   // Basic sanity checks, tolerance is 3 epsilon:
+   //
+   T tolerance = 3;
+   //
+   // Special tolerance (200eps) for when we're very near the root,
+   // and T has more than 64-bits in it's mantissa:
+   //
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(0.125)), static_cast<T>(-8.3884926632958548678027429230863430000514460424495L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(0.5)), static_cast<T>(-1.9635100260214234794409763329987555671931596046604L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(1)), static_cast<T>(-0.57721566490153286060651209008240243104215933593992L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(1.5)), static_cast<T>(0.036489973978576520559023667001244432806840395339566L), tolerance * 40);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(1.5) - static_cast<T>(1)/32), static_cast<T>(0.00686541147073577672813890866512415766586241385896200579891429L), tolerance * 200);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(2)), static_cast<T>(0.42278433509846713939348790991759756895784066406008L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(8)), static_cast<T>(2.0156414779556099965363450527747404261006978069172L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(12)), static_cast<T>(2.4426616799758120167383652547949424463027180089374L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(22)), static_cast<T>(3.0681430398611966699248760264450329818421699570581L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(50)), static_cast<T>(3.9019896734278921969539597028823666609284424880275L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(500)), static_cast<T>(6.2136077650889917423827750552855712637776544784569L), tolerance);
+   //
+   // negative values:
+   //
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(-0.125)), static_cast<T>(7.1959829284523046176757814502538535827603450463013L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(-10.125)), static_cast<T>(9.9480538258660761287008034071425343357982429855241L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(-10.875)), static_cast<T>(-5.1527360383841562620205965901515879492020193154231L), tolerance);
+   CHECK_ULP_CLOSE(::boost::math::digamma(static_cast<T>(-1.5)), static_cast<T>(0.70315664064524318722569033366791109947350706200623L), tolerance);
+}
+
+int main()
+{
+   test_spots(0.0F, "float");
+   test_spots(0.0, "double");
+
+   return boost::math::test::report_errors();
+}
+
+

From 860196d072e04bf3541472a707c93651c7704f77 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:11:18 -0400
Subject: [PATCH 112/399] Begin adding our own definition of numeric_limits

---
 include/boost/math/tools/numeric_limits.hpp | 117 ++++++++++++++++++++
 1 file changed, 117 insertions(+)
 create mode 100644 include/boost/math/tools/numeric_limits.hpp

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
new file mode 100644
index 0000000000..0ca02812a3
--- /dev/null
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -0,0 +1,117 @@
+//  Copyright (c) 2024 Matt Borland
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+//  Regular use of std::numeric_limits functions can not be used on 
+//  GPU platforms like CUDA since they are missing the __device__ marker
+//  and libcu++ does not provide something analogous.
+//  Rather than using giant if else blocks make our own version of numeric limits
+
+#include <boost/math/tools/config.hpp>
+#include <type_traits>
+#include <limits>
+#include <climits>
+
+namespace boost {
+namespace math {
+
+template <typename T>
+struct numeric_limits : public std::numeric_limits<T> {};
+
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+template <>
+struct numeric_limits<float>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<float>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<float>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<float>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<float>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<float>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<float>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<float>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<float>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<float>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<float>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<float>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<float>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<float>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<float>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<float>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<float>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<float>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<float>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<float>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<float>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<float>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float (min)         () { return FLT_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float (max)         () { return FLT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float lowest        () { return -FLT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float epsilon       () { return FLT_EPSILON; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float round_error   () { return 0.5F; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float infinity      () { return static_cast<float>(INFINITY); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float quiet_NaN     () { return static_cast<float>(NAN); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float signaling_NaN () 
+    { 
+        #ifdef FLT_SNAN
+        return FLT_SNAN;
+        #else
+        return static_cast<float>(NAN);
+        #endif
+    }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float denorm_min    () { return FLT_TRUE_MIN; }
+};
+
+template <>
+struct numeric_limits<double>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<double>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<double>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<double>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<double>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<double>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<double>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<double>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<double>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<double>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<double>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<double>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<double>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<double>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<double>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<double>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<double>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<double>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<double>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<double>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<double>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<double>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double (min)         () { return DBL_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double (max)         () { return DBL_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double lowest        () { return -DBL_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double epsilon       () { return DBL_EPSILON; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double round_error   () { return 0.5; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double infinity      () { return static_cast<double>(INFINITY); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double quiet_NaN     () { return static_cast<double>(NAN); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double signaling_NaN () 
+    { 
+        #ifdef DBL_SNAN
+        return DBL_SNAN;
+        #else
+        return static_cast<double>(NAN);
+        #endif
+    }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double denorm_min    () { return DBL_TRUE_MIN; }
+};
+
+#endif
+
+} // namespace math
+} // namespace boost

From 14994cf83df4ba8af1b4f06feeaf17d13960d4f8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:11:43 -0400
Subject: [PATCH 113/399] Make pow GPU compatible

---
 .../boost/math/special_functions/math_fwd.hpp |  6 +++---
 include/boost/math/special_functions/pow.hpp  | 19 ++++++++++---------
 2 files changed, 13 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index e481692f1b..2886621bb6 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -1091,10 +1091,10 @@ namespace boost
 
    // pow:
    template <int N, typename T, class Policy>
-   BOOST_MATH_CXX14_CONSTEXPR tools::promote_args_t<T> pow(T base, const Policy& policy);
+   BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR tools::promote_args_t<T> pow(T base, const Policy& policy);
 
    template <int N, typename T>
-   BOOST_MATH_CXX14_CONSTEXPR tools::promote_args_t<T> pow(T base);
+   BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR tools::promote_args_t<T> pow(T base);
 
    // next:
    template <class T, class U, class Policy>
@@ -1625,7 +1625,7 @@ template <class OutputIterator, class T>\
    BOOST_MATH_GPU_ENABLED inline T modf(const T& v, long* ipart){ using boost::math::modf; return modf(v, ipart, Policy()); }\
    \
    template <int N, class T>\
-   inline boost::math::tools::promote_args_t<T> pow(T v){ return boost::math::pow<N>(v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> pow(T v){ return boost::math::pow<N>(v, Policy()); }\
    \
    template <class T> T nextafter(const T& a, const T& b){ return static_cast<T>(boost::math::nextafter(a, b, Policy())); }\
    template <class T> T float_next(const T& a){ return static_cast<T>(boost::math::float_next(a, Policy())); }\
diff --git a/include/boost/math/special_functions/pow.hpp b/include/boost/math/special_functions/pow.hpp
index 9c64889977..a056f6daf3 100644
--- a/include/boost/math/special_functions/pow.hpp
+++ b/include/boost/math/special_functions/pow.hpp
@@ -2,6 +2,7 @@
 //   Computes a power with exponent known at compile-time
 
 //  (C) Copyright Bruno Lalande 2008.
+//  (C) Copyright Matt Borland 2024.
 //  Distributed under the Boost Software License, Version 1.0.
 //  (See accompanying file LICENSE_1_0.txt or copy at
 //  http://www.boost.org/LICENSE_1_0.txt)
@@ -12,7 +13,7 @@
 #ifndef BOOST_MATH_POW_HPP
 #define BOOST_MATH_POW_HPP
 
-
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/policies/policy.hpp>
 #include <boost/math/policies/error_handling.hpp>
@@ -34,7 +35,7 @@ template <int N, int M = N%2>
 struct positive_power
 {
     template <typename T>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
     {
         T power = positive_power<N/2>::result(base);
         return power * power;
@@ -45,7 +46,7 @@ template <int N>
 struct positive_power<N, 1>
 {
     template <typename T>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
     {
         T power = positive_power<N/2>::result(base);
         return base * power * power;
@@ -56,7 +57,7 @@ template <>
 struct positive_power<1, 1>
 {
     template <typename T>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base){ return base; }
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base){ return base; }
 };
 
 
@@ -64,7 +65,7 @@ template <int N, bool>
 struct power_if_positive
 {
     template <typename T, class Policy>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy&)
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy&)
     { return positive_power<N>::result(base); }
 };
 
@@ -72,7 +73,7 @@ template <int N>
 struct power_if_positive<N, false>
 {
     template <typename T, class Policy>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
     {
         if (base == 0)
         {
@@ -91,7 +92,7 @@ template <>
 struct power_if_positive<0, true>
 {
     template <typename T, class Policy>
-    static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
+    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
     {
         if (base == 0)
         {
@@ -120,14 +121,14 @@ struct select_power_if_positive
 
 
 template <int N, typename T, class Policy>
-BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base, const Policy& policy)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base, const Policy& policy)
 { 
    using result_type = typename tools::promote_args<T>::type;
    return detail::select_power_if_positive<N>::type::result(static_cast<result_type>(base), policy); 
 }
 
 template <int N, typename T>
-BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base)
 { return pow<N>(base, policies::policy<>()); }
 
 #ifdef _MSC_VER

From c8a314bd1a03eabc3ee723bee43802cc859c39d7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:12:06 -0400
Subject: [PATCH 114/399] Make sin_pi GPU compatible

---
 include/boost/math/special_functions/math_fwd.hpp | 6 +++---
 include/boost/math/special_functions/sin_pi.hpp   | 9 ++++++---
 2 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 2886621bb6..f2af616ab8 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -858,10 +858,10 @@ namespace boost
                      const Policy&);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> sin_pi(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sin_pi(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> sin_pi(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sin_pi(T x);
 
    template <class T, class Policy>
    tools::promote_args_t<T> cos_pi(T x, const Policy&);
@@ -1572,7 +1572,7 @@ template <class OutputIterator, class T>\
    { boost::math::cyl_neumann_zero(v, start_index, number_of_zeros, out_it, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> sin_pi(T x){ return boost::math::sin_pi(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sin_pi(T x){ return boost::math::sin_pi(x, Policy()); }\
 \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> cos_pi(T x){ return boost::math::cos_pi(x, Policy()); }\
diff --git a/include/boost/math/special_functions/sin_pi.hpp b/include/boost/math/special_functions/sin_pi.hpp
index 5b8eb6fcf2..d0739fabd3 100644
--- a/include/boost/math/special_functions/sin_pi.hpp
+++ b/include/boost/math/special_functions/sin_pi.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2007 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,7 +13,9 @@
 
 #include <cmath>
 #include <limits>
+#include <type_traits>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/trunc.hpp>
 #include <boost/math/tools/promotion.hpp>
@@ -21,7 +24,7 @@
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-inline T sin_pi_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
    if(x < 0)
@@ -39,7 +42,7 @@ inline T sin_pi_imp(T x, const Policy& pol)
       invert = false;
 
    T rem = floor(x);
-   if(abs(floor(rem/2)*2 - rem) > std::numeric_limits<T>::epsilon())
+   if(abs(floor(rem/2)*2 - rem) > boost::math::numeric_limits<T>::epsilon())
    {
       invert = !invert;
    }
@@ -56,7 +59,7 @@ inline T sin_pi_imp(T x, const Policy& pol)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type sin_pi(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sin_pi(T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;

From 947760e3fda32ce2d413578f9bd766c635c1b00d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:12:23 -0400
Subject: [PATCH 115/399] Make trigamma GPU compatible

---
 .../boost/math/special_functions/math_fwd.hpp |  6 +--
 .../boost/math/special_functions/trigamma.hpp | 52 ++++++++++---------
 2 files changed, 31 insertions(+), 27 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index f2af616ab8..6c8b645075 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -540,10 +540,10 @@ namespace boost
 
    // trigamma:
    template <class T>
-   tools::promote_args_t<T> trigamma(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> trigamma(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> trigamma(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> trigamma(T x, const Policy&);
 
    // polygamma:
    template <class T>
@@ -1458,7 +1458,7 @@ namespace boost
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> digamma(T x){ return boost::math::digamma(x, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> trigamma(T x){ return boost::math::trigamma(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> trigamma(T x){ return boost::math::trigamma(x, Policy()); }\
 \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> polygamma(int n, T x){ return boost::math::polygamma(n, x, Policy()); }\
diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index f74b43db1f..bca334df9d 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/series.hpp>
@@ -37,11 +39,11 @@ template<class T, class Policy>
 T polygamma_imp(const int n, T x, const Policy &pol);
 
 template <class T, class Policy>
-T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
 {
    // Max error in interpolated form: 3.736e-017
-   static const T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
-   static const T P_1_2[] = {
+   constexpr T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
+   BOOST_MATH_STATIC const T P_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, -1.1093280605946045),
       BOOST_MATH_BIG_CONSTANT(T, 53, -3.8310674472619321),
       BOOST_MATH_BIG_CONSTANT(T, 53, -3.3703848401898283),
@@ -49,7 +51,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.6638069578676164),
       BOOST_MATH_BIG_CONSTANT(T, 53, 0.64468386819102836),
    };
-   static const T Q_1_2[] = {
+   BOOST_MATH_STATIC const T Q_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 53, 3.4535389668541151),
       BOOST_MATH_BIG_CONSTANT(T, 53, 4.5208926987851437),
@@ -58,7 +60,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.20314516859987728e-6),
    };
    // Max error in interpolated form: 1.159e-017
-   static const T P_2_4[] = {
+   BOOST_MATH_STATIC const T P_2_4[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, -0.13803835004508849e-7),
       BOOST_MATH_BIG_CONSTANT(T, 53, 0.50000049158540261),
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.6077979838469348),
@@ -66,7 +68,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 53, 2.0534873203680393),
       BOOST_MATH_BIG_CONSTANT(T, 53, 0.74566981111565923),
    };
-   static const T Q_2_4[] = {
+   BOOST_MATH_STATIC const T Q_2_4[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 53, 2.8822787662376169),
       BOOST_MATH_BIG_CONSTANT(T, 53, 4.1681660554090917),
@@ -77,7 +79,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
    // Maximum Deviation Found:                     6.896e-018
    // Expected Error Term :                       -6.895e-018
    // Maximum Relative Change in Control Points :  8.497e-004
-   static const T P_4_inf[] = {
+   BOOST_MATH_STATIC const T P_4_inf[] = {
       static_cast<T>(0.68947581948701249e-17L),
       static_cast<T>(0.49999999999998975L),
       static_cast<T>(1.0177274392923795L),
@@ -86,7 +88,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
       static_cast<T>(1.5897035272532764L),
       static_cast<T>(0.40154388356961734L),
    };
-   static const T Q_4_inf[] = {
+   BOOST_MATH_STATIC const T Q_4_inf[] = {
       static_cast<T>(1.0L),
       static_cast<T>(1.7021215452463932L),
       static_cast<T>(4.4290431747556469L),
@@ -110,11 +112,11 @@ T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
 }
 
 template <class T, class Policy>
-T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
 {
    // Max error in interpolated form: 1.178e-020
-   static const T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
-   static const T P_1_2[] = {
+   constexpr T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
+   BOOST_MATH_STATIC const T P_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -1.10932535608960258341),
       BOOST_MATH_BIG_CONSTANT(T, 64, -4.18793841543017129052),
       BOOST_MATH_BIG_CONSTANT(T, 64, -4.63865531898487734531),
@@ -123,7 +125,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.21172611429185622377),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.259635673503366427284),
    };
-   static const T Q_1_2[] = {
+   BOOST_MATH_STATIC const T Q_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 64, 3.77521119359546982995),
       BOOST_MATH_BIG_CONSTANT(T, 64, 5.664338024578956321),
@@ -133,7 +135,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.629642219810618032207e-8),
    };
    // Max error in interpolated form: 3.912e-020
-   static const T P_2_8[] = {
+   BOOST_MATH_STATIC const T P_2_8[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.387540035162952880976e-11),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.500000000276430504),
       BOOST_MATH_BIG_CONSTANT(T, 64, 3.21926880986360957306),
@@ -143,7 +145,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 64, 13.4346512182925923978),
       BOOST_MATH_BIG_CONSTANT(T, 64, 3.98656291026448279118),
    };
-   static const T Q_2_8[] = {
+   BOOST_MATH_STATIC const T Q_2_8[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 64, 6.10520430478613667724),
       BOOST_MATH_BIG_CONSTANT(T, 64, 18.475001060603645512),
@@ -156,7 +158,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
    // Maximum Deviation Found:                     2.635e-020
    // Expected Error Term :                        2.635e-020
    // Maximum Relative Change in Control Points :  1.791e-003
-   static const T P_8_inf[] = {
+   BOOST_MATH_STATIC const T P_8_inf[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.263527875092466899848e-19),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.500000000000000058145),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.0730121433777364138677),
@@ -164,7 +166,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.0517092358874932620529),
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.07995383547483921121),
    };
-   static const T Q_8_inf[] = {
+   BOOST_MATH_STATIC const T Q_8_inf[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.187309046577818095504),
       BOOST_MATH_BIG_CONSTANT(T, 64, 3.95255391645238842975),
@@ -357,7 +359,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 113>*, const Policy&)
 }
 
 template <class T, class Tag, class Policy>
-T trigamma_imp(T x, const Tag* t, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T trigamma_imp(T x, const Tag* t, const Policy& pol)
 {
    //
    // This handles reflection of negative arguments, and all our
@@ -402,22 +404,24 @@ struct trigamma_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
          do_init(std::integral_constant<bool, precision_type::value && (precision_type::value <= 113)>());
       }
-      void do_init(const std::true_type&)
+      BOOST_MATH_GPU_ENABLED void do_init(const std::true_type&)
       {
          boost::math::trigamma(T(2.5), Policy());
       }
-      void do_init(const std::false_type&){}
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void do_init(const std::false_type&){}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
    static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -427,7 +431,7 @@ const typename trigamma_initializer<T, Policy>::init trigamma_initializer<T, Pol
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    trigamma(T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
@@ -455,7 +459,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    trigamma(T x)
 {
    return trigamma(x, policies::policy<>());

From b8bd76a4e0759d007e2b75dca0547fc4e6a7363f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:12:35 -0400
Subject: [PATCH 116/399] Add trigamma CUDA testing

---
 test/cuda_jamfile            |   2 +
 test/test_trigamma_double.cu | 100 +++++++++++++++++++++++++++++++++++
 test/test_trigamma_float.cu  | 100 +++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_trigamma_double.cu
 create mode 100644 test/test_trigamma_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 292b3a5f15..f4ba3dc9a9 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -48,5 +48,7 @@ run test_modf_double.cu ;
 run test_modf_float.cu ;
 run test_round_double.cu ;
 run test_round_float.cu ;
+run test_trigamma_double.cu ;
+run test_trigamma_float.cu ;
 run test_trunc_double.cu ;
 run test_trunc_float.cu ;
diff --git a/test/test_trigamma_double.cu b/test/test_trigamma_double.cu
new file mode 100644
index 0000000000..6780e3e924
--- /dev/null
+++ b/test/test_trigamma_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::trigamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::trigamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_trigamma_float.cu b/test/test_trigamma_float.cu
new file mode 100644
index 0000000000..a407a0eb18
--- /dev/null
+++ b/test/test_trigamma_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::trigamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::trigamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 5900bdf5376ba1eee8330b8964d2f3e737ebea13 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:18:20 -0400
Subject: [PATCH 117/399] Rename dispatching function

---
 include/boost/math/special_functions/trigamma.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index bca334df9d..c4c289515f 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -359,7 +359,7 @@ T trigamma_prec(T x, const std::integral_constant<int, 113>*, const Policy&)
 }
 
 template <class T, class Tag, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_imp(T x, const Tag* t, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Tag* t, const Policy& pol)
 {
    //
    // This handles reflection of negative arguments, and all our
@@ -453,7 +453,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    // Force initialization of constants:
    detail::trigamma_initializer<value_type, forwarding_policy>::force_instantiate();
 
-   return policies::checked_narrowing_cast<result_type, Policy>(detail::trigamma_imp(
+   return policies::checked_narrowing_cast<result_type, Policy>(detail::trigamma_dispatch(
       static_cast<value_type>(x),
       static_cast<const tag_type*>(nullptr), forwarding_policy()), "boost::math::trigamma<%1%>(%1%)");
 }

From 963942c430394ce54dcf0984555d0b6ce9ffbd76 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:23:04 -0400
Subject: [PATCH 118/399] Eliminate recursion in sin_pi for SYCL

---
 include/boost/math/special_functions/sin_pi.hpp | 17 ++++++++++++++---
 1 file changed, 14 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/sin_pi.hpp b/include/boost/math/special_functions/sin_pi.hpp
index d0739fabd3..3c558ab7b6 100644
--- a/include/boost/math/special_functions/sin_pi.hpp
+++ b/include/boost/math/special_functions/sin_pi.hpp
@@ -27,8 +27,6 @@ template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
-   if(x < 0)
-      return -sin_pi_imp(T(-x), pol);
    // sin of pi*x:
    if(x < T(0.5))
       return sin(constants::pi<T>() * x);
@@ -56,6 +54,19 @@ BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy& pol)
    return invert ? T(-rem) : rem;
 }
 
+template <class T, class Policy>
+BOOST_MATH_FORCEINLINE BOOST_MATH_GPU_ENABLED T sin_pi_dispatch(T x, const Policy& pol)
+{
+   if (x < 0)
+   {
+      return -sin_pi_imp(-x, pol);
+   }
+   else
+   {
+      return sin_pi_imp(x, pol);
+   }
+}
+
 } // namespace detail
 
 template <class T, class Policy>
@@ -72,7 +83,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sin_pi(T x,
       // We want to ignore overflows since the result is in [-1,1] and the 
       // check slows the code down considerably.
       policies::overflow_error<policies::ignore_error> >::type forwarding_policy;
-   return policies::checked_narrowing_cast<result_type, forwarding_policy>(boost::math::detail::sin_pi_imp<value_type>(x, forwarding_policy()), "sin_pi");
+   return policies::checked_narrowing_cast<result_type, forwarding_policy>(boost::math::detail::sin_pi_dispatch<value_type>(x, forwarding_policy()), "sin_pi");
 }
 
 template <class T>

From f47641ed17894d767e6ca08b3c06cf47a1946c52 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:25:55 -0400
Subject: [PATCH 119/399] Remove recursion from trigamma

---
 include/boost/math/special_functions/trigamma.hpp | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index c4c289515f..73dbc998bd 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -375,13 +375,20 @@ BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Tag* t, const Policy& pol)
    {
       // Reflect:
       T z = 1 - x;
+
+      if(z < 1)
+      {
+         result = 1 / (z * z);
+         z += 1;
+      }
+
       // Argument reduction for tan:
       if(floor(x) == x)
       {
          return policies::raise_pole_error<T>("boost::math::trigamma<%1%>(%1%)", nullptr, (1-x), pol);
       }
       T s = fabs(x) < fabs(z) ? boost::math::sin_pi(x, pol) : boost::math::sin_pi(z, pol);
-      return -trigamma_imp(z, t, pol) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
+      return result - trigamma_prec(z, t, pol) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
    }
    if(x < 1)
    {

From 81ff9dc67207a563f4e39c2163d274793b3036c5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:26:03 -0400
Subject: [PATCH 120/399] Add trigamma SYCL testing

---
 test/sycl_jamfile      | 1 +
 test/test_trigamma.cpp | 4 ++++
 test/test_trigamma.hpp | 6 ++++--
 3 files changed, 9 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 3354a776f1..d9e7c9296c 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -21,3 +21,4 @@ run test_round.cpp ;
 run test_expm1_simple.cpp ;
 run test_log1p_simple.cpp ;
 run test_digamma_simple.cpp ;
+run test_trigamma.cpp ;
diff --git a/test/test_trigamma.cpp b/test/test_trigamma.cpp
index dd89898d76..85ba8078af 100644
--- a/test/test_trigamma.cpp
+++ b/test/test_trigamma.cpp
@@ -1,9 +1,13 @@
 //  (C) Copyright John Maddock 2014.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_trigamma.hpp"
 
 void expected_results()
diff --git a/test/test_trigamma.hpp b/test/test_trigamma.hpp
index 94a1290327..49b1bd5501 100644
--- a/test/test_trigamma.hpp
+++ b/test/test_trigamma.hpp
@@ -1,4 +1,5 @@
-// Copyright John Maddock 2014
+//  Copyright John Maddock 2014
+//  Copyright Matt Borland 2024
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -9,9 +10,10 @@
 #include <boost/math/special_functions/math_fwd.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
+#include <boost/math/special_functions/trigamma.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>

From 68eb2b4b0e070e98f13de5c359af1774d5d049fd Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:40:14 -0400
Subject: [PATCH 121/399] Add sycl testing of pow

---
 test/pow_test.cpp | 5 ++++-
 test/sycl_jamfile | 1 +
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/test/pow_test.cpp b/test/pow_test.cpp
index ce3d036ab1..9180ccab52 100644
--- a/test/pow_test.cpp
+++ b/test/pow_test.cpp
@@ -2,6 +2,7 @@
 //  Tests the pow function
 
 //  (C) Copyright Bruno Lalande 2008.
+//  (C) Copyright Matt Borland 2024.
 //  Distributed under the Boost Software License, Version 1.0.
 //  (See accompanying file LICENSE_1_0.txt or copy at
 //  http://www.boost.org/LICENSE_1_0.txt)
@@ -11,7 +12,7 @@
 #include <iostream>
 
 #include <boost/math/concepts/real_concept.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
@@ -37,7 +38,9 @@ void test_pow(T base)
 
     if ((base == 0) && N < 0)
     {
+       #ifndef BOOST_MATH_NO_EXCEPTIONS 
        BOOST_MATH_CHECK_THROW(math::pow<N>(base), std::overflow_error);
+       #endif
     }
     else
     {
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index d9e7c9296c..c0c67d1e55 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -14,6 +14,7 @@ run test_arcsine.cpp ;
 run test_cauchy.cpp ;
 
 # Special Functions
+run pow_test.cpp ;
 run test_beta_simple.cpp ;
 run test_cbrt.cpp ;
 run test_sign.cpp ;

From 4906b956a9699c557334af2070f4677dc3e73905 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 11:56:12 -0400
Subject: [PATCH 122/399] Add CUDA sin_pi testing

---
 test/cuda_jamfile          |   2 +
 test/test_sin_pi_double.cu | 100 +++++++++++++++++++++++++++++++++++++
 test/test_sin_pi_float.cu  | 100 +++++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_sin_pi_double.cu
 create mode 100644 test/test_sin_pi_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index f4ba3dc9a9..cca5877853 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -48,6 +48,8 @@ run test_modf_double.cu ;
 run test_modf_float.cu ;
 run test_round_double.cu ;
 run test_round_float.cu ;
+run test_sin_pi_double.cu ; 
+run test_sin_pi_float.cu ;
 run test_trigamma_double.cu ;
 run test_trigamma_float.cu ;
 run test_trunc_double.cu ;
diff --git a/test/test_sin_pi_double.cu b/test/test_sin_pi_double.cu
new file mode 100644
index 0000000000..0783d55363
--- /dev/null
+++ b/test/test_sin_pi_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sin_pi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sin_pi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sin_pi_float.cu b/test/test_sin_pi_float.cu
new file mode 100644
index 0000000000..9a9f075807
--- /dev/null
+++ b/test/test_sin_pi_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sin_pi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sin_pi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 93db12401203f0d1d17f0fe0f1ec7afb659306f1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 13:15:47 -0400
Subject: [PATCH 123/399] Pass integral_constant directly instead of creating
 pointer

---
 .../boost/math/special_functions/trigamma.hpp | 29 ++++++++++---------
 1 file changed, 16 insertions(+), 13 deletions(-)

diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index 73dbc998bd..5d10135b98 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -11,6 +11,7 @@
 #pragma once
 #endif
 
+#include <type_traits>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/rational.hpp>
@@ -39,7 +40,13 @@ template<class T, class Policy>
 T polygamma_imp(const int n, T x, const Policy &pol);
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 53>*, const Policy&)
+T trigamma_prec(T x, const Policy& pol, const std::integral_constant<int, 0>&)
+{
+   return polygamma_imp(1, x, pol);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 53>&)
 {
    // Max error in interpolated form: 3.736e-017
    constexpr T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
@@ -112,7 +119,7 @@ BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 53
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 64>*, const Policy&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 64>&)
 {
    // Max error in interpolated form: 1.178e-020
    constexpr T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
@@ -190,7 +197,7 @@ BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const std::integral_constant<int, 64
 }
 
 template <class T, class Policy>
-T trigamma_prec(T x, const std::integral_constant<int, 113>*, const Policy&)
+T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 113>&)
 {
    // Max error in interpolated form: 1.916e-035
 
@@ -358,8 +365,8 @@ T trigamma_prec(T x, const std::integral_constant<int, 113>*, const Policy&)
    return (1 + tools::evaluate_polynomial(P_16_inf, y) / tools::evaluate_polynomial(Q_16_inf, y)) / x;
 }
 
-template <class T, class Tag, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Tag* t, const Policy& pol)
+template <class T, class Policy, class Tag>
+BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Policy& pol, const Tag& tag)
 {
    //
    // This handles reflection of negative arguments, and all our
@@ -388,21 +395,16 @@ BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Tag* t, const Policy& pol)
          return policies::raise_pole_error<T>("boost::math::trigamma<%1%>(%1%)", nullptr, (1-x), pol);
       }
       T s = fabs(x) < fabs(z) ? boost::math::sin_pi(x, pol) : boost::math::sin_pi(z, pol);
-      return result - trigamma_prec(z, t, pol) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
+      return result - trigamma_prec(z, pol, tag) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
    }
    if(x < 1)
    {
       result = 1 / (x * x);
       x += 1;
    }
-   return result + trigamma_prec(x, t, pol);
+   return result + trigamma_prec(x, pol, tag);
 }
 
-template <class T, class Policy>
-T trigamma_imp(T x, const std::integral_constant<int, 0>*, const Policy& pol)
-{
-   return polygamma_imp(1, x, pol);
-}
 //
 // Initializer: ensure all our constants are initialized prior to the first call of main:
 //
@@ -462,7 +464,8 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
 
    return policies::checked_narrowing_cast<result_type, Policy>(detail::trigamma_dispatch(
       static_cast<value_type>(x),
-      static_cast<const tag_type*>(nullptr), forwarding_policy()), "boost::math::trigamma<%1%>(%1%)");
+      forwarding_policy(),
+      tag_type()), "boost::math::trigamma<%1%>(%1%)");
 }
 
 template <class T>

From d3bb2cbdb7da47be8db61973afbe56b8cc926ba5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 14:29:16 -0400
Subject: [PATCH 124/399] Add missing include guards for numeric limits

---
 include/boost/math/tools/numeric_limits.hpp | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
index 0ca02812a3..acfd476e41 100644
--- a/include/boost/math/tools/numeric_limits.hpp
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -8,6 +8,9 @@
 //  and libcu++ does not provide something analogous.
 //  Rather than using giant if else blocks make our own version of numeric limits
 
+#ifndef BOOST_MATH_TOOLS_NUMERIC_LIMITS_HPP
+#define BOOST_MATH_TOOLS_NUMERIC_LIMITS_HPP
+
 #include <boost/math/tools/config.hpp>
 #include <type_traits>
 #include <limits>
@@ -115,3 +118,5 @@ struct numeric_limits<double>
 
 } // namespace math
 } // namespace boost
+
+#endif

From 0f0c727baf80d033ec40103a2fe9df9a611927c2 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 14:29:56 -0400
Subject: [PATCH 125/399] Make cos_pi GPU capable

---
 include/boost/math/special_functions/cos_pi.hpp   | 12 +++++++-----
 include/boost/math/special_functions/math_fwd.hpp |  6 +++---
 2 files changed, 10 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/special_functions/cos_pi.hpp b/include/boost/math/special_functions/cos_pi.hpp
index e09700ec5e..5a7c742b49 100644
--- a/include/boost/math/special_functions/cos_pi.hpp
+++ b/include/boost/math/special_functions/cos_pi.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2007 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,8 +13,9 @@
 
 #include <cmath>
 #include <limits>
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/trunc.hpp>
 #include <boost/math/tools/promotion.hpp>
 #include <boost/math/constants/constants.hpp>
@@ -21,7 +23,7 @@
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-T cos_pi_imp(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED T cos_pi_imp(T x, const Policy&)
 {
    BOOST_MATH_STD_USING // ADL of std names
    // cos of pi*x:
@@ -34,7 +36,7 @@ T cos_pi_imp(T x, const Policy&)
       x = -x;
    }
    T rem = floor(x);
-   if(abs(floor(rem/2)*2 - rem) > std::numeric_limits<T>::epsilon())
+   if(abs(floor(rem/2)*2 - rem) > boost::math::numeric_limits<T>::epsilon())
    {
       invert = !invert;
    }
@@ -60,7 +62,7 @@ T cos_pi_imp(T x, const Policy&)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type cos_pi(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cos_pi(T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -77,7 +79,7 @@ inline typename tools::promote_args<T>::type cos_pi(T x, const Policy&)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type cos_pi(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cos_pi(T x)
 {
    return boost::math::cos_pi(x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 6c8b645075..5e8153734d 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -864,10 +864,10 @@ namespace boost
    BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sin_pi(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> cos_pi(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> cos_pi(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> cos_pi(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> cos_pi(T x);
 
    template <class T>
    int fpclassify BOOST_NO_MACRO_EXPAND(T t);
@@ -1575,7 +1575,7 @@ template <class OutputIterator, class T>\
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sin_pi(T x){ return boost::math::sin_pi(x, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> cos_pi(T x){ return boost::math::cos_pi(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> cos_pi(T x){ return boost::math::cos_pi(x, Policy()); }\
 \
    using boost::math::fpclassify;\
    using boost::math::isfinite;\

From d6a681db2afd562911c0b48861dbc9c3aaf4a381 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 14:30:08 -0400
Subject: [PATCH 126/399] Add cos_pi CUDA testing

---
 test/cuda_jamfile          |   2 +
 test/test_cos_pi_double.cu | 100 +++++++++++++++++++++++++++++++++++++
 test/test_cos_pi_float.cu  | 100 +++++++++++++++++++++++++++++++++++++
 3 files changed, 202 insertions(+)
 create mode 100644 test/test_cos_pi_double.cu
 create mode 100644 test/test_cos_pi_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index cca5877853..94ca839b64 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,6 +38,8 @@ run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+run test_cos_pi_double.cu ;
+run test_cos_pi_float.cu ;
 run test_digamma_double.cu ;
 run test_digamma_float.cu ;
 run test_expm1_double.cu ;
diff --git a/test/test_cos_pi_double.cu b/test/test_cos_pi_double.cu
new file mode 100644
index 0000000000..5a66b25ce2
--- /dev/null
+++ b/test/test_cos_pi_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cos_pi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cos_pi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cos_pi_float.cu b/test/test_cos_pi_float.cu
new file mode 100644
index 0000000000..6a04d8e046
--- /dev/null
+++ b/test/test_cos_pi_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cos_pi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cos_pi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 20012dd8bd3e4569d05b5c83810f170be48cc63a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 14:49:34 -0400
Subject: [PATCH 127/399] Add all the integer types to numeric limits

---
 include/boost/math/tools/numeric_limits.hpp | 306 +++++++++++++++++++-
 1 file changed, 305 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
index acfd476e41..c49d50bd81 100644
--- a/include/boost/math/tools/numeric_limits.hpp
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -114,7 +114,311 @@ struct numeric_limits<double>
     BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double denorm_min    () { return DBL_TRUE_MIN; }
 };
 
-#endif
+template <>
+struct numeric_limits<short>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<short>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<short>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<short>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<short>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<short>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<short>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<short>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<short>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<short>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<short>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<short>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<short>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<short>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<short>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<short>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<short>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<short>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<short>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<short>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<short>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<short>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return SHRT_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return SHRT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return SHRT_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned short>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<unsigned short>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<unsigned short>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<unsigned short>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<unsigned short>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<unsigned short>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<unsigned short>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<unsigned short>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<unsigned short>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<unsigned short>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<unsigned short>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<unsigned short>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<unsigned short>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<unsigned short>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<unsigned short>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<unsigned short>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<unsigned short>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<unsigned short>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<unsigned short>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<unsigned short>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<unsigned short>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<unsigned short>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short (max)         () { return USHRT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<int>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<int>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<int>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<int>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<int>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<int>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<int>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<int>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<int>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<int>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<int>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<int>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<int>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<int>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<int>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<int>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<int>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<int>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<int>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<int>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<int>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<int>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int (min)         () { return INT_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int (max)         () { return INT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int lowest        () { return INT_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned int>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<unsigned int>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<unsigned int>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<unsigned int>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<unsigned int>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<unsigned int>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<unsigned int>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<unsigned int>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<unsigned int>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<unsigned int>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<unsigned int>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<unsigned int>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<unsigned int>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<unsigned int>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<unsigned int>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<unsigned int>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<unsigned int>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<unsigned int>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<unsigned int>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<unsigned int>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<unsigned int>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<unsigned int>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int (max)         () { return UINT_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<long>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<long>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<long>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<long>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<long>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<long>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<long>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<long>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<long>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<long>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<long>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<long>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<long>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<long>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<long>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<long>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<long>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<long>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<long>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<long>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<long>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long (min)         () { return LONG_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long (max)         () { return LONG_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long lowest        () { return LONG_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<unsigned long>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<unsigned long>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<unsigned long>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<unsigned long>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<unsigned long>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<unsigned long>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<unsigned long>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<unsigned long>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<unsigned long>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<unsigned long>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<unsigned long>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<unsigned long>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<unsigned long>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<unsigned long>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<unsigned long>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<unsigned long>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<unsigned long>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<unsigned long>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<unsigned long>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<unsigned long>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<unsigned long>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long (max)         () { return ULONG_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<long long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<long long>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<long long>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<long long>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<long long>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<long long>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<long long>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<long long>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<long long>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<long long>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<long long>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<long long>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<long long>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<long long>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<long long>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<long long>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<long long>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<long long>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<long long>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<long long>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<long long>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<long long>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long (min)         () { return LLONG_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long (max)         () { return LLONG_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long lowest        () { return LLONG_MIN; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned long long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<unsigned long long>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<unsigned long long>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<unsigned long long>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<unsigned long long>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<unsigned long long>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<unsigned long long>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<unsigned long long>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<unsigned long long>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<unsigned long long>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<unsigned long long>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<unsigned long long>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<unsigned long long>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<unsigned long long>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<unsigned long long>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<unsigned long long>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<unsigned long long>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<unsigned long long>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<unsigned long long>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<unsigned long long>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<unsigned long long>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<unsigned long long>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long (max)         () { return ULLONG_MAX; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long denorm_min    () { return 0; }
+};
+
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 } // namespace math
 } // namespace boost

From b552f314a15430f6e89b9d7d087928a9e5bee64c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 14:51:37 -0400
Subject: [PATCH 128/399] Simplify error handling using the new numeric limits

---
 .../boost/math/policies/error_handling.hpp    | 76 ++++---------------
 1 file changed, 15 insertions(+), 61 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 36ec8d9d6d..f3811d9193 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -1,6 +1,6 @@
 //  Copyright John Maddock 2007.
 //  Copyright Paul A. Bristow 2007.
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -9,6 +9,7 @@
 #define BOOST_MATH_POLICY_ERROR_HANDLING_HPP
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <iomanip>
 #include <string>
 #include <cstring>
@@ -304,7 +305,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
 #else
    raise_error<std::overflow_error, T>(function, message ? message : "numeric overflow");
    // We should never get here:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 #endif
 }
 
@@ -320,7 +321,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
 #else
    raise_error<std::overflow_error, T>(function, message ? message : "numeric overflow", val);
    // We should never get here:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 #endif
 }
 
@@ -332,7 +333,7 @@ BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
 {
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
 #ifdef BOOST_MATH_HAS_GPU_SUPPORT
@@ -370,7 +371,7 @@ BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
 {
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
 template <class T>
@@ -382,7 +383,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
    errno = ERANGE;
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
 template <class T>
@@ -395,7 +396,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
    errno = ERANGE;
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
-   return std::numeric_limits<T>::has_infinity ? std::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
 template <class T>
@@ -404,7 +405,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
            const char* message,
            const  ::boost::math::policies::overflow_error< ::boost::math::policies::user_error>&)
 {
-   return user_overflow_error(function, message, std::numeric_limits<T>::infinity());
+   return user_overflow_error(function, message, boost::math::numeric_limits<T>::infinity());
 }
 
 template <class T>
@@ -418,7 +419,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_overflow_error(
    std::string sval = prec_format(val);
    replace_all_in_string(m, "%1%", sval.c_str());
 
-   return user_overflow_error(function, m.c_str(), std::numeric_limits<T>::infinity());
+   return user_overflow_error(function, m.c_str(), boost::math::numeric_limits<T>::infinity());
 }
 
 template <class T>
@@ -597,55 +598,8 @@ BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(
 {
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
-   static_assert(std::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
-   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
-   return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
-   #else
-   BOOST_IF_CONSTEXPR (std::is_same<TargetType, short>::value)
-   {
-      return val > 0 ? SHRT_MAX : SHRT_MIN;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, int>::value)
-   {
-      return val > 0 ? INT_MAX : INT_MIN;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, long>::value)
-   {
-      return val > 0 ? LONG_MAX : LONG_MIN;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, long long>::value)
-   {
-      return val > 0 ? LLONG_MAX : LLONG_MIN;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned short>::value)
-   {
-      return val > 0 ? USHRT_MAX : static_cast<unsigned short>(0U);
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned>::value)
-   {
-      return val > 0 ? UINT_MAX : 0U;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned long>::value)
-   {
-      return val > 0 ? ULONG_MAX : 0UL;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, unsigned long long>::value)
-   {
-      return val > 0 ? ULLONG_MAX : 0ULL;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, float>::value)
-   {
-      return val > 0 ? FLT_MAX : -FLT_MAX;
-   }
-   else BOOST_IF_CONSTEXPR (std::is_same<TargetType, double>::value)
-   {
-      return val > 0 ? DBL_MAX : -DBL_MAX;
-   }
-   else
-   {
-      return val > 0 ? static_cast<TargetType>(-1) : static_cast<TargetType>(1);
-   }
-   #endif
+   static_assert(boost::math::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
+   return  val > 0 ? (boost::math::numeric_limits<TargetType>::max)() : (boost::math::numeric_limits<TargetType>::is_integer ? (boost::math::numeric_limits<TargetType>::min)() : -(boost::math::numeric_limits<TargetType>::max)());
 }
 
 template <class T, class TargetType>
@@ -659,8 +613,8 @@ BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
    errno = ERANGE;
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
-   static_assert(std::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
-   return  val > 0 ? (std::numeric_limits<TargetType>::max)() : (std::numeric_limits<TargetType>::is_integer ? (std::numeric_limits<TargetType>::min)() : -(std::numeric_limits<TargetType>::max)());
+   static_assert(boost::math::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
+   return  val > 0 ? (boost::math::numeric_limits<TargetType>::max)() : (boost::math::numeric_limits<TargetType>::is_integer ? (boost::math::numeric_limits<TargetType>::min)() : -(boost::math::numeric_limits<TargetType>::max)());
 }
 template <class T, class TargetType>
 BOOST_MATH_GPU_ENABLED inline TargetType raise_rounding_error(
@@ -686,7 +640,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_indeterminate_result_error(
 #else
    raise_error<std::domain_error, T>(function, message, val);
    // we never get here:
-   return std::numeric_limits<T>::quiet_NaN();
+   return boost::math::numeric_limits<T>::quiet_NaN();
 #endif
 }
 

From 7b536bacccc8079e87d789f98d044cc1628ea4ec Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:26:40 -0400
Subject: [PATCH 129/399] Add GPU support to derived accessors

---
 .../detail/derived_accessors.hpp              | 32 ++++++++++---------
 1 file changed, 17 insertions(+), 15 deletions(-)

diff --git a/include/boost/math/distributions/detail/derived_accessors.hpp b/include/boost/math/distributions/detail/derived_accessors.hpp
index eb76409a1c..9d39f2d59d 100644
--- a/include/boost/math/distributions/detail/derived_accessors.hpp
+++ b/include/boost/math/distributions/detail/derived_accessors.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -29,6 +30,7 @@
 
 #include <cmath>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/config.hpp>
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -39,24 +41,24 @@
 namespace boost{ namespace math{
 
 template <class Distribution>
-typename Distribution::value_type variance(const Distribution& dist);
+BOOST_MATH_GPU_ENABLED typename Distribution::value_type variance(const Distribution& dist);
 
 template <class Distribution>
-inline typename Distribution::value_type standard_deviation(const Distribution& dist)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type standard_deviation(const Distribution& dist)
 {
    BOOST_MATH_STD_USING  // ADL of sqrt.
    return sqrt(variance(dist));
 }
 
 template <class Distribution>
-inline typename Distribution::value_type variance(const Distribution& dist)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type variance(const Distribution& dist)
 {
    typename Distribution::value_type result = standard_deviation(dist);
    return result * result;
 }
 
 template <class Distribution, class RealType>
-inline typename Distribution::value_type hazard(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type hazard(const Distribution& dist, const RealType& x)
 { // hazard function
   // http://www.itl.nist.gov/div898/handbook/eda/section3/eda362.htm#HAZ
    typedef typename Distribution::value_type value_type;
@@ -75,7 +77,7 @@ inline typename Distribution::value_type hazard(const Distribution& dist, const
 }
 
 template <class Distribution, class RealType>
-inline typename Distribution::value_type chf(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type chf(const Distribution& dist, const RealType& x)
 { // cumulative hazard function.
   // http://www.itl.nist.gov/div898/handbook/eda/section3/eda362.htm#HAZ
    BOOST_MATH_STD_USING
@@ -83,7 +85,7 @@ inline typename Distribution::value_type chf(const Distribution& dist, const Rea
 }
 
 template <class Distribution>
-inline typename Distribution::value_type coefficient_of_variation(const Distribution& dist)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type coefficient_of_variation(const Distribution& dist)
 {
    typedef typename Distribution::value_type value_type;
    typedef typename Distribution::policy_type policy_type;
@@ -104,33 +106,33 @@ inline typename Distribution::value_type coefficient_of_variation(const Distribu
 // implementation with all arguments of the same type:
 //
 template <class Distribution, class RealType>
-inline typename Distribution::value_type pdf(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type pdf(const Distribution& dist, const RealType& x)
 {
    typedef typename Distribution::value_type value_type;
    return pdf(dist, static_cast<value_type>(x));
 }
 template <class Distribution, class RealType>
-inline typename Distribution::value_type logpdf(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type logpdf(const Distribution& dist, const RealType& x)
 {
    using std::log;
    typedef typename Distribution::value_type value_type;
    return log(pdf(dist, static_cast<value_type>(x)));
 }
 template <class Distribution, class RealType>
-inline typename Distribution::value_type cdf(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type cdf(const Distribution& dist, const RealType& x)
 {
    typedef typename Distribution::value_type value_type;
    return cdf(dist, static_cast<value_type>(x));
 }
 template <class Distribution, class Realtype>
-inline typename Distribution::value_type logcdf(const Distribution& dist, const Realtype& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type logcdf(const Distribution& dist, const Realtype& x)
 {
    using std::log;
    using value_type = typename Distribution::value_type;
    return log(cdf(dist, static_cast<value_type>(x)));
 }
 template <class Distribution, class RealType>
-inline typename Distribution::value_type quantile(const Distribution& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type quantile(const Distribution& dist, const RealType& x)
 {
    typedef typename Distribution::value_type value_type;
    return quantile(dist, static_cast<value_type>(x));
@@ -144,14 +146,14 @@ inline typename Distribution::value_type chf(const Distribution& dist, const Rea
 }
 */
 template <class Distribution, class RealType>
-inline typename Distribution::value_type cdf(const complemented2_type<Distribution, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type cdf(const complemented2_type<Distribution, RealType>& c)
 {
    typedef typename Distribution::value_type value_type;
    return cdf(complement(c.dist, static_cast<value_type>(c.param)));
 }
 
 template <class Distribution, class RealType>
-inline typename Distribution::value_type logcdf(const complemented2_type<Distribution, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type logcdf(const complemented2_type<Distribution, RealType>& c)
 {
    using std::log;
    typedef typename Distribution::value_type value_type;
@@ -159,14 +161,14 @@ inline typename Distribution::value_type logcdf(const complemented2_type<Distrib
 }
 
 template <class Distribution, class RealType>
-inline typename Distribution::value_type quantile(const complemented2_type<Distribution, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline typename Distribution::value_type quantile(const complemented2_type<Distribution, RealType>& c)
 {
    typedef typename Distribution::value_type value_type;
    return quantile(complement(c.dist, static_cast<value_type>(c.param)));
 }
 
 template <class Dist>
-inline typename Dist::value_type median(const Dist& d)
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type median(const Dist& d)
 { // median - default definition for those distributions for which a
   // simple closed form is not known,
   // and for which a domain_error and/or NaN generating function is NOT defined.

From 6ca4cb9c87b2745bef63cc583b774adefdbedbff Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:26:54 -0400
Subject: [PATCH 130/399] Add GPU support to complement distributions

---
 .../boost/math/distributions/complement.hpp   | 27 ++++++++++---------
 1 file changed, 15 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/distributions/complement.hpp b/include/boost/math/distributions/complement.hpp
index 5c062a7cdf..c63b8a5041 100644
--- a/include/boost/math/distributions/complement.hpp
+++ b/include/boost/math/distributions/complement.hpp
@@ -1,5 +1,6 @@
 //  (C) Copyright John Maddock 2006.
 //  (C) Copyright Paul A. Bristow 2006.
+//  (C) Copyright Matt Borland 2024
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -7,6 +8,8 @@
 #ifndef BOOST_STATS_COMPLEMENT_HPP
 #define BOOST_STATS_COMPLEMENT_HPP
 
+#include <boost/math/tools/config.hpp>
+
 //
 // This code really defines our own tuple type.
 // It would be nice to reuse boost::math::tuple
@@ -19,7 +22,7 @@ namespace boost{ namespace math{
 template <class Dist, class RealType>
 struct complemented2_type
 {
-   complemented2_type(
+   BOOST_MATH_GPU_ENABLED complemented2_type(
       const Dist& d, 
       const RealType& p1)
       : dist(d), 
@@ -35,7 +38,7 @@ struct complemented2_type
 template <class Dist, class RealType1, class RealType2>
 struct complemented3_type
 {
-   complemented3_type(
+   BOOST_MATH_GPU_ENABLED complemented3_type(
       const Dist& d, 
       const RealType1& p1,
       const RealType2& p2)
@@ -53,7 +56,7 @@ struct complemented3_type
 template <class Dist, class RealType1, class RealType2, class RealType3>
 struct complemented4_type
 {
-   complemented4_type(
+   BOOST_MATH_GPU_ENABLED complemented4_type(
       const Dist& d, 
       const RealType1& p1,
       const RealType2& p2,
@@ -74,7 +77,7 @@ struct complemented4_type
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4>
 struct complemented5_type
 {
-   complemented5_type(
+   BOOST_MATH_GPU_ENABLED complemented5_type(
       const Dist& d, 
       const RealType1& p1,
       const RealType2& p2,
@@ -98,7 +101,7 @@ struct complemented5_type
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4, class RealType5>
 struct complemented6_type
 {
-   complemented6_type(
+   BOOST_MATH_GPU_ENABLED complemented6_type(
       const Dist& d, 
       const RealType1& p1,
       const RealType2& p2,
@@ -125,7 +128,7 @@ struct complemented6_type
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4, class RealType5, class RealType6>
 struct complemented7_type
 {
-   complemented7_type(
+   BOOST_MATH_GPU_ENABLED complemented7_type(
       const Dist& d, 
       const RealType1& p1,
       const RealType2& p2,
@@ -153,37 +156,37 @@ struct complemented7_type
 };
 
 template <class Dist, class RealType>
-inline complemented2_type<Dist, RealType> complement(const Dist& d, const RealType& r)
+BOOST_MATH_GPU_ENABLED inline complemented2_type<Dist, RealType> complement(const Dist& d, const RealType& r)
 {
    return complemented2_type<Dist, RealType>(d, r);
 }
 
 template <class Dist, class RealType1, class RealType2>
-inline complemented3_type<Dist, RealType1, RealType2> complement(const Dist& d, const RealType1& r1, const RealType2& r2)
+BOOST_MATH_GPU_ENABLED inline complemented3_type<Dist, RealType1, RealType2> complement(const Dist& d, const RealType1& r1, const RealType2& r2)
 {
    return complemented3_type<Dist, RealType1, RealType2>(d, r1, r2);
 }
 
 template <class Dist, class RealType1, class RealType2, class RealType3>
-inline complemented4_type<Dist, RealType1, RealType2, RealType3> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3)
+BOOST_MATH_GPU_ENABLED inline complemented4_type<Dist, RealType1, RealType2, RealType3> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3)
 {
    return complemented4_type<Dist, RealType1, RealType2, RealType3>(d, r1, r2, r3);
 }
 
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4>
-inline complemented5_type<Dist, RealType1, RealType2, RealType3, RealType4> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4)
+BOOST_MATH_GPU_ENABLED inline complemented5_type<Dist, RealType1, RealType2, RealType3, RealType4> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4)
 {
    return complemented5_type<Dist, RealType1, RealType2, RealType3, RealType4>(d, r1, r2, r3, r4);
 }
 
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4, class RealType5>
-inline complemented6_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4, const RealType5& r5)
+BOOST_MATH_GPU_ENABLED inline complemented6_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4, const RealType5& r5)
 {
    return complemented6_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5>(d, r1, r2, r3, r4, r5);
 }
 
 template <class Dist, class RealType1, class RealType2, class RealType3, class RealType4, class RealType5, class RealType6>
-inline complemented7_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5, RealType6> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4, const RealType5& r5, const RealType6& r6)
+BOOST_MATH_GPU_ENABLED inline complemented7_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5, RealType6> complement(const Dist& d, const RealType1& r1, const RealType2& r2, const RealType3& r3, const RealType4& r4, const RealType5& r5, const RealType6& r6)
 {
    return complemented7_type<Dist, RealType1, RealType2, RealType3, RealType4, RealType5, RealType6>(d, r1, r2, r3, r4, r5, r6);
 }

From c75da28b3998878827c6e602e86a71697f009719 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:27:09 -0400
Subject: [PATCH 131/399] Add GPU support to the bernoulli distribution

---
 .../boost/math/distributions/bernoulli.hpp    | 43 ++++++++++---------
 1 file changed, 22 insertions(+), 21 deletions(-)

diff --git a/include/boost/math/distributions/bernoulli.hpp b/include/boost/math/distributions/bernoulli.hpp
index cce209a6fb..bb7dd22a54 100644
--- a/include/boost/math/distributions/bernoulli.hpp
+++ b/include/boost/math/distributions/bernoulli.hpp
@@ -2,6 +2,7 @@
 
 // Copyright John Maddock 2006.
 // Copyright Paul A. Bristow 2007.
+// Copyright Matt Borland 2024.
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -43,7 +44,7 @@ namespace boost
     {
       // Common error checking routines for bernoulli distribution functions:
       template <class RealType, class Policy>
-      inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& /* pol */)
+      BOOST_MATH_GPU_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& /* pol */)
       {
         if(!(boost::math::isfinite)(p) || (p < 0) || (p > 1))
         {
@@ -55,23 +56,23 @@ namespace boost
         return true;
       }
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */, const std::true_type&)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */, const std::true_type&)
       {
         return check_success_fraction(function, p, result, Policy());
       }
       template <class RealType, class Policy>
-      inline bool check_dist(const char* , const RealType& , RealType* , const Policy& /* pol */, const std::false_type&)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* , const RealType& , RealType* , const Policy& /* pol */, const std::false_type&)
       {
          return true;
       }
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */)
       {
          return check_dist(function, p, result, Policy(), typename policies::constructor_error_check<Policy>::type());
       }
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_k(const char* function, const RealType& p, RealType k, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function, const RealType& p, RealType k, RealType* result, const Policy& pol)
       {
         if(check_dist(function, p, result, Policy(), typename policies::method_error_check<Policy>::type()) == false)
         {
@@ -87,7 +88,7 @@ namespace boost
        return true;
       }
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, RealType p, RealType prob, RealType* result, const Policy& /* pol */)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, RealType p, RealType prob, RealType* result, const Policy& /* pol */)
       {
         if((check_dist(function, p, result, Policy(), typename policies::method_error_check<Policy>::type()) && detail::check_probability(function, prob, result, Policy())) == false)
         {
@@ -105,7 +106,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      bernoulli_distribution(RealType p = 0.5) : m_p(p)
+      BOOST_MATH_GPU_ENABLED bernoulli_distribution(RealType p = 0.5) : m_p(p)
       { // Default probability = half suits 'fair' coin tossing
         // where probability of heads == probability of tails.
         RealType result; // of checks.
@@ -115,7 +116,7 @@ namespace boost
           &result, Policy());
       } // bernoulli_distribution constructor.
 
-      RealType success_fraction() const
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const
       { // Probability.
         return m_p;
       }
@@ -132,21 +133,21 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const bernoulli_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const bernoulli_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable k = {0, 1}.
       using boost::math::tools::max_value;
       return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const bernoulli_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const bernoulli_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable k = {0, 1}.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
       return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const bernoulli_distribution<RealType, Policy>& dist)
     { // Mean of bernoulli distribution = p (n = 1).
       return dist.success_fraction();
     } // mean
@@ -159,13 +160,13 @@ namespace boost
     //} // median
 
     template <class RealType, class Policy>
-    inline RealType variance(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const bernoulli_distribution<RealType, Policy>& dist)
     { // Variance of bernoulli distribution =p * q.
       return  dist.success_fraction() * (1 - dist.success_fraction());
     } // variance
 
     template <class RealType, class Policy>
-    RealType pdf(const bernoulli_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED RealType pdf(const bernoulli_distribution<RealType, Policy>& dist, const RealType& k)
     { // Probability Density/Mass Function.
       BOOST_FPU_EXCEPTION_GUARD
       // Error check:
@@ -190,7 +191,7 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const bernoulli_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const bernoulli_distribution<RealType, Policy>& dist, const RealType& k)
     { // Cumulative Distribution Function Bernoulli.
       RealType p = dist.success_fraction();
       // Error check:
@@ -214,7 +215,7 @@ namespace boost
     } // bernoulli cdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<bernoulli_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<bernoulli_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function bernoulli.
       RealType const& k = c.param;
       bernoulli_distribution<RealType, Policy> const& dist = c.dist;
@@ -240,7 +241,7 @@ namespace boost
     } // bernoulli cdf complement
 
     template <class RealType, class Policy>
-    inline RealType quantile(const bernoulli_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const bernoulli_distribution<RealType, Policy>& dist, const RealType& p)
     { // Quantile or Percent Point Bernoulli function.
       // Return the number of expected successes k either 0 or 1.
       // for a given probability p.
@@ -265,7 +266,7 @@ namespace boost
     } // quantile
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<bernoulli_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<bernoulli_distribution<RealType, Policy>, RealType>& c)
     { // Quantile or Percent Point bernoulli function.
       // Return the number of expected successes k for a given
       // complement of the probability q.
@@ -294,13 +295,13 @@ namespace boost
     } // quantile complemented.
 
     template <class RealType, class Policy>
-    inline RealType mode(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const bernoulli_distribution<RealType, Policy>& dist)
     {
       return static_cast<RealType>((dist.success_fraction() <= 0.5) ? 0 : 1); // p = 0.5 can be 0 or 1
     }
 
     template <class RealType, class Policy>
-    inline RealType skewness(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const bernoulli_distribution<RealType, Policy>& dist)
     {
       BOOST_MATH_STD_USING; // Aid ADL for sqrt.
       RealType p = dist.success_fraction();
@@ -308,7 +309,7 @@ namespace boost
     }
 
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const bernoulli_distribution<RealType, Policy>& dist)
     {
       RealType p = dist.success_fraction();
       // Note Wolfram says this is kurtosis in text, but gamma2 is the kurtosis excess,
@@ -319,7 +320,7 @@ namespace boost
     }
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const bernoulli_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const bernoulli_distribution<RealType, Policy>& dist)
     {
       RealType p = dist.success_fraction();
       return 1 / (1 - p) + 1/p -6 + 3;

From 8e10bab3df354923b22ec6c1808150ed3e62f65a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:27:26 -0400
Subject: [PATCH 132/399] Add SYCL testing of bernoulli distribution

---
 test/sycl_jamfile       |  1 +
 test/test_bernoulli.cpp | 14 +++++++++++---
 2 files changed, 12 insertions(+), 3 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index c0c67d1e55..92580c93b7 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -11,6 +11,7 @@ project : requirements
 
 # Distributions
 run test_arcsine.cpp ;
+run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
 
 # Special Functions
diff --git a/test/test_bernoulli.cpp b/test/test_bernoulli.cpp
index d8c663399a..8513cec36d 100644
--- a/test/test_bernoulli.cpp
+++ b/test/test_bernoulli.cpp
@@ -2,6 +2,7 @@
 
 // Copyright John Maddock 2006.
 // Copyright  Paul A. Bristow 2007, 2012.
+// Copyright Matt Borland 2024
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -22,7 +23,7 @@
 
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 
 #include <boost/math/distributions/bernoulli.hpp> // for bernoulli_distribution
 using boost::math::bernoulli_distribution;
@@ -74,6 +75,7 @@ void test_spots(RealType)
   BOOST_CHECK_EQUAL(bernoulli_distribution<RealType>(static_cast<RealType>(0.1L)).success_fraction(), static_cast<RealType>(0.1L));
   BOOST_CHECK_EQUAL(bernoulli_distribution<RealType>(static_cast<RealType>(0.9L)).success_fraction(), static_cast<RealType>(0.9L));
 
+#ifndef BOOST_MATH_NO_EXCEPTIONS
   BOOST_MATH_CHECK_THROW( // Constructor success_fraction outside 0 to 1.
        bernoulli_distribution<RealType>(static_cast<RealType>(2)), std::domain_error);
   BOOST_MATH_CHECK_THROW(
@@ -86,7 +88,8 @@ void test_spots(RealType)
   BOOST_MATH_CHECK_THROW(
        pdf( // pdf k neither 0 nor 1.
           bernoulli_distribution<RealType>(static_cast<RealType>(0.25L)), static_cast<RealType>(2)), std::domain_error);
- 
+#endif
+
   BOOST_CHECK_EQUAL(
     pdf( // OK k (or n)
     bernoulli_distribution<RealType>(static_cast<RealType>(0.5L)), static_cast<RealType>(0)),
@@ -134,6 +137,7 @@ void test_spots(RealType)
        static_cast<RealType>(5.11111111111111111111111111111111111111111111L),
        tolerance);
 
+#ifndef BOOST_MATH_NO_EXCEPTIONS
   BOOST_MATH_CHECK_THROW(
      quantile(
         bernoulli_distribution<RealType>(static_cast<RealType>(2)), // prob >1
@@ -154,6 +158,7 @@ void test_spots(RealType)
         bernoulli_distribution<RealType>(static_cast<RealType>(0.5L)), // k < 0
         static_cast<RealType>(2)), std::domain_error
      );
+#endif
 
   BOOST_CHECK_CLOSE_FRACTION(
      cdf(
@@ -217,6 +222,7 @@ void test_spots(RealType)
 
    // Checks for 'bad' parameters.
    // Construction.
+   #ifndef BOOST_MATH_NO_EXCEPTIONS
    BOOST_MATH_CHECK_THROW(bernoulli_distribution<RealType>(-1), std::domain_error); // p outside 0 to 1.
    BOOST_MATH_CHECK_THROW(bernoulli_distribution<RealType>(+2), std::domain_error); // p outside 0 to 1.
 
@@ -269,7 +275,7 @@ void test_spots(RealType)
      BOOST_MATH_CHECK_THROW(quantile(w, +inf), std::domain_error); // p = + inf
      BOOST_MATH_CHECK_THROW(quantile(complement(w, +inf)), std::domain_error); // p = + inf
    } // has_infinity
-
+   #endif
 } // template <class RealType>void test_spots(RealType)
 
 BOOST_AUTO_TEST_CASE( test_main )
@@ -302,7 +308,9 @@ BOOST_AUTO_TEST_CASE( test_main )
   // (Parameter value, arbitrarily zero, only communicates the floating point type).
   test_spots(0.0F); // Test float.
   test_spots(0.0); // Test double.
+#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
   test_spots(0.0L); // Test long double.
+#endif
 #if !BOOST_WORKAROUND(BOOST_BORLANDC, BOOST_TESTED_AT(0x582)) && !defined(BOOST_MATH_NO_REAL_CONCEPT_TESTS)
   test_spots(boost::math::concepts::real_concept(0.)); // Test real concept.
 #endif

From 4b6c408a9be06a9f88acb80613cbeb71864d442c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:45:21 -0400
Subject: [PATCH 133/399] Add bernoulli cdf CUDA testing

---
 test/cuda_jamfile                 |   2 +
 test/test_bernoulli_cdf_double.cu | 110 ++++++++++++++++++++++++++++++
 test/test_bernoulli_cdf_float.cu  | 110 ++++++++++++++++++++++++++++++
 3 files changed, 222 insertions(+)
 create mode 100644 test/test_bernoulli_cdf_double.cu
 create mode 100644 test/test_bernoulli_cdf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 94ca839b64..bb184bd6e6 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -22,6 +22,8 @@ run test_arcsine_pdf_double.cu ;
 run test_arcsine_pdf_float.cu ;
 run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
+run test_bernoulli_cdf_double.cu ;
+run test_bernoulli_cdf_float.cu ;
 run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
diff --git a/test/test_bernoulli_cdf_double.cu b/test/test_bernoulli_cdf_double.cu
new file mode 100644
index 0000000000..e4c21ca062
--- /dev/null
+++ b/test/test_bernoulli_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::bernoulli_distribution<float_type>(in1[i]), static_cast<float_type>(1));
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::bernoulli_distribution<float_type>(input_vector1[i]), static_cast<float_type>(1)));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_bernoulli_cdf_float.cu b/test/test_bernoulli_cdf_float.cu
new file mode 100644
index 0000000000..82c0eabc0f
--- /dev/null
+++ b/test/test_bernoulli_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::bernoulli_distribution<float_type>(in1[i]), static_cast<float_type>(1));
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::bernoulli_distribution<float_type>(input_vector1[i]), static_cast<float_type>(1)));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 04f3bd7556512edd541080467a35da6bf65ec441 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 25 Jul 2024 15:47:15 -0400
Subject: [PATCH 134/399] Add bernoulli pdf CUDA testing

---
 test/cuda_jamfile                 |   2 +
 test/test_bernoulli_pdf_double.cu | 110 ++++++++++++++++++++++++++++++
 test/test_bernoulli_pdf_float.cu  | 110 ++++++++++++++++++++++++++++++
 3 files changed, 222 insertions(+)
 create mode 100644 test/test_bernoulli_pdf_double.cu
 create mode 100644 test/test_bernoulli_pdf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index bb184bd6e6..64dcae9e6e 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -24,6 +24,8 @@ run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
 run test_bernoulli_cdf_double.cu ;
 run test_bernoulli_cdf_float.cu ;
+run test_bernoulli_pdf_double.cu ;
+run test_bernoulli_pdf_float.cu ;
 run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
diff --git a/test/test_bernoulli_pdf_double.cu b/test/test_bernoulli_pdf_double.cu
new file mode 100644
index 0000000000..24b33c16c0
--- /dev/null
+++ b/test/test_bernoulli_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::bernoulli_distribution<float_type>(in1[i]), static_cast<float_type>(1));
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::bernoulli_distribution<float_type>(input_vector1[i]), static_cast<float_type>(1)));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_bernoulli_pdf_float.cu b/test/test_bernoulli_pdf_float.cu
new file mode 100644
index 0000000000..08d2ca5a01
--- /dev/null
+++ b/test/test_bernoulli_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::bernoulli_distribution<float_type>(in1[i]), static_cast<float_type>(1));
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::bernoulli_distribution<float_type>(input_vector1[i]), static_cast<float_type>(1)));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From bdf57a344c25c133616a3ed3d37e92d5138f1dab Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 11:08:54 -0400
Subject: [PATCH 135/399] Add bool to numeric limits for completeness

---
 include/boost/math/tools/numeric_limits.hpp | 38 +++++++++++++++++++++
 1 file changed, 38 insertions(+)

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
index c49d50bd81..7d3d5db268 100644
--- a/include/boost/math/tools/numeric_limits.hpp
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -418,6 +418,44 @@ struct numeric_limits<unsigned long long>
     BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long denorm_min    () { return 0; }
 };
 
+template <>
+struct numeric_limits<bool>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = std::numeric_limits<bool>::is_specialized;
+    BOOST_MATH_STATIC constexpr bool is_signed = std::numeric_limits<bool>::is_signed;
+    BOOST_MATH_STATIC constexpr bool is_integer = std::numeric_limits<bool>::is_integer;
+    BOOST_MATH_STATIC constexpr bool is_exact = std::numeric_limits<bool>::is_exact;
+    BOOST_MATH_STATIC constexpr bool has_infinity = std::numeric_limits<bool>::has_infinity;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = std::numeric_limits<bool>::has_quiet_NaN;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = std::numeric_limits<bool>::has_signaling_NaN;
+
+    BOOST_MATH_STATIC constexpr std::float_round_style round_style = std::numeric_limits<bool>::round_style;
+    BOOST_MATH_STATIC constexpr bool is_iec559 = std::numeric_limits<bool>::is_iec559;
+    BOOST_MATH_STATIC constexpr bool is_bounded = std::numeric_limits<bool>::is_bounded;
+    BOOST_MATH_STATIC constexpr bool is_modulo = std::numeric_limits<bool>::is_modulo;
+    BOOST_MATH_STATIC constexpr int digits = std::numeric_limits<bool>::digits;
+    BOOST_MATH_STATIC constexpr int digits10 = std::numeric_limits<bool>::digits10;
+    BOOST_MATH_STATIC constexpr int max_digits10 = std::numeric_limits<bool>::max_digits10;
+    BOOST_MATH_STATIC constexpr int radix = std::numeric_limits<bool>::radix;
+    BOOST_MATH_STATIC constexpr int min_exponent = std::numeric_limits<bool>::min_exponent;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = std::numeric_limits<bool>::min_exponent10;
+    BOOST_MATH_STATIC constexpr int max_exponent = std::numeric_limits<bool>::max_exponent;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = std::numeric_limits<bool>::max_exponent10;
+    BOOST_MATH_STATIC constexpr bool traps = std::numeric_limits<bool>::traps;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = std::numeric_limits<bool>::tinyness_before;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool (min)         () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool (max)         () { return true; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool lowest        () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool epsilon       () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool round_error   () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool infinity      () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool quiet_NaN     () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool signaling_NaN () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool denorm_min    () { return false; }
+};
+
 #endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 } // namespace math

From df18e3281b12d1c173aae4804c7fffeb65e9184c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:04:12 -0400
Subject: [PATCH 136/399] Multi-thread CMake builds

---
 .github/workflows/ci.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 4af5da980a..0bf82c16e0 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -606,7 +606,7 @@ jobs:
       - name: Build tests
         run: |
           cd ../boost-root/__build__
-          cmake --build . --target tests
+          cmake --build . --target tests -j $(nproc)
       - name: Run tests
         run: |
           cd ../boost-root/__build__
@@ -663,7 +663,7 @@ jobs:
       - name: Build tests
         run: |
           cd ../boost-root/__build__
-          cmake --build . --target tests
+          cmake --build . --target tests -j $(nproc)
       # Will leave this commented out for now. GHA does not install graphics cards by default
       #- name: Run tests
       #  run: |

From b16be96d72d6c91046e15aeb62d36dc4c4fbd2ef Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 11:54:29 -0400
Subject: [PATCH 137/399] Fix test poisson ambiguity with numeric_limits

---
 test/test_poisson.cpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/test/test_poisson.cpp b/test/test_poisson.cpp
index 9b75ce162f..73de4751e3 100644
--- a/test/test_poisson.cpp
+++ b/test/test_poisson.cpp
@@ -53,12 +53,12 @@ void test_spots(RealType)
    // guaranteed for type RealType, eg 6 for float, 15 for double,
    // expressed as a percentage (so -2) for BOOST_CHECK_CLOSE,
 
-   int decdigits = numeric_limits<RealType>::digits10;
+   int decdigits = std::numeric_limits<RealType>::digits10;
   // May eb >15 for 80 and 128-bit FP types.
   if (decdigits <= 0)
   { // decdigits is not defined, for example real concept,
     // so assume precision of most test data is double (for example, MathCAD).
-     decdigits = numeric_limits<double>::digits10; // == 15 for 64-bit
+     decdigits = std::numeric_limits<double>::digits10; // == 15 for 64-bit
   }
   if (decdigits > 15 ) // numeric_limits<double>::digits10)
   { // 15 is the accuracy of the MathCAD test data.
@@ -644,7 +644,7 @@ BOOST_AUTO_TEST_CASE( test_main )
   test_spots(0.0); // Test double.
 #endif
 #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
-  if (numeric_limits<long double>::digits10 > numeric_limits<double>::digits10)
+  if (std::numeric_limits<long double>::digits10 > std::numeric_limits<double>::digits10)
   { // long double is better than double (so not MSVC where they are same).
 #ifdef TEST_LDOUBLE
      test_spots(0.0L); // Test long double.

From fff00e3fbc6d726866ecba6a41a2d4fb84628599 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 12:00:03 -0400
Subject: [PATCH 138/399] Fix header paths

---
 test/test_bernoulli_constants.cpp | 2 +-
 test/test_float_io.cpp            | 2 +-
 test/test_owens_t.cpp             | 6 +++---
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/test/test_bernoulli_constants.cpp b/test/test_bernoulli_constants.cpp
index 6d73d82a4c..f5ae15a3ee 100644
--- a/test/test_bernoulli_constants.cpp
+++ b/test/test_bernoulli_constants.cpp
@@ -10,7 +10,7 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/bernoulli.hpp>
-#include <libs/math/test/table_type.hpp>
+#include "table_type.hpp"
 #include <boost/math/tools/test.hpp>
 #include <iostream>
 #include <iomanip>
diff --git a/test/test_float_io.cpp b/test/test_float_io.cpp
index 107cc39d4a..e1b5c67a12 100644
--- a/test/test_float_io.cpp
+++ b/test/test_float_io.cpp
@@ -301,7 +301,7 @@ void test()
          std::ios_base::fixed | std::ios_base::showpos}};
 
    std::array<std::array<const char*, 13 * 9>, 40> string_data = {{
-#include "libs/math/test/string_data.ipp"
+#include "string_data.ipp"
    }};
 
    double num   = 123456789.0;
diff --git a/test/test_owens_t.cpp b/test/test_owens_t.cpp
index 8c33e77f07..11389dd205 100644
--- a/test/test_owens_t.cpp
+++ b/test/test_owens_t.cpp
@@ -38,9 +38,9 @@ using boost::math::owens_t;
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/array.hpp>
 
-#include "libs/math/test/handle_test_result.hpp"
-#include "libs/math/test/table_type.hpp"
-#include "libs/math/test/functor.hpp"
+#include "handle_test_result.hpp"
+#include "table_type.hpp"
+#include "functor.hpp"
 #include "boost/math/tools/test_value.hpp"
 #include "test_owens_t.hpp"
 

From 1f7f23c2d4244309d0306bbd833dca94b50d1c8e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 13:36:07 -0400
Subject: [PATCH 139/399] Fix invalid constexpr variables

---
 .../boost/math/special_functions/digamma.hpp   | 18 +++++++++---------
 .../boost/math/special_functions/sin_pi.hpp    |  8 ++++----
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/include/boost/math/special_functions/digamma.hpp b/include/boost/math/special_functions/digamma.hpp
index 98c939237e..bde80f7ddb 100644
--- a/include/boost/math/special_functions/digamma.hpp
+++ b/include/boost/math/special_functions/digamma.hpp
@@ -327,11 +327,11 @@ BOOST_MATH_GPU_ENABLED T digamma_imp_1_2(T x, const std::integral_constant<int,
    // At double precision, max error found:  2.452e-17
    //
    // LCOV_EXCL_START
-   constexpr float Y = 0.99558162689208984F;
+   BOOST_MATH_STATIC const float Y = 0.99558162689208984F;
 
-   constexpr T root1 = T(1569415565) / 1073741824uL;
-   constexpr T root2 = (T(381566830) / 1073741824uL) / 1073741824uL;
-   constexpr T root3 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.9016312093258695918615325266959189453125e-19);
+   BOOST_MATH_STATIC const T root1 = T(1569415565) / 1073741824uL;
+   BOOST_MATH_STATIC const T root2 = (T(381566830) / 1073741824uL) / 1073741824uL;
+   BOOST_MATH_STATIC const T root3 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.9016312093258695918615325266959189453125e-19);
 
    BOOST_MATH_STATIC const T P[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, 0.25479851061131551),
@@ -378,16 +378,16 @@ BOOST_MATH_GPU_ENABLED inline T digamma_imp_1_2(T x, const std::integral_constan
    // At float precision, max error found:  2.008725e-008
    //
    // LCOV_EXCL_START
-   constexpr float Y = 0.99558162689208984f;
-   constexpr T root = 1532632.0f / 1048576;
-   constexpr T root_minor = static_cast<T>(0.3700660185912626595423257213284682051735604e-6L);
-   constexpr T P[] = {
+   BOOST_MATH_STATIC const float Y = 0.99558162689208984f;
+   BOOST_MATH_STATIC const T root = 1532632.0f / 1048576;
+   BOOST_MATH_STATIC const T root_minor = static_cast<T>(0.3700660185912626595423257213284682051735604e-6L);
+   BOOST_MATH_STATIC const T P[] = {
       0.25479851023250261e0f,
       -0.44981331915268368e0f,
       -0.43916936919946835e0f,
       -0.61041765350579073e-1f
    };
-   constexpr T Q[] = {
+   BOOST_MATH_STATIC const T Q[] = {
       0.1e1f,
       0.15890202430554952e1f,
       0.65341249856146947e0f,
diff --git a/include/boost/math/special_functions/sin_pi.hpp b/include/boost/math/special_functions/sin_pi.hpp
index 3c558ab7b6..acb5db29e2 100644
--- a/include/boost/math/special_functions/sin_pi.hpp
+++ b/include/boost/math/special_functions/sin_pi.hpp
@@ -55,15 +55,15 @@ BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-BOOST_MATH_FORCEINLINE BOOST_MATH_GPU_ENABLED T sin_pi_dispatch(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sin_pi_dispatch(T x, const Policy& pol)
 {
-   if (x < 0)
+   if (x < T(0))
    {
-      return -sin_pi_imp(-x, pol);
+      return -sin_pi_imp(T(-x), pol);
    }
    else
    {
-      return sin_pi_imp(x, pol);
+      return sin_pi_imp(T(x), pol);
    }
 }
 

From 6f5bc2b31aa2e3748288e5dc0e60450d3b464766 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 13:46:25 -0400
Subject: [PATCH 140/399] Fix new trigamma dispatch function and illegal
 constexpr

---
 include/boost/math/special_functions/trigamma.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index 5d10135b98..2ec6c52562 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -49,7 +49,7 @@ template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 53>&)
 {
    // Max error in interpolated form: 3.736e-017
-   constexpr T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
+   BOOST_MATH_STATIC const T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
    BOOST_MATH_STATIC const T P_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 53, -1.1093280605946045),
       BOOST_MATH_BIG_CONSTANT(T, 53, -3.8310674472619321),
@@ -122,7 +122,7 @@ template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 64>&)
 {
    // Max error in interpolated form: 1.178e-020
-   constexpr T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
+   BOOST_MATH_STATIC const T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
    BOOST_MATH_STATIC const T P_1_2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -1.10932535608960258341),
       BOOST_MATH_BIG_CONSTANT(T, 64, -4.18793841543017129052),
@@ -395,7 +395,7 @@ BOOST_MATH_GPU_ENABLED T trigamma_dispatch(T x, const Policy& pol, const Tag& ta
          return policies::raise_pole_error<T>("boost::math::trigamma<%1%>(%1%)", nullptr, (1-x), pol);
       }
       T s = fabs(x) < fabs(z) ? boost::math::sin_pi(x, pol) : boost::math::sin_pi(z, pol);
-      return result - trigamma_prec(z, pol, tag) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
+      return result - trigamma_prec(T(z), pol, tag) + boost::math::pow<2>(constants::pi<T>()) / (s * s);
    }
    if(x < 1)
    {

From 8dd785c9b1f80ab02f40b029675a14f22b83382a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:33:03 -0400
Subject: [PATCH 141/399] Add CUDA compatible alias to thrust::pair or
 std::pair

---
 include/boost/math/tools/tuple.hpp | 40 ++++++++++++++++++++++++++++--
 1 file changed, 38 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index b5e42fc59e..60867e06d0 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2010.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -6,12 +7,40 @@
 #ifndef BOOST_MATH_TUPLE_HPP_INCLUDED
 #define BOOST_MATH_TUPLE_HPP_INCLUDED
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/cxx03_warn.hpp>
 #include <tuple>
 
-namespace boost{ namespace math{
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+#include <thrust/pair.h>
+#include <thrust/tuple.h>
+
+namespace boost { 
+namespace math {
+
+using thrust::pair;
+using thrust::tuple;
+
+using thrust::make_pair;
+using thrust::make_tuple;
+
+using thrust::tie;
+using thrust::get;
+
+using thrust::tuple_size;
+using thrust::tuple_element;
+
+} // namespace math
+} // namespace boost
+
+#else
+
+namespace boost { 
+namespace math {
 
 using ::std::tuple;
+using ::std::pair;
 
 // [6.1.3.2] Tuple creation functions
 using ::std::ignore;
@@ -23,5 +52,12 @@ using ::std::get;
 using ::std::tuple_size;
 using ::std::tuple_element;
 
-}}
+// Pair helpers
+using ::std::make_pair;
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
 #endif

From ca109d7cf971eade65f27c59d018fb86806a0d38 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:33:23 -0400
Subject: [PATCH 142/399] Fix arcsine dist range and support with thrust

---
 include/boost/math/distributions/arcsine.hpp | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index 59bf666b9c..d921e1145f 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -2,6 +2,7 @@
 
 // Copyright John Maddock 2014.
 // Copyright Paul A. Bristow 2014.
+// Copyright Matt Borland 2024.
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -31,6 +32,7 @@
 
 #include <cmath>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/complement.hpp> // complements.
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks.
@@ -204,17 +206,17 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>
-    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const arcsine_distribution<RealType, Policy>&  dist)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-      return std::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(dist.x_min()), static_cast<RealType>(dist.x_max()));
     }
 
     template <class RealType, class Policy>

From 7dde526a2b0642a79f5329cf18709a4ee58c2006 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:33:34 -0400
Subject: [PATCH 143/399] Add CUDA testing of range and support

---
 test/cuda_jamfile                         |   1 +
 test/test_arcsine_range_support_double.cu | 110 ++++++++++++++++++++++
 test/test_arcsine_range_support_float.cu  | 110 ++++++++++++++++++++++
 3 files changed, 221 insertions(+)
 create mode 100644 test/test_arcsine_range_support_double.cu
 create mode 100644 test/test_arcsine_range_support_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 64dcae9e6e..e46554a440 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -22,6 +22,7 @@ run test_arcsine_pdf_double.cu ;
 run test_arcsine_pdf_float.cu ;
 run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
+run test_arcsine_range_support_double.cu ;
 run test_bernoulli_cdf_double.cu ;
 run test_bernoulli_cdf_float.cu ;
 run test_bernoulli_pdf_double.cu ;
diff --git a/test/test_arcsine_range_support_double.cu b/test/test_arcsine_range_support_double.cu
new file mode 100644
index 0000000000..cec919a1ae
--- /dev/null
+++ b/test/test_arcsine_range_support_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::arcsine_distribution<float_type>(in1[i])).first + support(boost::math::arcsine_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::arcsine_distribution<float_type>(input_vector1[i])).first + support(boost::math::arcsine_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_arcsine_range_support_float.cu b/test/test_arcsine_range_support_float.cu
new file mode 100644
index 0000000000..d397e0c86d
--- /dev/null
+++ b/test/test_arcsine_range_support_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::arcsine_distribution<float_type>(in1[i])).first + support(boost::math::arcsine_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::arcsine_distribution<float_type>(input_vector1[i])).first + support(boost::math::arcsine_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file

From 6b8e05d2932ee7f99180b63647481ace0caee22d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:37:54 -0400
Subject: [PATCH 144/399] Fix bernoulli dist use of std::pair for range and
 support

---
 include/boost/math/distributions/bernoulli.hpp | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/include/boost/math/distributions/bernoulli.hpp b/include/boost/math/distributions/bernoulli.hpp
index bb7dd22a54..30ab60b6c4 100644
--- a/include/boost/math/distributions/bernoulli.hpp
+++ b/include/boost/math/distributions/bernoulli.hpp
@@ -30,6 +30,7 @@
 
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/complement.hpp> // complements
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
@@ -133,17 +134,17 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const bernoulli_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const bernoulli_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable k = {0, 1}.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>
-    BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const bernoulli_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const bernoulli_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable k = {0, 1}.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>

From 6f4cf00468ec69059b023400f01b481a06b61e6f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 14:38:12 -0400
Subject: [PATCH 145/399] Add CUDA testing of range and support on bernoulli
 dist

---
 test/cuda_jamfile                           |   2 +
 test/test_bernoulli_range_support_double.cu | 110 ++++++++++++++++++++
 test/test_bernoulli_range_support_float.cu  | 110 ++++++++++++++++++++
 3 files changed, 222 insertions(+)
 create mode 100644 test/test_bernoulli_range_support_double.cu
 create mode 100644 test/test_bernoulli_range_support_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index e46554a440..8c10d4810a 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -27,6 +27,8 @@ run test_bernoulli_cdf_double.cu ;
 run test_bernoulli_cdf_float.cu ;
 run test_bernoulli_pdf_double.cu ;
 run test_bernoulli_pdf_float.cu ;
+run test_bernoulli_range_support_double.cu ;
+run test_bernoulli_range_support_float.cu ;
 run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
diff --git a/test/test_bernoulli_range_support_double.cu b/test/test_bernoulli_range_support_double.cu
new file mode 100644
index 0000000000..86c77bd114
--- /dev/null
+++ b/test/test_bernoulli_range_support_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::bernoulli_distribution<float_type>(in1[i])).first + support(boost::math::bernoulli_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::bernoulli_distribution<float_type>(input_vector1[i])).first + support(boost::math::bernoulli_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_bernoulli_range_support_float.cu b/test/test_bernoulli_range_support_float.cu
new file mode 100644
index 0000000000..cdcf544189
--- /dev/null
+++ b/test/test_bernoulli_range_support_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::bernoulli_distribution<float_type>(in1[i])).first + support(boost::math::bernoulli_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::bernoulli_distribution<float_type>(input_vector1[i])).first + support(boost::math::bernoulli_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file

From 6e42cd05b5561f5b67350f168b57d6eaff2e9ff0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 15:14:25 -0400
Subject: [PATCH 146/399] Fix more uses of std::pair in binomial and cauchy
 distributions

---
 include/boost/math/distributions/binomial.hpp |  9 +++++----
 include/boost/math/distributions/cauchy.hpp   | 14 ++++++++------
 2 files changed, 13 insertions(+), 10 deletions(-)

diff --git a/include/boost/math/distributions/binomial.hpp b/include/boost/math/distributions/binomial.hpp
index 4c1f8bfa00..b17893e422 100644
--- a/include/boost/math/distributions/binomial.hpp
+++ b/include/boost/math/distributions/binomial.hpp
@@ -80,6 +80,7 @@
 #define BOOST_MATH_SPECIAL_BINOMIAL_HPP
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for incomplete beta.
 #include <boost/math/distributions/complement.hpp> // complements
@@ -420,17 +421,17 @@ namespace boost
       #endif
 
       template <class RealType, class Policy>
-      BOOST_MATH_CUDA_ENABLED const std::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED const boost::math::pair<RealType, RealType> range(const binomial_distribution<RealType, Policy>& dist)
       { // Range of permissible values for random variable k.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(static_cast<RealType>(0), dist.trials());
+        return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), dist.trials());
       }
 
       template <class RealType, class Policy>
-      BOOST_MATH_CUDA_ENABLED const std::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
+      BOOST_MATH_CUDA_ENABLED const boost::math::pair<RealType, RealType> support(const binomial_distribution<RealType, Policy>& dist)
       { // Range of supported values for random variable k.
         // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-        return std::pair<RealType, RealType>(static_cast<RealType>(0),  dist.trials());
+        return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  dist.trials());
       }
 
       template <class RealType, class Policy>
diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index a1fcb63e5c..1276d34343 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -1,5 +1,6 @@
 // Copyright John Maddock 2006, 2007.
 // Copyright Paul A. Bristow 2007.
+// Copyright Matt Borland 2024.
 
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
@@ -14,6 +15,7 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -196,35 +198,35 @@ cauchy_distribution(RealType,RealType)->cauchy_distribution<typename boost::math
 #endif
 
 template <class RealType, class Policy>
-BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> range(const cauchy_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const cauchy_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
   BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
   { 
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   #endif
   { // Can only use max_value.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+   return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
   }
 }
 
 template <class RealType, class Policy>
-BOOST_MATH_GPU_ENABLED inline const std::pair<RealType, RealType> support(const cauchy_distribution<RealType, Policy>& )
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const cauchy_distribution<RealType, Policy>& )
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
   BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
   { 
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   #endif
   { // Can only use max_value.
      using boost::math::tools::max_value;
-     return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+     return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
   }
 }
 

From 6d5e17cc604fe98ede0c79ea75d129e6dd812b33 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 15:43:21 -0400
Subject: [PATCH 147/399] Fix usages of std::numeric_limits and add testing

---
 include/boost/math/distributions/cauchy.hpp |  29 +++--
 test/cuda_jamfile                           |   2 +
 test/test_cauchy_range_support_double.cu    | 110 +++++++++++++++++++
 test/test_cauchy_range_support_float.cu     | 111 ++++++++++++++++++++
 4 files changed, 236 insertions(+), 16 deletions(-)
 create mode 100644 test/test_cauchy_range_support_double.cu
 create mode 100644 test/test_cauchy_range_support_float.cu

diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index 1276d34343..91c848c911 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -16,6 +16,7 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -79,11 +80,11 @@ BOOST_MATH_GPU_ENABLED RealType cdf_imp(const cauchy_distribution<RealType, Poli
       return static_cast<RealType>((complement) ? 1 : 0);
    }
    #else
-   if(std::numeric_limits<RealType>::has_infinity && x == std::numeric_limits<RealType>::infinity())
+   if(boost::math::numeric_limits<RealType>::has_infinity && x == boost::math::numeric_limits<RealType>::infinity())
    { // cdf +infinity is unity.
      return static_cast<RealType>((complement) ? 0 : 1);
    }
-   if(std::numeric_limits<RealType>::has_infinity && x == -std::numeric_limits<RealType>::infinity())
+   if(boost::math::numeric_limits<RealType>::has_infinity && x == -boost::math::numeric_limits<RealType>::infinity())
    { // cdf -infinity is zero.
      return static_cast<RealType>((complement) ? 1 : 0);
    }
@@ -200,13 +201,11 @@ cauchy_distribution(RealType,RealType)->cauchy_distribution<typename boost::math
 template <class RealType, class Policy>
 BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const cauchy_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-  #ifndef BOOST_MATH_HAS_GPU_SUPPORT
-  BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-     return boost::math::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
-  #endif
   { // Can only use max_value.
    using boost::math::tools::max_value;
    return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
@@ -217,13 +216,11 @@ template <class RealType, class Policy>
 BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const cauchy_distribution<RealType, Policy>& )
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-  #ifndef BOOST_MATH_HAS_GPU_SUPPORT
-  BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-     return boost::math::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
-  #endif
   { // Can only use max_value.
      using boost::math::tools::max_value;
      return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
@@ -252,7 +249,7 @@ BOOST_MATH_GPU_ENABLED inline RealType pdf(const cauchy_distribution<RealType, P
      return 0; // pdf + and - infinity is zero.
    }
    // These produce MSVC 4127 warnings, so the above used instead.
-   //if(std::numeric_limits<RealType>::has_infinity && abs(x) == std::numeric_limits<RealType>::infinity())
+   //if(boost::math::numeric_limits<RealType>::has_infinity && abs(x) == boost::math::numeric_limits<RealType>::infinity())
    //{ // pdf + and - infinity is zero.
    //  return 0;
    //}
@@ -301,7 +298,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mean(const cauchy_distribution<RealType,
       "boost::math::mean(cauchy<%1%>&)",
       "The Cauchy distribution does not have a mean: "
       "the only possible return value is %1%.",
-      std::numeric_limits<RealType>::quiet_NaN(), Policy());
+      boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
@@ -315,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline RealType variance(const cauchy_distribution<RealTy
       "boost::math::variance(cauchy<%1%>&)",
       "The Cauchy distribution does not have a variance: "
       "the only possible return value is %1%.",
-      std::numeric_limits<RealType>::quiet_NaN(), Policy());
+      boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
@@ -341,7 +338,7 @@ BOOST_MATH_GPU_ENABLED inline RealType skewness(const cauchy_distribution<RealTy
       "boost::math::skewness(cauchy<%1%>&)",
       "The Cauchy distribution does not have a skewness: "
       "the only possible return value is %1%.",
-      std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+      boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
 
 template <class RealType, class Policy>
@@ -355,7 +352,7 @@ BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const cauchy_distribution<RealTy
       "boost::math::kurtosis(cauchy<%1%>&)",
       "The Cauchy distribution does not have a kurtosis: "
       "the only possible return value is %1%.",
-      std::numeric_limits<RealType>::quiet_NaN(), Policy());
+      boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
@@ -369,7 +366,7 @@ BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const cauchy_distribution
       "boost::math::kurtosis_excess(cauchy<%1%>&)",
       "The Cauchy distribution does not have a kurtosis: "
       "the only possible return value is %1%.",
-      std::numeric_limits<RealType>::quiet_NaN(), Policy());
+      boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 8c10d4810a..3fd3e9db8c 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -36,6 +36,8 @@ run test_cauchy_pdf_double.cu ;
 run test_cauchy_pdf_float.cu ;
 run test_cauchy_quan_double.cu ;
 run test_cauchy_quan_float.cu ;
+run test_cauchy_range_support_double.cu ;
+run test_cauchy_range_support_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_cauchy_range_support_double.cu b/test/test_cauchy_range_support_double.cu
new file mode 100644
index 0000000000..4ec792ce30
--- /dev/null
+++ b/test/test_cauchy_range_support_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = support(boost::math::cauchy_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(support(boost::math::cauchy_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_cauchy_range_support_float.cu b/test/test_cauchy_range_support_float.cu
new file mode 100644
index 0000000000..1cdd90e407
--- /dev/null
+++ b/test/test_cauchy_range_support_float.cu
@@ -0,0 +1,111 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::cauchy_distribution<float_type>(in1[i])).first;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::cauchy_distribution<float_type>(input_vector1[i])).first);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            std::cerr << "Device got: " << output_vector[i] << ", and serial got: " << results[i] << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file

From 92a15947b0bca7e52a13f2c10d4e1051b04231dc Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 16:00:06 -0400
Subject: [PATCH 148/399] Add GPU support to the exponential dist

---
 .../boost/math/distributions/exponential.hpp  | 70 ++++++++++---------
 1 file changed, 37 insertions(+), 33 deletions(-)

diff --git a/include/boost/math/distributions/exponential.hpp b/include/boost/math/distributions/exponential.hpp
index 164e01f205..0d6c15d3d4 100644
--- a/include/boost/math/distributions/exponential.hpp
+++ b/include/boost/math/distributions/exponential.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -6,6 +7,9 @@
 #ifndef BOOST_STATS_EXPONENTIAL_HPP
 #define BOOST_STATS_EXPONENTIAL_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/log1p.hpp>
@@ -29,7 +33,7 @@ namespace detail{
 // Error check:
 //
 template <class RealType, class Policy>
-inline bool verify_lambda(const char* function, RealType l, RealType* presult, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool verify_lambda(const char* function, RealType l, RealType* presult, const Policy& pol)
 {
    if((l <= 0) || !(boost::math::isfinite)(l))
    {
@@ -42,7 +46,7 @@ inline bool verify_lambda(const char* function, RealType l, RealType* presult, c
 }
 
 template <class RealType, class Policy>
-inline bool verify_exp_x(const char* function, RealType x, RealType* presult, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool verify_exp_x(const char* function, RealType x, RealType* presult, const Policy& pol)
 {
    if((x < 0) || (boost::math::isnan)(x))
    {
@@ -63,14 +67,14 @@ class exponential_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit exponential_distribution(RealType l_lambda = 1)
+   BOOST_MATH_GPU_ENABLED explicit exponential_distribution(RealType l_lambda = 1)
       : m_lambda(l_lambda)
    {
       RealType err;
       detail::verify_lambda("boost::math::exponential_distribution<%1%>::exponential_distribution", l_lambda, &err, Policy());
    } // exponential_distribution
 
-   RealType lambda()const { return m_lambda; }
+   BOOST_MATH_GPU_ENABLED RealType lambda()const { return m_lambda; }
 
 private:
    RealType m_lambda;
@@ -84,21 +88,21 @@ exponential_distribution(RealType)->exponential_distribution<typename boost::mat
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const exponential_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-    return std::pair<RealType, RealType>(static_cast<RealType>(0), std::numeric_limits<RealType>::infinity()); // 0 to + infinity.
+    return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), boost::math::numeric_limits<RealType>::infinity()); // 0 to + infinity.
   }
   else
   {
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + max
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + max
   }
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const exponential_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
@@ -108,11 +112,11 @@ inline std::pair<RealType, RealType> support(const exponential_distribution<Real
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType lambda = dist.lambda();
    RealType result = 0;
@@ -128,11 +132,11 @@ inline RealType pdf(const exponential_distribution<RealType, Policy>& dist, cons
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logpdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logpdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType lambda = dist.lambda();
    RealType result = -std::numeric_limits<RealType>::infinity();
@@ -146,11 +150,11 @@ inline RealType logpdf(const exponential_distribution<RealType, Policy>& dist, c
 } // logpdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = dist.lambda();
@@ -164,11 +168,11 @@ inline RealType cdf(const exponential_distribution<RealType, Policy>& dist, cons
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType logcdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const exponential_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = dist.lambda();
@@ -182,11 +186,11 @@ inline RealType logcdf(const exponential_distribution<RealType, Policy>& dist, c
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const exponential_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const exponential_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = dist.lambda();
@@ -205,11 +209,11 @@ inline RealType quantile(const exponential_distribution<RealType, Policy>& dist,
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = c.dist.lambda();
@@ -226,11 +230,11 @@ inline RealType cdf(const complemented2_type<exponential_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-inline RealType logcdf(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = c.dist.lambda();
@@ -247,11 +251,11 @@ inline RealType logcdf(const complemented2_type<exponential_distribution<RealTyp
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<exponential_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const exponential_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const exponential_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    RealType lambda = c.dist.lambda();
@@ -272,7 +276,7 @@ inline RealType quantile(const complemented2_type<exponential_distribution<RealT
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const exponential_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const exponential_distribution<RealType, Policy>& dist)
 {
    RealType result = 0;
    RealType lambda = dist.lambda();
@@ -282,7 +286,7 @@ inline RealType mean(const exponential_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType standard_deviation(const exponential_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType standard_deviation(const exponential_distribution<RealType, Policy>& dist)
 {
    RealType result = 0;
    RealType lambda = dist.lambda();
@@ -292,38 +296,38 @@ inline RealType standard_deviation(const exponential_distribution<RealType, Poli
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const exponential_distribution<RealType, Policy>& /*dist*/)
 {
    return 0;
 }
 
 template <class RealType, class Policy>
-inline RealType median(const exponential_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const exponential_distribution<RealType, Policy>& dist)
 {
    using boost::math::constants::ln_two;
    return ln_two<RealType>() / dist.lambda(); // ln(2) / lambda
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const exponential_distribution<RealType, Policy>& /*dist*/)
 {
    return 2;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const exponential_distribution<RealType, Policy>& /*dist*/)
 {
    return 9;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const exponential_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const exponential_distribution<RealType, Policy>& /*dist*/)
 {
    return 6;
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const exponential_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const exponential_distribution<RealType, Policy>& dist)
 {
    using std::log;
    return 1 - log(dist.lambda());

From 9456724b51e9169a77271c2a2cddaafa2678f1fe Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 16:13:18 -0400
Subject: [PATCH 149/399] Add exponential dist CUDA testing

---
 .../boost/math/distributions/exponential.hpp  |   2 +-
 test/cuda_jamfile                             |   8 ++
 test/test_exponential_cdf_double.cu           | 110 +++++++++++++++++
 test/test_exponential_cdf_float.cu            | 110 +++++++++++++++++
 test/test_exponential_pdf_double.cu           | 110 +++++++++++++++++
 test/test_exponential_pdf_float.cu            | 110 +++++++++++++++++
 test/test_exponential_quan_double.cu          | 110 +++++++++++++++++
 test/test_exponential_quan_float.cu           | 110 +++++++++++++++++
 test/test_exponential_range_support_double.cu | 110 +++++++++++++++++
 test/test_exponential_range_support_float.cu  | 111 ++++++++++++++++++
 10 files changed, 890 insertions(+), 1 deletion(-)
 create mode 100644 test/test_exponential_cdf_double.cu
 create mode 100644 test/test_exponential_cdf_float.cu
 create mode 100644 test/test_exponential_pdf_double.cu
 create mode 100644 test/test_exponential_pdf_float.cu
 create mode 100644 test/test_exponential_quan_double.cu
 create mode 100644 test/test_exponential_quan_float.cu
 create mode 100644 test/test_exponential_range_support_double.cu
 create mode 100644 test/test_exponential_range_support_float.cu

diff --git a/include/boost/math/distributions/exponential.hpp b/include/boost/math/distributions/exponential.hpp
index 0d6c15d3d4..2cd4c8e8e8 100644
--- a/include/boost/math/distributions/exponential.hpp
+++ b/include/boost/math/distributions/exponential.hpp
@@ -107,7 +107,7 @@ BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(cons
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
    using boost::math::tools::min_value;
-   return std::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
    // min_value<RealType>() to avoid a discontinuity at x = 0.
 }
 
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 3fd3e9db8c..7ce67a94de 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -38,6 +38,14 @@ run test_cauchy_quan_double.cu ;
 run test_cauchy_quan_float.cu ;
 run test_cauchy_range_support_double.cu ;
 run test_cauchy_range_support_float.cu ;
+run test_exponential_cdf_double.cu ;
+run test_exponential_cdf_float.cu ;
+run test_exponential_pdf_double.cu ;
+run test_exponential_pdf_float.cu ;
+run test_exponential_quan_double.cu ;
+run test_exponential_quan_float.cu ;
+run test_exponential_range_support_double.cu ;
+run test_exponential_range_support_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_exponential_cdf_double.cu b/test/test_exponential_cdf_double.cu
new file mode 100644
index 0000000000..8601d1c081
--- /dev/null
+++ b/test/test_exponential_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_cdf_float.cu b/test/test_exponential_cdf_float.cu
new file mode 100644
index 0000000000..aa5ef9153e
--- /dev/null
+++ b/test/test_exponential_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_pdf_double.cu b/test/test_exponential_pdf_double.cu
new file mode 100644
index 0000000000..9a5615f1bc
--- /dev/null
+++ b/test/test_exponential_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_pdf_float.cu b/test/test_exponential_pdf_float.cu
new file mode 100644
index 0000000000..f15ee3ea81
--- /dev/null
+++ b/test/test_exponential_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_quan_double.cu b/test/test_exponential_quan_double.cu
new file mode 100644
index 0000000000..ea5a5a6813
--- /dev/null
+++ b/test/test_exponential_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_quan_float.cu b/test/test_exponential_quan_float.cu
new file mode 100644
index 0000000000..ea5a5a6813
--- /dev/null
+++ b/test/test_exponential_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::exponential_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_exponential_range_support_double.cu b/test/test_exponential_range_support_double.cu
new file mode 100644
index 0000000000..eec3981d2a
--- /dev/null
+++ b/test/test_exponential_range_support_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = support(boost::math::exponential_distribution<float_type>(in1[i])).second;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(support(boost::math::exponential_distribution<float_type>(input_vector1[i])).second);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_exponential_range_support_float.cu b/test/test_exponential_range_support_float.cu
new file mode 100644
index 0000000000..00f443e52f
--- /dev/null
+++ b/test/test_exponential_range_support_float.cu
@@ -0,0 +1,111 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type* in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = range(boost::math::exponential_distribution<float_type>(in1[i])).first;
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(range(boost::math::exponential_distribution<float_type>(input_vector1[i])).first);
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            std::cerr << "Device got: " << output_vector[i] << ", and serial got: " << results[i] << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file

From 2d1d6cf33607f3116703f92aaaeb0aba0c14abcb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 16:30:23 -0400
Subject: [PATCH 150/399] Adjust test tools definition of throw in GPU
 environment

---
 include_private/boost/math/tools/test.hpp | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/include_private/boost/math/tools/test.hpp b/include_private/boost/math/tools/test.hpp
index 8f4db18c15..7547ef5be2 100644
--- a/include_private/boost/math/tools/test.hpp
+++ b/include_private/boost/math/tools/test.hpp
@@ -306,7 +306,9 @@ void test_check_throw(Val v, boost::math::rounding_error const*)
   // exception-free testing support, ideally we'd only define this in our tests,
   // but to keep things simple we really need it somewhere that's always included:
   //
-#ifdef BOOST_MATH_NO_EXCEPTIONS
+#if defined(BOOST_MATH_NO_EXCEPTIONS) && defined(BOOST_MATH_HAS_GPU_SUPPORT)
+#  define BOOST_MATH_CHECK_THROW(x, y)
+#elif defined(BOOST_MATH_NO_EXCEPTIONS) 
 #  define BOOST_MATH_CHECK_THROW(x, ExceptionType) boost::math::tools::test_check_throw(x, static_cast<ExceptionType const*>(nullptr));
 #else
 #  define BOOST_MATH_CHECK_THROW(x, y) BOOST_CHECK_THROW(x, y)

From 70420396265dba32048eec205a3a0435332a5841 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 16:31:23 -0400
Subject: [PATCH 151/399] Add SYCL testing of exponential dist

---
 test/sycl_jamfile              | 1 +
 test/test_exponential_dist.cpp | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 92580c93b7..f02065a390 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -13,6 +13,7 @@ project : requirements
 run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
+run test_exponential_dist.cpp ;
 
 # Special Functions
 run pow_test.cpp ;
diff --git a/test/test_exponential_dist.cpp b/test/test_exponential_dist.cpp
index d1898fa7c4..1b21df1411 100644
--- a/test/test_exponential_dist.cpp
+++ b/test/test_exponential_dist.cpp
@@ -8,7 +8,7 @@
 
 // test_exponential_dist.cpp
 
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 #include <boost/math/distributions/exponential.hpp>
     using boost::math::exponential_distribution;

From 8a7c17b97cf15b843a307f118eb089e2c6d50e39 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 26 Jul 2024 16:45:26 -0400
Subject: [PATCH 152/399] Fix use of std::numeric_limits

---
 include/boost/math/distributions/exponential.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/exponential.hpp b/include/boost/math/distributions/exponential.hpp
index 2cd4c8e8e8..01c442fa81 100644
--- a/include/boost/math/distributions/exponential.hpp
+++ b/include/boost/math/distributions/exponential.hpp
@@ -139,7 +139,7 @@ BOOST_MATH_GPU_ENABLED inline RealType logpdf(const exponential_distribution<Rea
    constexpr auto function = "boost::math::logpdf(const exponential_distribution<%1%>&, %1%)";
 
    RealType lambda = dist.lambda();
-   RealType result = -std::numeric_limits<RealType>::infinity();
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
    if(0 == detail::verify_lambda(function, lambda, &result, Policy()))
       return result;
    if(0 == detail::verify_exp_x(function, x, &result, Policy()))

From 49524ce235f24c4c174b2fc7e15c5282d5ef930d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 10:30:56 -0400
Subject: [PATCH 153/399] Add GPU support to landau dist

---
 include/boost/math/distributions/landau.hpp | 584 ++++++++++----------
 1 file changed, 294 insertions(+), 290 deletions(-)

diff --git a/include/boost/math/distributions/landau.hpp b/include/boost/math/distributions/landau.hpp
index 8dff2041dd..1ffa503459 100644
--- a/include/boost/math/distributions/landau.hpp
+++ b/include/boost/math/distributions/landau.hpp
@@ -1,4 +1,5 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,6 +12,9 @@
 #pragma warning(disable : 4127) // conditional expression is constant
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -28,7 +32,7 @@ class landau_distribution;
 namespace detail {
 
 template <class RealType>
-inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -36,7 +40,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 6.1179e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.62240126375351657026e-1),
             static_cast<RealType>(3.37943593381366824691e-1),
             static_cast<RealType>(1.53537606095123787618e-1),
@@ -46,7 +50,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(3.46237168332264544791e-7),
             static_cast<RealType>(2.54512306953704347532e-8),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.61596691542333069131e0),
             static_cast<RealType>(1.31560197919990191004e0),
@@ -63,7 +67,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.1560e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(1.63531240868022603476e-1),
             static_cast<RealType>(1.42818648212508067982e-1),
             static_cast<RealType>(4.95816076364679661943e-2),
@@ -71,7 +75,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(5.76649181954629544285e-4),
             static_cast<RealType>(-5.66279925274108366994e-7),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.41478104966077351483e0),
             static_cast<RealType>(9.41180365857002724714e-1),
@@ -88,7 +92,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 9.1732e-19
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(9.55242261334771588094e-2),
             static_cast<RealType>(6.66529732353979943139e-2),
             static_cast<RealType>(1.80958840194356287100e-2),
@@ -98,7 +102,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(4.37245276130361710865e-9),
             static_cast<RealType>(-8.10479404400603805292e-11),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.21670723402658089612e0),
             static_cast<RealType>(6.58224466688607822769e-1),
@@ -115,7 +119,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 7.6621e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.83643820409470770350e-2),
             static_cast<RealType>(1.97555000044256883088e-2),
             static_cast<RealType>(3.71748668368617282698e-3),
@@ -125,7 +129,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(5.36581791174380716937e-11),
             static_cast<RealType>(-5.50656207669255770963e-13),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.09290785092251223006e-1),
             static_cast<RealType>(3.49404120360701349529e-1),
@@ -142,7 +146,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.6311e-19
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.12656323880287532947e-2),
             static_cast<RealType>(2.87311140580416132088e-3),
             static_cast<RealType>(2.61788674390925516376e-4),
@@ -152,7 +156,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(4.33383971045699197233e-14),
             static_cast<RealType>(-1.75185581239955717728e-16),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.94430267268436822392e-1),
             static_cast<RealType>(1.00370783567964448346e-1),
@@ -169,7 +173,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 5.6459e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.83847488747490686627e-3),
             static_cast<RealType>(4.95641151588714788287e-4),
             static_cast<RealType>(2.79159792287747766415e-5),
@@ -178,7 +182,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(-4.86595415551823027835e-14),
             static_cast<RealType>(9.68524606019510324447e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.01847536766892219351e-1),
             static_cast<RealType>(3.63152433272831196527e-2),
@@ -195,7 +199,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.5205e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(6.85767880395157523315e-4),
             static_cast<RealType>(4.08288098461672797376e-5),
             static_cast<RealType>(8.10640732723079320426e-7),
@@ -203,7 +207,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(1.37951861368789813737e-11),
             static_cast<RealType>(-1.25906441382637535543e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.23722380864018634550e-1),
             static_cast<RealType>(6.05800403141772433527e-3),
@@ -220,7 +224,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 3.5572e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(6.78613480244945294595e-1),
             static_cast<RealType>(9.61675759893298556080e-1),
             static_cast<RealType>(3.45159462006746978086e-1),
@@ -229,7 +233,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(4.69867700169714338273e-4),
             static_cast<RealType>(1.76219117171149694118e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.44693640094228656726e0),
             static_cast<RealType>(5.46298626321591162873e-1),
@@ -246,7 +250,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 5.7408e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.51438485661317103070e-1),
             static_cast<RealType>(2.67941671074735988081e-1),
             static_cast<RealType>(5.18564629295719783781e-2),
@@ -257,7 +261,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(3.35670921544537716055e-8),
             static_cast<RealType>(5.06987792821954864905e-10),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.23792506680780833665e-1),
             static_cast<RealType>(8.17040643791396371682e-2),
@@ -276,7 +280,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.0195e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(6.36745544906925230102e-1),
             static_cast<RealType>(2.06319686601209029700e-1),
             static_cast<RealType>(3.27498059700133287053e-2),
@@ -288,7 +292,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(1.76754192209232807941e-10),
             static_cast<RealType>(-2.78616504641875874275e-17),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.24145654925686670201e-1),
             static_cast<RealType>(5.14350019501887110402e-2),
@@ -307,7 +311,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 8.0433e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.36619776379492082324e-1),
             static_cast<RealType>(2.68158440168597706495e-1),
             static_cast<RealType>(5.49040993767853738389e-2),
@@ -318,7 +322,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(9.57557353473514565245e-8),
             static_cast<RealType>(5.16773829224576217348e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.21222294324039934056e-1),
             static_cast<RealType>(8.62431574655015481812e-2),
@@ -341,7 +345,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 
 
 template <class RealType>
-inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -350,7 +354,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 7.4629e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62240126375351657025589608183516471315e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94698530837122818345222883832757839888e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06728003509081587907620543204047536319e0),
@@ -366,7 +370,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55873076454666680466531097660277995317e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.80771940886011613393622410616035955976e-13),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35771004134750535117224809381897395331e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.37002484862962406489509174332580745411e0),
@@ -390,7 +394,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 6.6684e-38
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63531240868022603475813051802104652763e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.17803013130262393286657457221415701909e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77780575692956605214628767143941600132e-1),
@@ -405,7 +409,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.14296339768511312584670061679121003569e-12),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.52631422678659858574974085885146420544e-15),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.48481735580594347909096198787726314434e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.91598585888012869317473155570063821216e0),
@@ -429,7 +433,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 6.3397e-35
         // LCOV_EXCL_START
-        static const RealType P[12] = {
+        BOOST_MATH_STATIC const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55242261334771588093967856464157010584e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48866040463435403672044647455806606078e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04241715667984551487882549843428953917e-1),
@@ -443,7 +447,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18067019247793233704208913546277631267e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96745094401496364651919224112160111958e-12),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07735872062601280828576861757316683396e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00667909426245388114411629440735066799e0),
@@ -468,7 +472,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 8.0238e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83643820409470770350079809236512802618e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.02996762669868036727057860510914079553e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88220267784864518806154823373656292346e-2),
@@ -484,7 +488,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11666384975358223644665199669986358056e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.30202644697506464624965700043476935471e-22),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.44479208003384373099160875893986831861e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.54290037675901616362332580709754113529e-1),
@@ -508,7 +512,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 3.2541e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.12656323880287532946687856443190592955e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31374972240605659239154788518240221417e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10776910971729651587578902049263096117e-3),
@@ -524,7 +528,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.65525705592205245661726488519562256000e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60698835222044786453848932477732972928e-26),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.88605948104664828377228254521124685930e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.58594705700945215121673591119784576258e-1),
@@ -549,7 +553,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 4.1276e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83847488747490686627461184914507143000e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61220392257287638364190361688188696363e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42217711448675893329072184826328300776e-4),
@@ -565,7 +569,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.94920633206242554892676642458535141153e-28),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18030442958390399095902441284074544279e-31),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65871972115253665568580046072625013145e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.74531522538358367003224536101724206626e-2),
@@ -590,7 +594,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.8458e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85767880395157523314894776472286059373e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07684379950498990874449661385130414967e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.29181715091139597455177955800910928786e-6),
@@ -606,7 +610,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35979606245171162602352579985003194602e-33),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.50946115943875327149319867495704969908e-36),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21212467547297045538111676107434471585e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17663841151156626845609176694801024524e-2),
@@ -630,7 +634,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 2.6634e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78613480244945294594505480426643613242e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07362312709864018864207848733814857157e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.47727521897653923649758175033206259109e-1),
@@ -645,7 +649,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30306828175920576070486704404727265760e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.05908347665846652276910544097430115068e-13),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07218191317166728296013167220324207427e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.38908532499742180532814291654329829544e-1),
@@ -669,7 +673,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 6.1919e-36
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.51438485661317103069553924870169052838e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.29652867028564588922931020456447362877e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90557738902930002845457640269863338815e-1),
@@ -690,7 +694,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.15896012319823666881998903857141624070e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62176014448801854863922778456328119208e-25),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.79042471052521112984740498925369905803e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.55058068535501327896327971200536085268e-1),
@@ -719,7 +723,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.2411e-36
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36745544906925230101752563433306496000e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.73688900814770369626527563956988302379e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81718746296195151971617726268038570065e-2),
@@ -739,7 +743,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73017950634516660552375272495618707905e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68519137981001059472024985205381913202e-24),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.29948066505039082395951244410552705780e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.13730690908098361287472898564563217987e-2),
@@ -768,7 +772,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 2.0348e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619776379492082323649724050601750141e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29818158612993476124594583743266388964e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07736315744724186061845512973085067283e-2),
@@ -789,7 +793,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.50639358104925465711435411537609380290e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.47593981758247424082096107205150226114e-40),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60997521267746350015610841742718472657e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.40470704349086277215167519790809981379e-2),
@@ -818,7 +822,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 4.3963e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344984274685280416528592e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72417390936686577479751162141499390532e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74319117326966091295365258834959120634e-2),
@@ -838,7 +842,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07464506614287925844993490382319608619e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60173555862875972119871402681133785088e-23),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27912237038396638341492536677313983747e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02138359905285600768927677649467546192e-2),
@@ -869,7 +873,7 @@ inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_
 }
 
 template <class RealType>
-inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -879,7 +883,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 9.3928e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(2.21762208692280384264e-1),
             static_cast<RealType>(7.10041055270973473923e-1),
             static_cast<RealType>(8.66556480457430718380e-1),
@@ -890,7 +894,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-2.76271972015177236271e-4),
             static_cast<RealType>(1.89483904652983701680e-5),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1),
             static_cast<RealType>(2.18155995697310361937e0),
             static_cast<RealType>(2.53173077603836285217e0),
@@ -908,7 +912,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.4742e-18
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             static_cast<RealType>(6.50763682207511020789e-3),
             static_cast<RealType>(5.73790055136022120436e-2),
             static_cast<RealType>(2.22375662069496257066e-1),
@@ -921,7 +925,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(1.09503400950148681072e-3),
             static_cast<RealType>(-9.00045301380982997382e-5),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.07919389927659014373e0),
             static_cast<RealType>(2.56142472873207168042e0),
@@ -948,7 +952,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 5.8685e-18
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(6.31126317567898819465e-1),
                 static_cast<RealType>(5.28493759149515726917e-1),
                 static_cast<RealType>(3.28301410420682938866e-1),
@@ -958,7 +962,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 static_cast<RealType>(9.97883658430364658707e-4),
                 static_cast<RealType>(6.05131104440018116255e-5),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1),
                 static_cast<RealType>(8.47781139548258655981e-1),
                 static_cast<RealType>(5.21797290075642096762e-1),
@@ -976,7 +980,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 3.2532e-17
-            static const RealType P[9] = {
+            BOOST_MATH_STATIC const RealType P[9] = {
                 static_cast<RealType>(6.26864481454444278646e-1),
                 static_cast<RealType>(5.10647753508714204745e-1),
                 static_cast<RealType>(1.98551443303285119497e-1),
@@ -987,7 +991,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 static_cast<RealType>(4.17249760274638104772e-6),
                 static_cast<RealType>(7.73502439313710606153e-12),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1),
                 static_cast<RealType>(8.15124079722976906223e-1),
                 static_cast<RealType>(3.16755852188961901369e-1),
@@ -1009,7 +1013,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1020,7 +1024,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 1.2803e-36
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21762208692280384264052188465103527015e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07121154108880017947709737976750200391e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34036993772851526455115746887751392080e0),
@@ -1038,7 +1042,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98034330388999615249606466662289782222e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.67931741921878993598048665757824165533e-12),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81019852414657529520034272090632311645e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.51602582973416348091361820936922274106e0),
@@ -1064,7 +1068,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 3.8590e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.50763682207511020788551990942118742910e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35160148798611192350830963080055471564e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85567614778755464918744664468938413626e-1),
@@ -1085,7 +1089,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.51522041748753421579496885726802106514e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.28554063325397021905295499768922434904e-10),
         };
-        static const RealType Q[19] = {
+        BOOST_MATH_STATIC const RealType Q[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.55889733194498836168215560931863059152e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45050534010127542130960211621894286688e0),
@@ -1121,7 +1125,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             // Rational Approximation
             // Maximum Relative Error: 7.0019e-35
             // LCOV_EXCL_START
-            static const RealType P[18] = {
+            BOOST_MATH_STATIC const RealType P[18] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31126317567898819464557840628449107915e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.31008645911415314700225107327351636697e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.60743397071713227215207831174512626190e-1),
@@ -1141,7 +1145,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.05432616288832680241611577865488417904e-13),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08723511461992818779941378551362882730e-14),
             };
-            static const RealType Q[16] = {
+            BOOST_MATH_STATIC const RealType Q[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01021278581037282130358759075689669228e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.91783545335316986601746168681457332835e-1),
@@ -1168,7 +1172,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
             // Rational Approximation
             // Maximum Relative Error: 6.4095e-35
             // LCOV_EXCL_START
-            static const RealType P[18] = {
+            BOOST_MATH_STATIC const RealType P[18] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.26864481454444278645937156746132802908e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35052316263030534355724898036735352905e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46701697626917441774916114124028252971e0),
@@ -1188,7 +1192,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53199672688507288037695102377982544434e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.97283413733676690377949556457649405210e-14),
             };
-            static const RealType Q[18] = {
+            BOOST_MATH_STATIC const RealType Q[18] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15492787140203223641846510939273526038e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34095796298757853634036909432345998054e0),
@@ -1220,7 +1224,7 @@ inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
     if (x >= 0) {
         return landau_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1228,12 +1232,12 @@ inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_const
         return landau_pdf_minus_imp_prec<RealType>(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return landau_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1241,18 +1245,18 @@ inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_const
         return landau_pdf_minus_imp_prec<RealType>(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType landau_pdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x) {
     //
     // This calculates the pdf of the Landau distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::pdf(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::pdf(landau<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -1289,7 +1293,7 @@ inline RealType landau_pdf_imp(const landau_distribution<RealType, Policy>& dist
 }
 
 template <class RealType>
-inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1297,7 +1301,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 2.7348e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(6.34761298487625202628e-1),
             static_cast<RealType>(7.86558857265845597915e-1),
             static_cast<RealType>(4.30220871807399303399e-1),
@@ -1306,7 +1310,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(1.48926177023501002834e-3),
             static_cast<RealType>(-5.93750588554108593271e-7),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.65227304522196452589e0),
             static_cast<RealType>(1.29276828719607419526e0),
@@ -1323,7 +1327,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 6.1487e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(4.22133240358047652363e-1),
             static_cast<RealType>(3.48421126689016131480e-1),
             static_cast<RealType>(1.15402429637790321091e-1),
@@ -1331,7 +1335,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(1.26628667888851698698e-3),
             static_cast<RealType>(-5.75103242931559285281e-7),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.21277435324167238159e0),
             static_cast<RealType>(6.38324046905267845243e-1),
@@ -1347,7 +1351,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 3.2975e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(2.95892137955791216378e-1),
             static_cast<RealType>(2.29083899043580095868e-1),
             static_cast<RealType>(7.09374171394372356009e-2),
@@ -1355,7 +1359,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(7.69674715320139398655e-4),
             static_cast<RealType>(1.63486840000680408991e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.09704883482087441931e0),
             static_cast<RealType>(5.10139057077147935327e-1),
@@ -1372,7 +1376,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.6740e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.73159318667565938776e-1),
             static_cast<RealType>(6.95847424776057206679e-2),
             static_cast<RealType>(1.04513924567165899506e-2),
@@ -1382,7 +1386,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(-4.55493341295654514558e-11),
             static_cast<RealType>(6.71119091495929467041e-13),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(6.23409270429130114247e-1),
             static_cast<RealType>(1.54791925441839372663e-1),
@@ -1398,7 +1402,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 7.6772e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(8.90469147411748292410e-2),
             static_cast<RealType>(2.76033447621178662228e-2),
             static_cast<RealType>(3.26577485081539607943e-3),
@@ -1407,7 +1411,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(3.19415703637929092564e-8),
             static_cast<RealType>(-1.79900915228302845362e-13),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.36499987260915480890e-1),
             static_cast<RealType>(7.67544181756713372678e-2),
@@ -1424,7 +1428,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.5678e-20
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.35157264931262089762e-2),
             static_cast<RealType>(8.46833474333913742597e-3),
             static_cast<RealType>(6.43769318301002170686e-4),
@@ -1434,7 +1438,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(1.04851094362145160445e-11),
             static_cast<RealType>(-8.50646541795105885254e-18),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1),
             static_cast<RealType>(2.59832721225510968607e-1),
             static_cast<RealType>(2.75929030381330309762e-2),
@@ -1452,7 +1456,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 2.2534e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.11253031965493064317e-2),
             static_cast<RealType>(1.36656844320536022509e-3),
             static_cast<RealType>(2.99036224749763963099e-5),
@@ -1461,7 +1465,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(-6.92803349600061706079e-16),
             static_cast<RealType>(5.47233092767314029032e-19),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(9.71506209641408410168e-2),
             static_cast<RealType>(3.52744690483830496158e-3),
@@ -1477,7 +1481,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 3.8057e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(6.60754766433212615409e-1),
             static_cast<RealType>(2.47190065739055522599e-1),
             static_cast<RealType>(4.17560046901040308267e-2),
@@ -1486,7 +1490,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(2.52070598577347523483e-6),
             static_cast<RealType>(-1.63741595848354479992e-8),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(3.92836792184266080580e-1),
             static_cast<RealType>(6.64332913820571574875e-2),
@@ -1502,7 +1506,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 1.5585e-18
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.44802371584831601817e-1),
             static_cast<RealType>(2.74177359656349204309e-1),
             static_cast<RealType>(5.53659240731871433983e-2),
@@ -1513,7 +1517,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(6.10941845734962836501e-8),
             static_cast<RealType>(1.39403332890347813312e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.32345127287830884682e-1),
             static_cast<RealType>(8.70500634789942065799e-2),
@@ -1532,7 +1536,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 8.4773e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.36685748306554972132e-1),
             static_cast<RealType>(2.22217783148381285219e-1),
             static_cast<RealType>(3.79173960692559280353e-2),
@@ -1543,7 +1547,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(2.18258684729250152138e-8),
             static_cast<RealType>(3.93038365129320422968e-10),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(3.49087806008685701060e-1),
             static_cast<RealType>(5.95568283529034601477e-2),
@@ -1562,7 +1566,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
         // Rational Approximation
         // Maximum Relative Error: 4.1441e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.36619774420718062663e-1),
             static_cast<RealType>(2.68594096777677177874e-1),
             static_cast<RealType>(5.50713044649497737064e-2),
@@ -1573,7 +1577,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             static_cast<RealType>(9.65240367429172366675e-8),
             static_cast<RealType>(5.21722720068664704240e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.21906621389193043384e-1),
             static_cast<RealType>(8.65058026826346828750e-2),
@@ -1596,7 +1600,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 
 
 template <class RealType>
-inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1605,7 +1609,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 2.6472e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.34761298487625202628055609797763667089e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.67589195401255255724121983550745957195e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07502511824371206858547365520593277966e0),
@@ -1621,7 +1625,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.49572523814120679048097861755172556652e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.50719933268462244255954307285373705456e-13),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05332427324361912631483249892199461926e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46280417679002004953145547112352398783e0),
@@ -1645,7 +1649,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.2387e-36
         // LCOV_EXCL_START
-        static const RealType P[12] = {
+        BOOST_MATH_STATIC const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.22133240358047652363270514524313049653e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35860518549481281929441026718420080571e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89900189271177970319691370395978805326e-1),
@@ -1659,7 +1663,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77487285800889132325390488044487626942e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41654614425073025870130302460301244273e-13),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13058739144695658589427075788960660400e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11792528400843967390452475642793635419e0),
@@ -1682,7 +1686,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.2281e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95892137955791216377776422765473500279e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.65957634570689820998348206103212047458e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.34657686985192350529330481818991619730e-1),
@@ -1697,7 +1701,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07058773850795175564735754911699285828e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.76765053309825506619419451346428518606e-16),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89758965744489334954041814073547951925e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65985298582650601001220682594742473012e0),
@@ -1721,7 +1725,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 5.3269e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73159318667565938775602634998889798568e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95149372103869634275319490207451722385e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.87504411659823400690797222216564651939e-2),
@@ -1737,7 +1741,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.73506415766100115673754920344659223382e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66918494546396383814682000746818494148e-21),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34854858486201481385140426291984169791e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.25379978655428608198799717171321453517e-1),
@@ -1761,7 +1765,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 4.8719e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.90469147411748292410422813492550092930e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.20196598836093298098360769875443462143e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92579652651763461802771336515384878994e-2),
@@ -1777,7 +1781,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76962456941948786610101052244821659252e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56004343709960620209823076030906442732e-25),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.22996422556023111037354479836605618488e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05244279198013248402385148537421114680e-1),
@@ -1802,7 +1806,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 5.3269e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35157264931262089761621934621402648954e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51407493866635569361305338029611888082e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30886132894858313459359493329266696766e-3),
@@ -1818,7 +1822,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02838174509144355795908173352005717435e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07343581702278433243268463675468320030e-30),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13166129191902183515154099741529804400e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.58587877615076239769720197025023333190e-2),
@@ -1842,7 +1846,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.0937e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.11253031965493064317003259449214452745e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66886306590939856622089350675801752704e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.77786526684921036345823450504680078696e-4),
@@ -1858,7 +1862,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.41009036423458926116066353864843586169e-31),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04965807080681693416200699806159303323e-34),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06133417626680943824361625182288165823e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87991711814130682492211639336942588926e-2),
@@ -1882,7 +1886,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 3.1671e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60754766433212615408805486898847664740e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.76143516602438873568296501921670869526e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.25254763859315398784817302471631188095e-1),
@@ -1897,7 +1901,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.08894662488905377548940479566994482806e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11472306961184868827300852021969296872e-12),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04202386226609593823214781180612848612e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07648212684952405730772649955008739292e-1),
@@ -1921,7 +1925,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 6.8517e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.44802371584831601817146389426921705500e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.32962058761590152378007743852342151897e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93461601407042255925193793376118641680e-1),
@@ -1941,7 +1945,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84493774639724473576782806157757824413e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03526708437207438952843827018631758857e-20),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.88770963972332750838571146142568699263e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60273143287476497658795203149608758815e-1),
@@ -1970,7 +1974,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 6.5315e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36685748306554972131586673701426039950e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75892450098649456865500477195142009984e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.77167300709199375935767980419262418694e-2),
@@ -1990,7 +1994,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29257874466803586327275841282905821499e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.06781616867813418930916928811492801723e-31),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.33391038950576592915531240096703257292e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.06598147816889621749840662500099582486e-2),
@@ -2018,7 +2022,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 1.0538e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619774420718062663274858007687066488e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30268560944740805268408378762250557522e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.09208091036436297425427953080968023835e-2),
@@ -2039,7 +2043,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58944184323201470938493323680744408698e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35050162268451658064792430214910233545e-40),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61705010674524952791495931314010679992e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42782564900556152436041716057503104160e-2),
@@ -2068,7 +2072,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
         // Rational Approximation
         // Maximum Relative Error: 2.2309e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344040890134127619524371e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72522424358877592972375801826826390634e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74749058021341871895402838175268752603e-2),
@@ -2088,7 +2092,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07931799710240978706633227327649731325e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60935135769719557933955672887720342220e-23),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.28077223152164982690351137450174450926e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02813709168750724641877726632095676090e-2),
@@ -2119,7 +2123,7 @@ inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_
 }
 
 template <class RealType>
-inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2129,7 +2133,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 4.8279e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(9.61609610406317335842e-2),
             static_cast<RealType>(3.91836314722738553695e-1),
             static_cast<RealType>(6.79862925205625107133e-1),
@@ -2139,7 +2143,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(3.16100502353317199197e-2),
             static_cast<RealType>(3.94935603975622336575e-3),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.76863983252615276767e0),
             static_cast<RealType>(1.81486018095087241378e0),
@@ -2157,7 +2161,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.3675e-17
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             static_cast<RealType>(7.07114056489178077423e-4),
             static_cast<RealType>(7.35277969197058909845e-3),
             static_cast<RealType>(3.45402694579204809691e-2),
@@ -2170,7 +2174,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(9.46543177731050647162e-3),
             static_cast<RealType>(1.50949646857411896396e-3),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.19520021153535414164e0),
             static_cast<RealType>(2.24057032777744601624e0),
@@ -2197,7 +2201,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 6.6532e-17
-            static const RealType P[9] = {
+            BOOST_MATH_STATIC const RealType P[9] = {
                 static_cast<RealType>(3.71658823632747235572e-1),
                 static_cast<RealType>(2.81493346318174084721e-1),
                 static_cast<RealType>(1.80052521696460721846e-1),
@@ -2208,7 +2212,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 static_cast<RealType>(8.36993181707604609065e-6),
                 static_cast<RealType>(-8.38295154747385945293e-6),
             };
-            static const RealType Q[9] = {
+            BOOST_MATH_STATIC const RealType Q[9] = {
                 static_cast<RealType>(1),
                 static_cast<RealType>(6.62107509936390708604e-1),
                 static_cast<RealType>(4.72501892305147483696e-1),
@@ -2227,7 +2231,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 
             // Rational Approximation
             // Maximum Relative Error: 2.6331e-17
-            static const RealType P[10] = {
+            BOOST_MATH_STATIC const RealType P[10] = {
                 static_cast<RealType>(3.97500903816385095134e-1),
                 static_cast<RealType>(5.08559630146730380854e-1),
                 static_cast<RealType>(2.99190443368166803486e-1),
@@ -2239,7 +2243,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 static_cast<RealType>(2.91644292826084281875e-6),
                 static_cast<RealType>(9.75453868235609527534e-12),
             };
-            static const RealType Q[9] = {
+            BOOST_MATH_STATIC const RealType Q[9] = {
                 static_cast<RealType>(1),
                 static_cast<RealType>(1.27376091725485414303e0),
                 static_cast<RealType>(7.49829208702328578188e-1),
@@ -2262,7 +2266,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2273,7 +2277,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 1.2055e-36
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61609610406317335842332400044553397267e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74152295981095898203847178356629061821e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58642905042588731020840168744866124345e0),
@@ -2291,7 +2295,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76463460016745893121574217030494989443e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.08380585744336744543979680558024295296e-12),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.66458574743150749245922924142120646408e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87010262350733534202724862784081296105e0),
@@ -2317,7 +2321,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 3.4133e-36
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07114056489178077422539043012078031613e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.18006784954579394004360967455655021959e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.60309646092161147676756546417366564213e-2),
@@ -2338,7 +2342,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.66563884565518965562535171848480872267e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.23954896921292896539048530795544784261e-6),
         };
-        static const RealType Q[19] = {
+        BOOST_MATH_STATIC const RealType Q[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77934931846682015134812629288297137499e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.85052416252910403272283619201501701345e0),
@@ -2374,7 +2378,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             // Rational Approximation
             // Maximum Relative Error: 9.2619e-35
             // LCOV_EXCL_START
-            static const RealType P[19] = {
+            BOOST_MATH_STATIC const RealType P[19] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71658823632747235572391863987803415545e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20402452680758356732340074285765302037e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53870483364594487885882489517365212394e-1),
@@ -2395,7 +2399,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07567013469555215514702758084138467446e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84619752008414239602732630339626773669e-14),
             };
-            static const RealType Q[17] = {
+            BOOST_MATH_STATIC const RealType Q[17] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.28669950018285475182750690468224641923e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.12421557061005325313661189943328446480e-1),
@@ -2423,7 +2427,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
             // Rational Approximation
             // Maximum Relative Error: 4.9208e-35
             // LCOV_EXCL_START
-            static const RealType P[20] = {
+            BOOST_MATH_STATIC const RealType P[20] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97500903816385095134217223320239082420e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02058997410109156148729828665298333233e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30492992901887465108077581566548743407e0),
@@ -2445,7 +2449,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.12671859603774617133607658779709622453e-14),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03211544596001317143519388487481133891e-20),
             };
-            static const RealType Q[19] = {
+            BOOST_MATH_STATIC const RealType Q[19] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.56188463983858614833914386500628633184e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27273165410457713017446497319550252691e0),
@@ -2478,7 +2482,7 @@ inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
     }
@@ -2486,12 +2490,12 @@ inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const st
         return complement ? 1 - landau_cdf_minus_imp_prec(x, tag) : landau_cdf_minus_imp_prec(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
     }
@@ -2499,18 +2503,18 @@ inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const st
         return complement ? 1 - landau_cdf_minus_imp_prec(x, tag) : landau_cdf_minus_imp_prec(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType landau_cdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp(const landau_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
     //
     // This calculates the cdf of the Landau distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::cdf(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(landau<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -2547,7 +2551,7 @@ inline RealType landau_cdf_imp(const landau_distribution<RealType, Policy>& dist
 }
 
 template <class RealType>
-inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2557,7 +2561,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 3.0596e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(3.74557416577759554506e-2),
             static_cast<RealType>(3.87808262376545756299e0),
             static_cast<RealType>(4.03092288183382979104e0),
@@ -2565,7 +2569,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-6.99689838230114367276e0),
             static_cast<RealType>(1.51123479911771488314e1),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.37863773851525662884e-1),
             static_cast<RealType>(-6.35020262707816744534e0),
@@ -2582,7 +2586,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 5.2780e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(-4.17764764050720190117e-1),
             static_cast<RealType>(1.27887601021900963655e0),
             static_cast<RealType>(1.80329928265996817279e1),
@@ -2591,7 +2595,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-2.36192101013335692266e1),
             static_cast<RealType>(8.30396110938939237358e0),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(5.37459525158081633669e0),
             static_cast<RealType>(2.35696607501498012129e0),
@@ -2607,7 +2611,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Absolute Error: 6.3254e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-8.77109518013577785811e-1),
             static_cast<RealType>(-1.03442936529923615496e1),
             static_cast<RealType>(-1.03389868296950570121e1),
@@ -2617,7 +2621,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-5.38213647878547918506e2),
             static_cast<RealType>(1.99214574934960143349e2),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.64177607733998839003e1),
             static_cast<RealType>(8.10042194014991761178e1),
@@ -2634,7 +2638,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 3.5192e-18
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(-8.77109518013577852585e-1),
             static_cast<RealType>(-1.08703720146608358678e0),
             static_cast<RealType>(-4.34198537684719253325e-1),
@@ -2642,7 +2646,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-4.20721933993302797971e-3),
             static_cast<RealType>(-6.27420063107527426396e-5),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(8.38688797993971740640e-1),
             static_cast<RealType>(2.47558526682310722526e-1),
@@ -2658,7 +2662,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.1196e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-1.16727296241754548410e0),
             static_cast<RealType>(-1.12325365855062172009e0),
             static_cast<RealType>(-3.96403456954867129566e-1),
@@ -2668,7 +2672,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-1.81536405273085024830e-6),
             static_cast<RealType>(-9.65262938333207656548e-10),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(7.55271574611337871389e-1),
             static_cast<RealType>(2.16323131117540100488e-1),
@@ -2685,7 +2689,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.0763e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-1.78348038398799868409e0),
             static_cast<RealType>(-7.74779087785346936524e-1),
             static_cast<RealType>(-1.27121601027522656374e-1),
@@ -2695,7 +2699,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-3.06397799506512676163e-8),
             static_cast<RealType>(-7.34821360521886161256e-12),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(3.76606062137668223823e-1),
             static_cast<RealType>(5.37821995022686641494e-2),
@@ -2712,7 +2716,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 9.9936e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-2.32474749499506229415e0),
             static_cast<RealType>(-4.81681429397597263092e-1),
             static_cast<RealType>(-3.79696253130015182335e-2),
@@ -2722,7 +2726,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-5.04229972664978604816e-10),
             static_cast<RealType>(-5.49506755992282162712e-14),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.87186049570056737301e-1),
             static_cast<RealType>(1.32852903862611979806e-2),
@@ -2739,7 +2743,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 9.2449e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-2.82318656228158372998e0),
             static_cast<RealType>(-2.84346379198027589453e-1),
             static_cast<RealType>(-1.09194719815749710073e-2),
@@ -2749,7 +2753,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-8.22634582905944543176e-12),
             static_cast<RealType>(-4.10585514777842307175e-16),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(9.29910333991046040738e-2),
             static_cast<RealType>(3.27860300729204691815e-3),
@@ -2766,7 +2770,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 8.6453e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-3.29700011190686231229e0),
             static_cast<RealType>(-1.62920309130909343601e-1),
             static_cast<RealType>(-3.07152472866757852259e-3),
@@ -2776,7 +2780,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-1.34109445298156050256e-13),
             static_cast<RealType>(-3.08843378675512185582e-18),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.62324092774919223927e-2),
             static_cast<RealType>(8.10410923007867515072e-4),
@@ -2793,7 +2797,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 8.2028e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-3.75666995985336008568e0),
             static_cast<RealType>(-9.15751436135409108392e-2),
             static_cast<RealType>(-8.51745858385908954959e-4),
@@ -2803,7 +2807,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-2.19023097542770265117e-15),
             static_cast<RealType>(-2.34270094396556916060e-20),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(2.30119177073875808729e-2),
             static_cast<RealType>(2.00787377759037971795e-4),
@@ -2820,7 +2824,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 7.8900e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-4.20826069989721597050e0),
             static_cast<RealType>(-5.07864788729928381957e-2),
             static_cast<RealType>(-2.33825872475869133650e-4),
@@ -2830,7 +2834,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-3.58448226638949307172e-17),
             static_cast<RealType>(-1.79092368272097571876e-22),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(1.14671758705641048135e-2),
             static_cast<RealType>(4.98614103841229871806e-5),
@@ -2847,7 +2851,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 7.6777e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-4.65527239540648658214e0),
             static_cast<RealType>(-2.78834161568280967534e-2),
             static_cast<RealType>(-6.37014695368461940922e-5),
@@ -2857,7 +2861,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(-5.87602374631705229119e-19),
             static_cast<RealType>(-1.37812578498484605190e-24),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(5.72000087046224585566e-3),
             static_cast<RealType>(1.24068329655043560901e-5),
@@ -2870,7 +2874,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else{
-        result = -std::numeric_limits<RealType>::infinity();
+        result = -boost::math::numeric_limits<RealType>::infinity();
     }
 
     return result;
@@ -2878,7 +2882,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
 
 
 template <class RealType>
-inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2889,7 +2893,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Absolute Error: 2.5723e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.74557416577759248536854968412794870581e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.04379368253541440583870397314012269006e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12622841210720956864564105821904588447e1),
@@ -2904,7 +2908,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.98534922151507267157370682137856253991e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.09159286510191893522643172277831735606e0),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.86204686129323171601167115178777357431e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.43698274248278918649234376575855135232e0),
@@ -2927,7 +2931,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Absolute Error: 6.1583e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.17764764050720242897742634974454113395e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.80044093802431965072543552425830082205e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23613318632011593171919848575560968064e1),
@@ -2942,7 +2946,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02847586753967876900858299686189155164e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.29953583375818707785500963989580066735e1),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27455303165341271216882778791555788609e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41762124591820618604790027888328605963e1),
@@ -2966,7 +2970,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Absolute Error: 1.3135e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160121458e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.05813204052660740589813216397258899528e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.19628607167020425528944673039894592264e2),
@@ -2983,7 +2987,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23815021378788622035604969476085727123e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.17262073948257994617723369387261569086e4),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.94901665980514882602824575757494472790e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54328910175180674300123471690771017388e2),
@@ -3009,7 +3013,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 2.0498e-35
         // LCOV_EXCL_START
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.77109518013577849065583862782160155093e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.77585398076895266354686007069850894777e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.47522378123968853907102309276280187353e0),
@@ -3022,7 +3026,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.34187895701093934279414993393750297714e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.64090928155753225614302094820737249510e-10),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62401464973350962823995096121206419019e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11979822811128264831341485706314465894e0),
@@ -3044,7 +3048,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.7643e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16727296241754547290632950718657117630e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97822895738734630842909028778257589627e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45580723831325060656664869189975355503e0),
@@ -3060,7 +3064,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.27785620133198676852587951604694784533e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.89999814745618370028655821500875451178e-16),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48772690114094395052120751771215809418e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.72281013057830222881716429522080327421e-1),
@@ -3085,7 +3089,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.4987e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78348038398799867332294266481364810762e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42913983922316889357725662957488617770e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.02077376277824482097703213549730657663e-1),
@@ -3101,7 +3105,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.65547426464916480144982028081303670013e-16),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.01788104318587272115031165074724363239e-19),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.43507070588695242714872431565299762416e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42808541175677232789532731946043918868e-1),
@@ -3126,7 +3130,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.4643e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.32474749499506228416012679106564727824e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.11125026189437033131539969177846635890e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.56906722402983201196890012041528422765e-1),
@@ -3142,7 +3146,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.39435252454410259267870094713230289131e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32672767938414655620839066142834241506e-23),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.71913035066927544877255131988977106466e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07499674325721771035402891723823952963e-2),
@@ -3167,7 +3171,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.2783e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.82318656228158372073367735499501003484e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.46261040951642110189344545942990712460e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.64741560190892266676648641695426188913e-2),
@@ -3183,7 +3187,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.14321784268659603072523892366718901165e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.69804409248161357472540739283978368871e-27),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85763741109198600677877934140774914793e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51555423561034635648725665049090572375e-2),
@@ -3208,7 +3212,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.0123e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.29700011190686230364493911161520668302e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.16175031776740080906111179721128106011e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33343982195432985864570319341790342784e-2),
@@ -3224,7 +3228,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.93656169061287808919601714139458074543e-27),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.14930159772574816086864316805656403181e-31),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27154900915819978649344191118112870943e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77527908332591966425460814882436207182e-3),
@@ -3249,7 +3253,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.7624e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.75666995985336007747791649448887723610e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.78960399079208663111712385988217075907e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.74942252057371678208959612011771010491e-3),
@@ -3265,7 +3269,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.50976593324256906782731237116487284834e-31),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.71308835356954147218854223581309967814e-35),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.62732785401286024270119905692156750540e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.40382961238668912455720345718267045656e-4),
@@ -3290,7 +3294,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.5621e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.20826069989721596260510558511263035942e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.97440158261228371765435988840257904642e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.03971528248920108158059927256206438162e-3),
@@ -3306,7 +3310,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.91906782399731224228792112460580813901e-34),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.42769091263044979075875010403899574987e-39),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31008507886426704374911618340654350029e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.34370110384866123378972324145883460422e-4),
@@ -3331,7 +3335,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.4128e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.65527239540648657446629479052874029563e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.49609214609793557370425343404734771058e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85355312961840000203681352424632999367e-4),
@@ -3347,7 +3351,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.90550919589933206991152832258558972394e-38),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.33785768143117121220383154455316199086e-43),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15365252334339030944695314405853064901e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.84519641047962864523571386561993045416e-5),
@@ -3372,7 +3376,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.3064e-35
         //LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.09971143249822249471944441552701756051e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.00154235169065403254826962372636417554e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.76859552294270710004718457715250134998e-5),
@@ -3388,7 +3392,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25433604872532935232490414753194993235e-41),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.49792182967344082832448065912949074241e-47),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.76316274347013095030195725596822418859e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45872499993438633169552184478587544165e-5),
@@ -3413,7 +3417,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.2337e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.54271778755494231572464179212263718102e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62737121212473668543011440432166267791e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.10099492629239750693134803100262740506e-5),
@@ -3429,7 +3433,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20746149769511232987820552765701234564e-45),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.97544543671003989410397788518265345930e-51),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87980995989632171985079518382705421728e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.64234691529227024725728122489224211774e-6),
@@ -3454,7 +3458,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.1864e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.98493298246627952401490656857159302716e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.76990949843357898517869703626917264559e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.65042794324685841303461715489845834903e-6),
@@ -3470,7 +3474,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.19893980415902021846066305054394089887e-49),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.85434486590981105149494168639321627061e-55),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43932168599456260558411716919165161381e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.09851997458503734167541584552305867433e-7),
@@ -3495,7 +3499,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.1568e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.42671464308364892089984144203590292562e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.70165333325375920690660683988390032004e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.51230594210711745541592189387307516997e-6),
@@ -3511,7 +3515,7 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.09423327107440352766843873264503717048e-52),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12386630925835960782702757402676887380e-58),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.19477412398085422408065302795208098500e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27347517804649548179786994390985841531e-7),
@@ -3531,14 +3535,14 @@ inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::int
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
-        result = -std::numeric_limits<RealType>::infinity();
+        result = -boost::math::numeric_limits<RealType>::infinity();
     }
 
     return result;
 }
 
 template <class RealType>
-inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3548,7 +3552,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.1286e-20
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.31348919222343858178e0),
             static_cast<RealType>(-1.06646675961352786791e0),
             static_cast<RealType>(-1.80946160022120488884e1),
@@ -3557,7 +3561,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(4.61048467818771410732e0),
             static_cast<RealType>(-2.80957284947853532418e1),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.71007453129016317772e0),
             static_cast<RealType>(1.31946404969596908872e0),
@@ -3575,7 +3579,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 3.4934e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.55081568282045924981e0),
             static_cast<RealType>(5.38750533719526696218e0),
             static_cast<RealType>(-2.32797421725187349036e1),
@@ -3584,7 +3588,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(3.35014421131920266346e1),
             static_cast<RealType>(-1.17490458743273503838e1),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(7.52439409918350484765e0),
             static_cast<RealType>(1.34784954182866689668e1),
@@ -3601,7 +3605,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 4.0795e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(5.68160868054034111703e0),
             static_cast<RealType>(1.06098927525586705381e2),
             static_cast<RealType>(5.74509518025029027944e2),
@@ -3611,7 +3615,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(2.49195208452006100935e3),
             static_cast<RealType>(1.29413301335116683836e3),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1),
             static_cast<RealType>(2.69603865809599480308e1),
             static_cast<RealType>(2.63378422475372461819e2),
@@ -3628,7 +3632,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 4.4618e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(7.10201085067542566037e-1),
             static_cast<RealType>(6.70042401812679849451e-1),
             static_cast<RealType>(2.42799404088685074098e-1),
@@ -3637,7 +3641,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(5.09172911021654842046e-4),
             static_cast<RealType>(-6.63145317984529265677e-6),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1),
             static_cast<RealType>(9.18649629646213969612e-1),
             static_cast<RealType>(3.66343989541898286306e-1),
@@ -3653,7 +3657,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 5.8994e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(7.06147398566773538296e-1),
             static_cast<RealType>(4.26802162741800814387e-1),
             static_cast<RealType>(1.32254436707168800420e-1),
@@ -3664,7 +3668,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(8.76982374043363061978e-7),
             static_cast<RealType>(-1.99744396595921347207e-8),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(6.28190787856605587324e-1),
             static_cast<RealType>(2.10992746593815791546e-1),
@@ -3683,7 +3687,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 8.8685e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.48209596014908359251e-1),
             static_cast<RealType>(2.52611824671691390768e-1),
             static_cast<RealType>(4.65114070477803399291e-2),
@@ -3694,7 +3698,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(6.92614450423703079737e-9),
             static_cast<RealType>(-3.89531123166658723619e-10),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(3.99413988076189200840e-1),
             static_cast<RealType>(7.32068638518417765776e-2),
@@ -3713,7 +3717,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 1.0253e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(6.36719010559816164896e-1),
             static_cast<RealType>(2.06504115804034148753e-1),
             static_cast<RealType>(3.28085429275407182582e-2),
@@ -3725,7 +3729,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(1.77492646969597480221e-10),
             static_cast<RealType>(-2.19331267300885448673e-17),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(3.24422807416528490276e-1),
             static_cast<RealType>(5.15290129833049138552e-2),
@@ -3744,7 +3748,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
         // Rational Approximation
         // Maximum Relative Error: 8.1705e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(6.36619775525705206992e-1),
             static_cast<RealType>(2.68335698140634792041e-1),
             static_cast<RealType>(5.49803347535070103650e-2),
@@ -3755,7 +3759,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             static_cast<RealType>(9.56133960810049319917e-8),
             static_cast<RealType>(5.26850116571886385248e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1),
             static_cast<RealType>(4.21500730173440590900e-1),
             static_cast<RealType>(8.63629077498258325752e-2),
@@ -3778,7 +3782,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 
 
 template <class RealType>
-inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3789,7 +3793,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 1.4465e-35
         // LCOV_EXCL_START
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.08338732735341567163440035550389989556e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27245731792290848390848202647311435023e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29317169036386848462079766136373749420e1),
@@ -3802,7 +3806,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.42232005306623465126477816911649683789e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.24816048952817367950452675590290535540e0),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.80464069267458650284548842830642770344e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.28240205449280944407125436342013240876e0),
@@ -3823,7 +3827,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 5.1929e-35
         // LCOV_EXCL_START
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31348919222343858173602105619413801018e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02800226274700443079521563669609776285e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.02091675505570786434803291987263553778e1),
@@ -3836,7 +3840,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.26390836417639942474165178280649450755e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.18212484486162942333407102351878915285e0),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.97802777458574322604171035748634755981e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.33277809211107726455308655998819166901e0),
@@ -3857,7 +3861,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 3.2765e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55081568282045925871949387822806890848e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21080883686702131458668798583937913025e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15083151599213113740932148510289036342e1),
@@ -3872,7 +3876,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.32825234826729794599233825734928884074e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.47352171888649528242284500266830013906e1),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40793887011403443604922082103267036101e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.04348824299115035210088417095305744248e1),
@@ -3896,7 +3900,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 1.8007e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68160868054034088524891526884683014057e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85165791469635551063850795991424359350e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42938802867742165917839659578485422534e3),
@@ -3912,7 +3916,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25168985723506298009849577846542992545e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01179759985059408785527092464505889999e5),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08766677593618443545489115711858395831e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.05163374816838964338807027995515659842e2),
@@ -3938,7 +3942,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 6.1905e-36
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.10201085067542610656114408605853786551e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04725580445598482170291458376577106746e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35945839005443673797792325217359695272e-1),
@@ -3953,7 +3957,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11932910013840927659486142481532276176e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64064398716881126082770692219937093427e-10),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24909572944428286558287313527068259394e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.70912720447370835699164559729287157119e-1),
@@ -3977,7 +3981,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 8.5157e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.06147398566773479301585022897491054494e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06137881154706023038556659418303323027e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.00274868819366386235164897614448662308e-1),
@@ -3997,7 +4001,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.57808410784300002747916947756919004207e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.93860773322862111592582321183379587624e-16),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52683694883265337797012770275040297516e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17837082293165509684677505408307814500e0),
@@ -4026,7 +4030,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 7.6812e-36
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48209596014908270566135466727658374314e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02026332003132864886056710532156370366e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68941634461905013212266453851941196774e-1),
@@ -4046,7 +4050,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32583227076029470589713734885690555562e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18237323554153660947807202150429686004e-20),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.38459552164692902984228821988876295376e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21584899508575302641780901222203752951e-1),
@@ -4075,7 +4079,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 2.8388e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36719010559816175149447242695581604280e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14714772485724956396126176973339095223e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47792450677638612907408723539943311437e-2),
@@ -4095,7 +4099,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.87812199530402923085142356622707924805e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76810877067601573471489978907720495511e-24),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.94373217074550329856398644558576545146e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17462725343185049507839058445338783693e-1),
@@ -4124,7 +4128,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 1.8746e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619775525705288697351261475419832625e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.29882145587771350744255724773409752285e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07952726597277085327360888304737411175e-2),
@@ -4145,7 +4149,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.53604301472332155307661986064796109517e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65664588229982894587678197374867153136e-40),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61098031370834273919229478584740981117e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.40810642301361416278392589243623940154e-2),
@@ -4174,7 +4178,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
         // Rational Approximation
         // Maximum Relative Error: 3.9915e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581344576326594951209529606e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72456363182667891167613558295097711432e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74486567435450138741058930951301644059e-2),
@@ -4194,7 +4198,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07803703545135964499326712080667886449e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61500479431085205124031101160332446432e-23),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27973454499231032893774072677004977154e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.02401389920613749641292661572240166038e-2),
@@ -4225,7 +4229,7 @@ inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::int
 }
 
 template <class RealType>
-inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
         return landau_quantile_imp_prec(1 - p, !complement, tag);
@@ -4235,7 +4239,7 @@ inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, con
 }
 
 template <class RealType>
-inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
         return landau_quantile_imp_prec(1 - p, !complement, tag);
@@ -4245,12 +4249,12 @@ inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, con
 }
 
 template <class RealType, class Policy>
-inline RealType landau_quantile_imp(const landau_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp(const landau_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
 {
     // This routine implements the quantile for the Landau distribution,
     // the value p may be the probability, or its complement if complement=true.
 
-    static const char* function = "boost::math::quantile(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(landau<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -4287,23 +4291,23 @@ inline RealType landau_quantile_imp(const landau_distribution<RealType, Policy>&
 }
 
 template <class RealType>
-inline RealType landau_mode_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-0.42931452986133525017);
 }
 
 template <class RealType>
-inline RealType landau_mode_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.42931452986133525016556463510885028346);
 }
 
 template <class RealType, class Policy>
-inline RealType landau_mode_imp(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp(const landau_distribution<RealType, Policy>& dist)
 {
     // This implements the mode for the Landau distribution,
 
-    static const char* function = "boost::math::mode(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::mode(landau<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -4336,23 +4340,23 @@ inline RealType landau_mode_imp(const landau_distribution<RealType, Policy>& dis
 }
 
 template <class RealType>
-inline RealType landau_median_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(0.57563014394507821440);
 }
 
 template <class RealType>
-inline RealType landau_median_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 0.57563014394507821439627930892257517269);
 }
 
 template <class RealType, class Policy>
-inline RealType landau_median_imp(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp(const landau_distribution<RealType, Policy>& dist)
 {
     // This implements the median for the Landau distribution,
 
-    static const char* function = "boost::math::median(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::median(landau<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -4385,23 +4389,23 @@ inline RealType landau_median_imp(const landau_distribution<RealType, Policy>& d
 }
 
 template <class RealType>
-inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.37263644000448182448);
 }
 
 template <class RealType>
-inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.3726364400044818244844049010588577710);
 }
 
 template <class RealType, class Policy>
-inline RealType landau_entropy_imp(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp(const landau_distribution<RealType, Policy>& dist)
 {
     // This implements the entropy for the Landau distribution,
 
-    static const char* function = "boost::math::entropy(landau<%1%>&, %1%)";
+    constexpr auto function = "boost::math::entropy(landau<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -4436,10 +4440,10 @@ class landau_distribution
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    landau_distribution(RealType l_location = 0, RealType l_scale = 1)
+    BOOST_MATH_GPU_ENABLED landau_distribution(RealType l_location = 0, RealType l_scale = 1)
         : mu(l_location), c(l_scale)
     {
-        static const char* function = "boost::math::landau_distribution<%1%>::landau_distribution";
+        constexpr auto function = "boost::math::landau_distribution<%1%>::landau_distribution";
         RealType result = 0;
         detail::check_location(function, l_location, &result, Policy());
         detail::check_scale(function, l_scale, &result, Policy());
@@ -4448,15 +4452,15 @@ class landau_distribution
         location_bias = -2 / constants::pi<RealType>() * log(l_scale);
     } // landau_distribution
 
-    RealType location()const
+    BOOST_MATH_GPU_ENABLED RealType location()const
     {
         return mu;
     }
-    RealType scale()const
+    BOOST_MATH_GPU_ENABLED RealType scale()const
     {
         return c;
     }
-    RealType bias()const
+    BOOST_MATH_GPU_ENABLED RealType bias()const
     {
         return location_bias;
     }
@@ -4477,66 +4481,66 @@ landau_distribution(RealType, RealType) -> landau_distribution<typename boost::m
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const landau_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const landau_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const landau_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const landau_distribution<RealType, Policy>&)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::landau_pdf_imp(dist, x);
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const landau_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::landau_cdf_imp(dist, x, false);
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const landau_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const landau_distribution<RealType, Policy>& dist, const RealType& p)
 {
     return detail::landau_quantile_imp(dist, p, false);
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::landau_cdf_imp(c.dist, c.param, true);
 } //  cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<landau_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::landau_quantile_imp(c.dist, c.param, true);
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const landau_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const landau_distribution<RealType, Policy>&)
 {  // There is no mean:
     typedef typename Policy::assert_undefined_type assert_type;
     static_assert(assert_type::value == 0, "The Landau Distribution has no mean");
@@ -4545,11 +4549,11 @@ inline RealType mean(const landau_distribution<RealType, Policy>&)
         "boost::math::mean(landau<%1%>&)",
         "The Landau distribution does not have a mean: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const landau_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const landau_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no variance:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4559,23 +4563,23 @@ inline RealType variance(const landau_distribution<RealType, Policy>& /*dist*/)
         "boost::math::variance(landau<%1%>&)",
         "The Landau distribution does not have a variance: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const landau_distribution<RealType, Policy>& dist)
 {
     return detail::landau_mode_imp(dist);
 }
 
 template <class RealType, class Policy>
-inline RealType median(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const landau_distribution<RealType, Policy>& dist)
 {
     return detail::landau_median_imp(dist);
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const landau_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const landau_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4585,11 +4589,11 @@ inline RealType skewness(const landau_distribution<RealType, Policy>& /*dist*/)
         "boost::math::skewness(landau<%1%>&)",
         "The Landau distribution does not have a skewness: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const landau_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const landau_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4599,11 +4603,11 @@ inline RealType kurtosis(const landau_distribution<RealType, Policy>& /*dist*/)
         "boost::math::kurtosis(landau<%1%>&)",
         "The Landau distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const landau_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const landau_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4613,11 +4617,11 @@ inline RealType kurtosis_excess(const landau_distribution<RealType, Policy>& /*d
         "boost::math::kurtosis_excess(landau<%1%>&)",
         "The Landau distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const landau_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const landau_distribution<RealType, Policy>& dist)
 {
     return detail::landau_entropy_imp(dist);
 }

From 3cf9562c1b95681b8c76a23cd9e1566e8568e94f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 10:31:05 -0400
Subject: [PATCH 154/399] Add landau dist CUDA tests

---
 test/cuda_jamfile               |   6 ++
 test/test_landau_cdf_double.cu  | 110 ++++++++++++++++++++++++++++++++
 test/test_landau_cdf_float.cu   | 110 ++++++++++++++++++++++++++++++++
 test/test_landau_pdf_double.cu  | 110 ++++++++++++++++++++++++++++++++
 test/test_landau_pdf_float.cu   | 110 ++++++++++++++++++++++++++++++++
 test/test_landau_quan_double.cu | 110 ++++++++++++++++++++++++++++++++
 test/test_landau_quan_float.cu  | 110 ++++++++++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_landau_cdf_double.cu
 create mode 100644 test/test_landau_cdf_float.cu
 create mode 100644 test/test_landau_pdf_double.cu
 create mode 100644 test/test_landau_pdf_float.cu
 create mode 100644 test/test_landau_quan_double.cu
 create mode 100644 test/test_landau_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 7ce67a94de..3a109e0955 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -46,6 +46,12 @@ run test_exponential_quan_double.cu ;
 run test_exponential_quan_float.cu ;
 run test_exponential_range_support_double.cu ;
 run test_exponential_range_support_float.cu ;
+run test_landau_cdf_double.cu ;
+run test_landau_cdf_float.cu ;
+run test_landau_pdf_double.cu ;
+run test_landau_pdf_float.cu ;
+run test_landau_quan_double.cu;
+run test_landau_quan_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_landau_cdf_double.cu b/test/test_landau_cdf_double.cu
new file mode 100644
index 0000000000..092fff00ed
--- /dev/null
+++ b/test/test_landau_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_landau_cdf_float.cu b/test/test_landau_cdf_float.cu
new file mode 100644
index 0000000000..143755aff9
--- /dev/null
+++ b/test/test_landau_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_landau_pdf_double.cu b/test/test_landau_pdf_double.cu
new file mode 100644
index 0000000000..eea6f87add
--- /dev/null
+++ b/test/test_landau_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_landau_pdf_float.cu b/test/test_landau_pdf_float.cu
new file mode 100644
index 0000000000..a424bdd678
--- /dev/null
+++ b/test/test_landau_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_landau_quan_double.cu b/test/test_landau_quan_double.cu
new file mode 100644
index 0000000000..8cdf12588d
--- /dev/null
+++ b/test/test_landau_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_landau_quan_float.cu b/test/test_landau_quan_float.cu
new file mode 100644
index 0000000000..8cdf12588d
--- /dev/null
+++ b/test/test_landau_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::landau_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 4c5a3849f77411616e0d250af4b9ddc8c27be120 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 10:37:29 -0400
Subject: [PATCH 155/399] Remove recursion from quantile dispatch function

---
 include/boost/math/distributions/landau.hpp | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/include/boost/math/distributions/landau.hpp b/include/boost/math/distributions/landau.hpp
index 1ffa503459..424931c276 100644
--- a/include/boost/math/distributions/landau.hpp
+++ b/include/boost/math/distributions/landau.hpp
@@ -4231,8 +4231,9 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const Real
 template <class RealType>
 BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
-    if (p > 0.5) {
-        return landau_quantile_imp_prec(1 - p, !complement, tag);
+    if (p > 0.5) 
+    {
+        return !complement ? landau_quantile_upper_imp_prec(1 - p, tag) : landau_quantile_lower_imp_prec(1 - p, tag);
     }
 
     return complement ? landau_quantile_upper_imp_prec(p, tag) : landau_quantile_lower_imp_prec(p, tag);
@@ -4241,8 +4242,9 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType&
 template <class RealType>
 BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
-    if (p > 0.5) {
-        return landau_quantile_imp_prec(1 - p, !complement, tag);
+    if (p > 0.5) 
+    {
+        return !complement ? landau_quantile_upper_imp_prec(1 - p, tag) : landau_quantile_lower_imp_prec(1 - p, tag);
     }
 
     return complement ? landau_quantile_upper_imp_prec(p, tag) : landau_quantile_lower_imp_prec(p, tag);

From d428b9dcc1a439be2ccee67c5656a2502938ae7a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 10:37:39 -0400
Subject: [PATCH 156/399] Add SYCL test for Landau distribution

---
 test/sycl_jamfile    |  1 +
 test/test_landau.cpp | 26 ++++++++++++++++++++++----
 2 files changed, 23 insertions(+), 4 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index f02065a390..ae4742c47d 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -14,6 +14,7 @@ run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
 run test_exponential_dist.cpp ;
+run test_landau.cpp ;
 
 # Special Functions
 run pow_test.cpp ;
diff --git a/test/test_landau.cpp b/test/test_landau.cpp
index 08d18ec8e6..297589bc09 100644
--- a/test/test_landau.cpp
+++ b/test/test_landau.cpp
@@ -1,14 +1,14 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
 #define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsLandauTest
+#include <boost/math/tools/config.hpp>
 #include <boost/test/included/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
-#include <boost/multiprecision/cpp_bin_float.hpp>
-
 #include <boost/math/distributions/landau.hpp>
 
 #if __has_include(<stdfloat>)
@@ -16,7 +16,11 @@
 #endif
 
 using boost::math::landau_distribution;
-using boost::multiprecision::cpp_bin_float_quad;
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#  include <boost/multiprecision/cpp_bin_float.hpp>
+   using boost::multiprecision::cpp_bin_float_quad;
+#endif
 
 template<class RealType, int N>
 void do_test_landau_pdf(){
@@ -738,10 +742,12 @@ BOOST_AUTO_TEST_CASE(landau_pdf_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_pdf_fp128)
 {
     do_test_landau_pdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_cdf_fp64)
 {
@@ -755,10 +761,12 @@ BOOST_AUTO_TEST_CASE(landau_cdf_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_cdf_fp128)
 {
     do_test_landau_cdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_ccdf_fp64)
 {
@@ -772,10 +780,12 @@ BOOST_AUTO_TEST_CASE(landau_ccdf_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_ccdf_fp128)
 {
     do_test_landau_ccdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp64)
 {
@@ -789,10 +799,12 @@ BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_quantile_nearzero_fp128)
 {
     do_test_landau_quantile_nearzero<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp64)
 {
@@ -806,10 +818,12 @@ BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_quantile_lower_fp128)
 {
     do_test_landau_quantile_lower<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp64)
 {
@@ -823,10 +837,12 @@ BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_quantile_upper_fp128)
 {
     do_test_landau_quantile_upper<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(landau_locscale_fp64)
 {
@@ -840,8 +856,10 @@ BOOST_AUTO_TEST_CASE(landau_locscale_fp64_std)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(landau_locscale_fp128)
 {
     do_test_landau_locscale_param<cpp_bin_float_quad, 113>();
 }
+#endif
 

From fcb8e205dc0fa014553b5759ee6cb917526a3973 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:12:13 -0400
Subject: [PATCH 157/399] Add GPU support to mapairy dist

---
 include/boost/math/distributions/mapairy.hpp | 560 ++++++++++---------
 1 file changed, 282 insertions(+), 278 deletions(-)

diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index f5f88486ef..542cf6da38 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -1,4 +1,5 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,6 +12,9 @@
 #pragma warning(disable : 4127) // conditional expression is constant
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -29,7 +33,7 @@ class mapairy_distribution;
 namespace detail {
 
 template <class RealType>
-inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -37,7 +41,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 3.7591e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.97516171847191855610e-1),
             static_cast<RealType>(3.67488253628465083737e-2),
             static_cast<RealType>(-9.73242224038828612673e-4),
@@ -47,7 +51,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(1.04960324426666933327e-5),
             static_cast<RealType>(-6.58470237954242016920e-7),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.09464351647314165710e-1),
             static_cast<RealType>(3.66413036246461392316e-1),
@@ -64,7 +68,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.5996e-20
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.06251243013238748252e-1),
             static_cast<RealType>(1.38178831205785069108e-2),
             static_cast<RealType>(4.19280374368049006206e-3),
@@ -74,7 +78,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.30090180307471994500e-6),
             static_cast<RealType>(5.24801123304330014713e-8),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.10853683888611687140e-1),
             static_cast<RealType>(3.89361261627717143905e-1),
@@ -92,7 +96,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.1592e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(5.33842514891989443409e-2),
             static_cast<RealType>(1.23301980674903270971e-2),
             static_cast<RealType>(3.45717831433988631923e-3),
@@ -103,7 +107,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(9.15896323073109992939e-9),
             static_cast<RealType>(-3.14068002815368247985e-10),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.08772985520393226044e-1),
             static_cast<RealType>(4.26418573702560818267e-1),
@@ -120,7 +124,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 9.2228e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.58950538583133457384e-2),
             static_cast<RealType>(7.47835440063141601948e-3),
             static_cast<RealType>(1.81137244353261478410e-3),
@@ -130,7 +134,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.54976465724771282989e-9),
             static_cast<RealType>(1.30762989300333026019e-11),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.95505437381674174441e-1),
             static_cast<RealType>(4.58882737262511297099e-1),
@@ -148,7 +152,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.0257e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.22517551525042172428e-3),
             static_cast<RealType>(1.12822806030796339659e-3),
             static_cast<RealType>(1.54489389961322571031e-4),
@@ -158,7 +162,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-2.15498112371756202097e-12),
             static_cast<RealType>(6.41838355699777435924e-15),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.53390465399680164234e-1),
             static_cast<RealType>(1.82759048270449018482e-1),
@@ -176,7 +180,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 6.0510e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(5.82527663232857270992e-4),
             static_cast<RealType>(6.89502117025124630567e-5),
             static_cast<RealType>(2.24909795087265741433e-6),
@@ -186,7 +190,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.13308546492906818388e-16),
             static_cast<RealType>(5.32472028720777735712e-19),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.74018883667663396766e-1),
             static_cast<RealType>(2.95901195665990089660e-2),
@@ -203,7 +207,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 7.3294e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.03264853379349880039e-4),
             static_cast<RealType>(5.35256306644392405447e-6),
             static_cast<RealType>(9.00657716972118816692e-8),
@@ -213,7 +217,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(7.28133811621687143754e-19),
             static_cast<RealType>(-7.38047553655951666420e-22),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.29920843258164337377e-1),
             static_cast<RealType>(6.75018577147646502386e-3),
@@ -230,14 +234,14 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 5.6693e-20
-        static const RealType P[5] = {
+        BOOST_MATH_STATIC const RealType P[5] = {
             static_cast<RealType>(5.98413420602149016910e-1),
             static_cast<RealType>(3.14584075817417883086e-5),
             static_cast<RealType>(1.62977928311793051895e1),
             static_cast<RealType>(-4.12903117172994371875e-4),
             static_cast<RealType>(-1.06404478702135751872e2),
         };
-        static const RealType Q[3] = {
+        BOOST_MATH_STATIC const RealType Q[3] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.25696892802060720079e-5),
             static_cast<RealType>(4.03600055498020483920e1),
@@ -251,7 +255,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 
 
 template <class RealType>
-inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -260,7 +264,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 7.8308e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97516171847191855609649452292217911973e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17531822787252717270400174744562144891e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.85115358761409188259685286269086053296e-2),
@@ -275,7 +279,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43150486566834492207695241913522311930e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46130347604880355784938321408765318948e-13),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11845869711743584628289654085905424438e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.80391154854347711297249357734993136108e-1),
@@ -299,7 +303,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 3.0723e-35
         // LCOV_EXCL_START
-        static const RealType P[12] = {
+        BOOST_MATH_STATIC const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06251243013238748252181151646220197947e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.92438638323563234519452281479338921158e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83335793178622701784730867677919844599e-2),
@@ -313,7 +317,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.81756745849477762773082030302943341729e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.65915115243311285178083515017249358853e-12),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33250387018216706082200927591739589024e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.71707718560216685629188467984384070512e-1),
@@ -337,7 +341,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 4.0903e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.33842514891989443409465171800884519331e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.53264053296761245408991932692426094424e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23210520807186629205810670362048049836e-2),
@@ -352,7 +356,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10030596535721362628619523622308581344e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19376016170255697546854583591494809062e-13),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52686177278870816414637961315363468426e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19872083945442288336636376283295310445e0),
@@ -378,7 +382,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 6.5015e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58950538583133457383574346194006716984e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.25447644411503971725638816502617490834e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47605882774114100209665040117276675598e-2),
@@ -395,7 +399,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.35248179978735448062307216459232932068e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53569375838863862590910010617140120876e-18),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94337325681904859647161946168957959628e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77120402023938328899162557073347121463e0),
@@ -423,7 +427,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 2.0995e-35
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.22517551525042172427941302520759668293e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.86576974828476461442549217748945498966e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18419822818191546598384139622512477000e-3),
@@ -441,7 +445,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68829978902134103249656805130103045021e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42496376687241918803028631991083570963e-26),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19213376162053391168605415200906099633e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65578261958732385181558047087365997878e-1),
@@ -468,7 +472,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 2.0937e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.82527663232857270992129793621400616909e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41696401156754081476312871174198295322e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.42036620449365724707919875710197564857e-5),
@@ -485,7 +489,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.81390322233700529779563477285232205886e-28),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52190981930441828041102818178755246228e-31),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.70564782441895707961338319466546005093e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47770566490107388849474183308889339231e-1),
@@ -511,7 +515,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 1.5856e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03264853379349880038687006045193401399e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.79539964604630527636184900467871907171e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34840369549460790638336121351837912308e-6),
@@ -528,7 +532,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.69069082510020066864633718082941688708e-34),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.33468198065176301137949068264633336529e-37),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51951069241510130465691156908893803280e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84647597299970149588010858770320631739e-2),
@@ -553,7 +557,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 3.5081e-36
         // LCOV_EXCL_START
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98413420602149016909919089901572802714e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.30303835860684077803651094768293625633e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.89097726237252419724261295392691855545e1),
@@ -563,7 +567,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.16343347002845084264982358165052437094e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.59558963351172885545760841064831356701e3),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.51965956124978480521462518750569617550e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61700833299761977287211297600922591853e2),
@@ -580,7 +584,7 @@ inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -590,7 +594,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 3.7525e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.76859868856746781256e-1),
             static_cast<RealType>(1.10489814676299003241e-1),
             static_cast<RealType>(-6.25690643488236678667e-3),
@@ -600,7 +604,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(-2.22575633858411851032e-5),
             static_cast<RealType>(2.94270091008508492304e-6),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.98673671503410894284e-1),
             static_cast<RealType>(3.15907666864554716291e-1),
@@ -617,7 +621,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 4.0995e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.14483832832989822788e-1),
             static_cast<RealType>(3.72789690317712876663e-1),
             static_cast<RealType>(1.86473650057086284496e-1),
@@ -627,7 +631,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(4.88651392754189961173e-4),
             static_cast<RealType>(-6.13516242712196835055e-5),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.06478618107122200489e0),
             static_cast<RealType>(4.08809060854459518663e-1),
@@ -648,7 +652,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 2.4768e-18
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(2.74308494787955998605e-1),
                 static_cast<RealType>(4.87765991440983416392e-1),
                 static_cast<RealType>(3.84524365110270427617e-1),
@@ -658,7 +662,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.20417225696161842090e-3),
                 static_cast<RealType>(6.97462693097107007719e-5),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.81256903248465876424e0),
                 static_cast<RealType>(1.43959302060852067876e0),
@@ -676,7 +680,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 1.5741e-17
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(2.67391547707456587286e-1),
                 static_cast<RealType>(3.39319035621314371924e-1),
                 static_cast<RealType>(1.85434799940724207230e-1),
@@ -686,7 +690,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(4.60769537123286016400e-5),
                 static_cast<RealType>(-4.92754650783224582641e-13),
             };
-            static const RealType Q[7] = {
+            BOOST_MATH_STATIC const RealType Q[7] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.27271216837333318516e0),
                 static_cast<RealType>(6.96551952883867277759e-1),
@@ -703,7 +707,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 4.6579e-17
-            static const RealType P[6] = {
+            BOOST_MATH_STATIC const RealType P[6] = {
                 static_cast<RealType>(2.66153901932100301337e-1),
                 static_cast<RealType>(1.65767350677458230714e-1),
                 static_cast<RealType>(4.19801402197670061146e-2),
@@ -711,7 +715,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(3.50811247702301287586e-4),
                 static_cast<RealType>(9.21758454778883157515e-6),
             };
-            static const RealType Q[6] = {
+            BOOST_MATH_STATIC const RealType Q[6] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(6.23092941554668369107e-1),
                 static_cast<RealType>(1.57829914506366827914e-1),
@@ -727,14 +731,14 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 5.2014e-17
-            static const RealType P[5] = {
+            BOOST_MATH_STATIC const RealType P[5] = {
                 static_cast<RealType>(2.65985830928929730672e-1),
                 static_cast<RealType>(7.19655029633308583205e-2),
                 static_cast<RealType>(7.26293125679558421946e-3),
                 static_cast<RealType>(3.24276402295343802262e-4),
                 static_cast<RealType>(5.40508013573989841127e-6),
             };
-            static const RealType Q[5] = {
+            BOOST_MATH_STATIC const RealType Q[5] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(2.70578525590448009961e-1),
                 static_cast<RealType>(2.73082032706004833847e-2),
@@ -753,7 +757,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 }
 
 template <class RealType>
-inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -764,7 +768,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
         // Rational Approximation
         // Maximum Relative Error: 5.2870e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.76859868856746781256050397658493368372e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13037642242224438972685982606987140111e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.93206268361082760254653961897373271146e-2),
@@ -780,7 +784,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77632857558257155545506847333166147492e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00448215148716947837105979735199471601e-11),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.69069814466926608209872727645156315374e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.89657828158127300370734997707096744077e-1),
@@ -804,7 +808,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
         // Rational Approximation
         // Maximum Relative Error: 1.1977e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.14483832832989822788477500521594411868e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75657192307644021285091474845448102656e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.40437358470633234235031852091608646844e-1),
@@ -819,7 +823,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11130363073235247786909976446790746902e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.49023728251751416730708805268921994420e-10),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.11919889346080886194925406930280687022e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.99082771425048574611745923487528183522e-1),
@@ -848,7 +852,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 5.4547e-35
             // LCOV_EXCL_START
-            static const RealType P[15] = {
+            BOOST_MATH_STATIC const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.74308494787955998605105974174143750745e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.56767876568276519015214709629156760546e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23402577465454790961498400214198520261e0),
@@ -865,7 +869,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.88118741063309731598638313174835288433e-8),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.78908322579081615215057968216358892954e-9),
             };
-            static const RealType Q[15] = {
+            BOOST_MATH_STATIC const RealType Q[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15777668058369565739250784347385217839e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.58275582332060589146223977924181161908e0),
@@ -891,7 +895,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 1.8813e-35
             // LCOV_EXCL_START
-            static const RealType P[15] = {
+            BOOST_MATH_STATIC const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.67391547707456587286086623414017962238e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.69944730920904699720804320295067934914e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.80384452804523880914883464295008532437e-1),
@@ -908,7 +912,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17645475312219452046348851569796494059e-9),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06306499345515479193219487228315566344e-11),
             };
-            static const RealType Q[15] = {
+            BOOST_MATH_STATIC const RealType Q[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13521398369589479131299586715604029947e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17680254721938920978999949995837883884e0),
@@ -934,7 +938,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 3.7501e-35
             // LCOV_EXCL_START
-            static const RealType P[13] = {
+            BOOST_MATH_STATIC const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66153901932100301337118653561328446399e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52542079386371212946566450189144670788e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17560936304516198261138159102435548430e-1),
@@ -949,7 +953,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19214263302271253341410568192952269518e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.36635313919771528255819112450043338510e-12),
             };
-            static const RealType Q[13] = {
+            BOOST_MATH_STATIC const RealType Q[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32484755553196872705775494679365596205e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17714315014480774542066462899317631393e-1),
@@ -973,7 +977,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 9.2696e-36
             // LCOV_EXCL_START
-            static const RealType P[12] = {
+            BOOST_MATH_STATIC const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65985830928929730672052407058361701971e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.80409998734303497641108024806388734755e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.49286120625421787109350223436127409819e-2),
@@ -987,7 +991,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.13183856815615371136129883169639301710e-13),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.02405342795439598418033139109649640085e-35),
             };
-            static const RealType Q[11] = {
+            BOOST_MATH_STATIC const RealType Q[11] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.78286317363568496229516074305435186276e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06519013547074134846431611115576250187e-1),
@@ -1009,7 +1013,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 2.3524e-35
             // LCOV_EXCL_START
-            static const RealType P[10] = {
+            BOOST_MATH_STATIC const RealType P[10] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65964563346442080104568381680822923977e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.77958685324702990033291591478515962894e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.56419338083136866686699803771820491401e-3),
@@ -1021,7 +1025,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.85553643603397817535280932672322232325e-13),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.46207029637607033398822620480584537642e-38),
             };
-            static const RealType Q[9] = {
+            BOOST_MATH_STATIC const RealType Q[9] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54906717312241693103173902792310528801e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.84408124581401290943345932332007045483e-2),
@@ -1044,7 +1048,7 @@ inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integra
 }
 
 template <class RealType>
-inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
     if (x >= 0) {
         return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1052,12 +1056,12 @@ inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_cons
         return mapairy_pdf_minus_imp_prec<RealType>(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1065,18 +1069,18 @@ inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_cons
         return mapairy_pdf_minus_imp_prec<RealType>(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x) {
     //
     // This calculates the pdf of the Map-Airy distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::pdf(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::pdf(mapairy<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -1112,7 +1116,7 @@ inline RealType mapairy_pdf_imp(const mapairy_distribution<RealType, Policy>& di
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1120,7 +1124,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 2.9194e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(3.33333333333333333333e-1),
             static_cast<RealType>(7.49532137610545010591e-2),
             static_cast<RealType>(9.25326921848155048716e-3),
@@ -1129,7 +1133,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(8.22766804917461941348e-5),
             static_cast<RealType>(-3.97941251650023182117e-6),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.17408156824742736411e-1),
             static_cast<RealType>(3.57041011418415988268e-1),
@@ -1146,7 +1150,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 3.1531e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.84196970581015939888e-1),
             static_cast<RealType>(-1.19398028299089933853e-3),
             static_cast<RealType>(1.21954054797949597854e-2),
@@ -1155,7 +1159,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-1.33271812303025233648e-5),
             static_cast<RealType>(5.35982226125013888796e-7),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.70352826101668448273e-1),
             static_cast<RealType>(1.98852010141232271304e-1),
@@ -1171,7 +1175,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 1.8348e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.07409273397524124098e-1),
             static_cast<RealType>(3.83900318969331880402e-2),
             static_cast<RealType>(1.17926652359826576790e-2),
@@ -1181,7 +1185,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(1.97360985832285866640e-8),
             static_cast<RealType>(-1.06076300080048408251e-9),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.54435380513870673497e-1),
             static_cast<RealType>(3.66021233157880878411e-1),
@@ -1198,7 +1202,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.6624e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.70720199535228802538e-2),
             static_cast<RealType>(2.67200763833749070079e-2),
             static_cast<RealType>(7.37400551855064729769e-3),
@@ -1208,7 +1212,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(2.03102753319827713542e-8),
             static_cast<RealType>(-5.16172854149066643529e-11),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.05317644829451086870e-1),
             static_cast<RealType>(3.73713496637025562492e-1),
@@ -1226,7 +1230,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 2.6243e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.74847564444513000450e-2),
             static_cast<RealType>(6.00209162595027323742e-3),
             static_cast<RealType>(7.86550260761375576075e-4),
@@ -1236,7 +1240,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-9.81286503831545640189e-12),
             static_cast<RealType>(2.98763969872672156104e-14),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.27732094554221674504e-1),
             static_cast<RealType>(1.14330643482604301178e-1),
@@ -1253,7 +1257,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 5.4684e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(6.22684103170563193015e-3),
             static_cast<RealType>(1.34714356588780958096e-3),
             static_cast<RealType>(9.51289465377874891896e-5),
@@ -1263,7 +1267,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(-6.18017115447736427379e-14),
             static_cast<RealType>(9.11626234402148561268e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.09895694991285975774e-1),
             static_cast<RealType>(3.69874670435930773471e-2),
@@ -1280,7 +1284,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 6.5947e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.20357145727036120652e-3),
             static_cast<RealType>(1.45412555771401325111e-4),
             static_cast<RealType>(3.27819006009093198652e-6),
@@ -1289,7 +1293,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             static_cast<RealType>(5.71421706870777687254e-14),
             static_cast<RealType>(-1.48321866072033823195e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.12851983233980279746e-1),
             static_cast<RealType>(4.94650928817638043712e-3),
@@ -1307,13 +1311,13 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
         // Rational Approximation
         // Maximum Relative Error: 6.2709e-17
-        static const RealType P[4] = {
+        BOOST_MATH_STATIC const RealType P[4] = {
             static_cast<RealType>(3.98942280401432677940e-1),
             static_cast<RealType>(2.89752186412133782995e-2),
             static_cast<RealType>(4.67360459917040710474e0),
             static_cast<RealType>(-1.26770824563800250704e-1),
         };
-        static const RealType Q[3] = {
+        BOOST_MATH_STATIC const RealType Q[3] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.26301023103568827709e-2),
             static_cast<RealType>(1.60899894281099149848e1),
@@ -1327,7 +1331,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 
 
 template <class RealType>
-inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1336,7 +1340,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 4.7720e-37
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.33333333333333333333333333333333333333e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38519736580901276671338330967060054188e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.07012342772403725079487012557507575976e-2),
@@ -1352,7 +1356,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.23420723211833268177898025846064230665e-12),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13807083548358335699029971528179486964e-13),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00810772528427939684296334977783425582e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.24383652800043768524894854013745098654e-1),
@@ -1375,7 +1379,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 1.6297e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.84196970581015939887507434989936103587e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23864910443500344832158256856064580005e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.72066675347648126090497588433854314742e-2),
@@ -1390,7 +1394,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.19848671456872291336347012756651759817e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.00479393063394570750334218362674723065e-13),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24929390929112144560152115661603117364e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.34853762543033883106055186520573363290e-1),
@@ -1413,7 +1417,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 2.8103e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07409273397524124098315500450332255837e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.98373054365213259465522536994638631699e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30851284606709136235419547406278197945e-2),
@@ -1429,7 +1433,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.72220647682193638971237255396233171508e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.45008884108655511268690849420714428764e-15),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.42652074703683973183213296310906006173e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03479786698331153607905223548719296572e0),
@@ -1454,7 +1458,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 7.5930e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70720199535228802537946089633331273434e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.85220706158476482443562698303252970927e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55090221054465759649629178911450010833e-2),
@@ -1470,7 +1474,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.73710011278079325323578951018770847628e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.70140037580287364298206334732060874507e-16),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36848014038411798213992770858203510748e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.15373052017549822413011375404872359177e-1),
@@ -1497,7 +1501,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 7.3609e-35
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74847564444513000450056174922427854591e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56842503159303803254436983444304764079e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.48504629497687889354406208309334148575e-3),
@@ -1515,7 +1519,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.09912208206107606750610288716869139753e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.98451733054622166748935243139556132704e-26),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08148065380582488495702136465010348576e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.42385352331252779422725444021027377277e-1),
@@ -1541,7 +1545,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 9.7192e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.22684103170563193014558918295924551173e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.55222688816852408105912768186300290291e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.60747505331765587662432023547517953629e-4),
@@ -1558,7 +1562,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.02156808288545876198121127510075217184e-27),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.65549196385656698597261688277898043367e-30),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.03426141030409708635168766288764563749e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13808987755928828118915442251025992769e-1),
@@ -1583,7 +1587,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 9.7799e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.20357145727036120652264700679701054983e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.95712324967981162396595365933255312698e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08619492652809635942960438372427086939e-5),
@@ -1598,7 +1602,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15780217054514513493147192853488153246e-24),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31961589164397397724611386366339562789e-28),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26440207646105117747875545474828367516e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.27872879091838733280518786463281413334e-2),
@@ -1625,7 +1629,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
         // Rational Approximation
         // Maximum Relative Error: 3.5865e-37
         // LCOV_EXCL_START
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12426566605292130233061857505057433291e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.91574528280329492283287073127040983832e1),
@@ -1635,7 +1639,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.44343825578434751356083230369361399507e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07224810408790092272497403739984510394e2),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.32474438135610721926278423612948794250e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.27594461167587027771303292526448542806e2),
@@ -1652,7 +1656,7 @@ inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1662,7 +1666,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 1.6964e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.23238998449671083670e-1),
             static_cast<RealType>(4.95353582976475183891e-1),
             static_cast<RealType>(2.45823281826037784270e-1),
@@ -1672,7 +1676,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(2.66220579589280704089e-4),
             static_cast<RealType>(3.09442180091323751049e-6),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.16241922223786900600e-1),
             static_cast<RealType>(2.75690727171711638879e-1),
@@ -1689,7 +1693,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
         // Rational Approximation
         // Maximum Relative Error: 5.8303e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.62598955251978523175e-1),
             static_cast<RealType>(2.30154661502402196205e-1),
             static_cast<RealType>(1.29233975368291684522e-1),
@@ -1699,7 +1703,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             static_cast<RealType>(3.35259917978421935141e-4),
             static_cast<RealType>(1.22071311320012805777e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.63771793313770952352e-2),
             static_cast<RealType>(2.23602260938227310054e-1),
@@ -1719,7 +1723,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 3.6017e-18
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(8.31806744221966404520e-1),
                 static_cast<RealType>(1.34481067378012055850e0),
                 static_cast<RealType>(9.12139427469494995264e-1),
@@ -1729,7 +1733,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.89700733471520162946e-3),
                 static_cast<RealType>(1.13854052826846329787e-4),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.29694286517571741097e0),
                 static_cast<RealType>(7.99686735441213882518e-1),
@@ -1747,7 +1751,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 1.3504e-17
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(1.10294551528734705946e0),
                 static_cast<RealType>(1.26696377028973554615e0),
                 static_cast<RealType>(6.63115985833429688941e-1),
@@ -1757,7 +1761,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(4.04328442334023561279e-4),
                 static_cast<RealType>(1.42364413902075896503e-5),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.09709853682665798542e0),
                 static_cast<RealType>(5.63687797989627787500e-1),
@@ -1775,7 +1779,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 8.8272e-18
-            static const RealType P[7] = {
+            BOOST_MATH_STATIC const RealType P[7] = {
                 static_cast<RealType>(1.18246847255744057280e0),
                 static_cast<RealType>(8.41320657699741240497e-1),
                 static_cast<RealType>(2.55093097377551881478e-1),
@@ -1784,7 +1788,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(2.04688276265993954527e-4),
                 static_cast<RealType>(4.43354791268634655473e-6),
             };
-            static const RealType Q[7] = {
+            BOOST_MATH_STATIC const RealType Q[7] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(7.07103973315808077783e-1),
                 static_cast<RealType>(2.13664682181055450396e-1),
@@ -1801,7 +1805,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 
             // Rational Approximation
             // Maximum Relative Error: 2.6236e-18
-            static const RealType P[6] = {
+            BOOST_MATH_STATIC const RealType P[6] = {
                 static_cast<RealType>(1.19497306481411168356e0),
                 static_cast<RealType>(3.90497195765498241356e-1),
                 static_cast<RealType>(5.13120330037626853257e-2),
@@ -1809,7 +1813,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 static_cast<RealType>(1.12075935888344736993e-4),
                 static_cast<RealType>(1.48743616420183584738e-6),
             };
-            static const RealType Q[6] = {
+            BOOST_MATH_STATIC const RealType Q[6] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(3.26493785348088598123e-1),
                 static_cast<RealType>(4.28813205161574223713e-2),
@@ -1829,7 +1833,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1840,7 +1844,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
         // Rational Approximation
         // Maximum Relative Error: 1.0688e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.23238998449671083670041452413316011920e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.14900991369455846775267187236501987891e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.19132787054572299485638029221977944555e-1),
@@ -1856,7 +1860,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21838020977580479741299141050400953125e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.46723648594704078875476888175530463986e-12),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.98700317671474659677458220091101276158e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.00405631175818416028878082789095587658e-1),
@@ -1880,7 +1884,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
         // Rational Approximation
         // Maximum Relative Error: 5.1815e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.62598955251978523174755901843430986522e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.08127698872954954678270473317137288772e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70144997468767751317246482211703706086e-1),
@@ -1896,7 +1900,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.30746545799073289786965697800049892311e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41870129065056783732691371215602982173e-9),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.75919235734607601884356783586727272494e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.57656678936617227532275100649989944452e-1),
@@ -1924,7 +1928,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 6.4678e-36
             // LCOV_EXCL_START
-            static const RealType P[16] = {
+            BOOST_MATH_STATIC const RealType P[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.31806744221966404520449104514474066823e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50292887071777664663197915067642779665e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.45140067157601150721516139901304901854e0),
@@ -1942,7 +1946,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96371756262605118060185816854433322493e-8),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88472819535099746216179119978362211227e-10),
             };
-            static const RealType Q[16] = {
+            BOOST_MATH_STATIC const RealType Q[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.68923525157720774962908922391133419863e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.40714902096062779527207435671907059131e0),
@@ -1969,7 +1973,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 3.5975e-36
             // LCOV_EXCL_START
-            static const RealType P[16] = {
+            BOOST_MATH_STATIC const RealType P[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.10294551528734705945662709421382590676e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.26135857114883288617323671166863478751e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23504465936865651893193560109437792738e0),
@@ -1987,7 +1991,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.93965060142992479149039624149602039394e-10),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36407983918582149239548869529460234702e-12),
             };
-            static const RealType Q[16] = {
+            BOOST_MATH_STATIC const RealType Q[16] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99867960957804580209868321228347067213e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94236623527818880544030470097296139679e0),
@@ -2014,7 +2018,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 2.6792e-35
             // LCOV_EXCL_START
-            static const RealType P[15] = {
+            BOOST_MATH_STATIC const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18246847255744057280356900905660312795e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.77955886026107125189834586992142580148e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24948425302263641813107623611637262126e0),
@@ -2031,7 +2035,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.15388861641344998301210173677051088515e-12),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.83956842740198388242245209024484381888e-29),
             };
-            static const RealType Q[14] = {
+            BOOST_MATH_STATIC const RealType Q[14] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.50056124032615852703112365430040751173e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05112559537845833793684655693572118348e0),
@@ -2056,7 +2060,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 2.1744e-36
             // LCOV_EXCL_START
-            static const RealType P[12] = {
+            BOOST_MATH_STATIC const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19497306481411168355692832231058399132e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.15593166681833539521403250736661720488e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54020260738207743315755235213180652303e-1),
@@ -2070,7 +2074,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29602226691665918537895803270497291716e-11),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.53666531487585211574942518181922132884e-14),
             };
-            static const RealType Q[12] = {
+            BOOST_MATH_STATIC const RealType Q[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.82230649578130958108098853863277631065e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.12412482738973738235656376802445565005e-1),
@@ -2093,7 +2097,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
             // Rational Approximation
             // Maximum Relative Error: 3.4699e-36
             // LCOV_EXCL_START
-            static const RealType P[10] = {
+            BOOST_MATH_STATIC const RealType P[10] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19659414007358083585943280640656311534e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.36969140730640253987817932335415532846e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21946928005759888612066397569236165853e-2),
@@ -2105,7 +2109,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.00054716479138657682306851175059678989e-11),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48798342894235412426464893852098239746e-14),
             };
-            static const RealType Q[10] = {
+            BOOST_MATH_STATIC const RealType Q[10] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81588658109851219975949691772676519853e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.52583331848892383968186924120872369151e-2),
@@ -2129,7 +2133,7 @@ inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integra
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
     }
@@ -2137,12 +2141,12 @@ inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const s
         return complement ? 1 - mapairy_cdf_minus_imp_prec(x, tag) : mapairy_cdf_minus_imp_prec(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
     }
@@ -2150,18 +2154,18 @@ inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const s
         return complement ? 1 - mapairy_cdf_minus_imp_prec(x, tag) : mapairy_cdf_minus_imp_prec(x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
     //
     // This calculates the cdf of the Map-Airy distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::cdf(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(mapairy<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -2197,7 +2201,7 @@ inline RealType mapairy_cdf_imp(const mapairy_distribution<RealType, Policy>& di
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2207,7 +2211,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.5488e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(-1.17326074020471664075e0),
             static_cast<RealType>(1.51461298154568349598e0),
             static_cast<RealType>(1.19979368094343490487e1),
@@ -2216,7 +2220,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(7.17766543775229176131e0),
             static_cast<RealType>(4.79284243496552841508e0),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.76268072706610602584e0),
             static_cast<RealType>(-4.88492535243404839734e0),
@@ -2233,7 +2237,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 7.5181e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(-1.63281240925531302762e0),
             static_cast<RealType>(-4.92351310795930780147e0),
             static_cast<RealType>(1.43448529253101759409e1),
@@ -2242,7 +2246,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.87298447423841965301e1),
             static_cast<RealType>(1.31575930750093554120e1),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.38761652244702318296e0),
             static_cast<RealType>(2.40932080746189543284e0),
@@ -2258,7 +2262,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.3028e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-2.18765177572396469657e0),
             static_cast<RealType>(-3.65752788934974426531e1),
             static_cast<RealType>(-1.81144810822028903904e2),
@@ -2268,7 +2272,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-8.76285742384616909177e2),
             static_cast<RealType>(-2.33786726970025938837e2),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.91797638291395345792e1),
             static_cast<RealType>(1.24293724082506952768e2),
@@ -2286,7 +2290,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 6.1147e-18
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(-2.18765177572396470773e0),
             static_cast<RealType>(-2.19887766409334094428e0),
             static_cast<RealType>(-7.77080107207360785208e-1),
@@ -2294,7 +2298,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-6.64711321022529990367e-3),
             static_cast<RealType>(-9.74212491048543799073e-5),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.91919722132624625590e-1),
             static_cast<RealType>(2.17415447268626558639e-1),
@@ -2310,7 +2314,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.0508e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-2.59822399410385085335e0),
             static_cast<RealType>(-2.24306757759003016244e0),
             static_cast<RealType>(-7.36208578161752060979e-1),
@@ -2320,7 +2324,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-3.33661282483762192446e-6),
             static_cast<RealType>(-4.19292241201527861927e-9),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.23065798041556418844e-1),
             static_cast<RealType>(1.96731305131315877264e-1),
@@ -2337,7 +2341,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.1997e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-3.67354365380697580447e0),
             static_cast<RealType>(-1.52181685844845957618e0),
             static_cast<RealType>(-2.40883948836320845233e-1),
@@ -2347,7 +2351,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-6.12797605223700996671e-8),
             static_cast<RealType>(-3.78061321691170114390e-11),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.57770840766081587688e-1),
             static_cast<RealType>(4.81290550545412209056e-2),
@@ -2364,7 +2368,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.4331e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-4.92187819510636697128e0),
             static_cast<RealType>(-9.94924018698264727979e-1),
             static_cast<RealType>(-7.69914962772717316098e-2),
@@ -2374,7 +2378,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-1.13886013623971006760e-9),
             static_cast<RealType>(-3.46758191090170732580e-13),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.77270673840643360017e-1),
             static_cast<RealType>(1.18099604045834575786e-2),
@@ -2391,7 +2395,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 2.7742e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-6.41443550638291133784e0),
             static_cast<RealType>(-6.38369359780748328332e-1),
             static_cast<RealType>(-2.43420704406734621618e-2),
@@ -2401,7 +2405,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.14338367751477432622e-11),
             static_cast<RealType>(-3.23343844538964435927e-15),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.79845511272943785289e-2),
             static_cast<RealType>(2.90839059356197474893e-3),
@@ -2418,7 +2422,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.2451e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-8.23500806363233610938e0),
             static_cast<RealType>(-4.05652655284908839003e-1),
             static_cast<RealType>(-7.65978833819859622912e-3),
@@ -2428,7 +2432,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-4.07882839359528825925e-13),
             static_cast<RealType>(-3.05720104049292610799e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.37395212065018405474e-2),
             static_cast<RealType>(7.18654254114820140590e-4),
@@ -2445,7 +2449,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 3.8732e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-1.04845570631944023913e1),
             static_cast<RealType>(-2.56502856165700644836e-1),
             static_cast<RealType>(-2.40615394566347412600e-3),
@@ -2455,7 +2459,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-7.83146284114485675414e-15),
             static_cast<RealType>(-2.92218240202835807955e-19),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.17740414929742679904e-2),
             static_cast<RealType>(1.78084231709097280884e-4),
@@ -2472,7 +2476,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 4.6946e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-1.32865827226175698181e1),
             static_cast<RealType>(-1.61802434199627472010e-1),
             static_cast<RealType>(-7.55642602577784211259e-4),
@@ -2482,7 +2486,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-1.51422473889348610974e-16),
             static_cast<RealType>(-2.81661279271583206526e-21),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.08518414679241420227e-2),
             static_cast<RealType>(4.42335224797004486239e-5),
@@ -2499,7 +2503,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 5.7586e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(-1.67937186583822375593e1),
             static_cast<RealType>(-1.01958138247797604098e-1),
             static_cast<RealType>(-2.37409774265951876695e-4),
@@ -2509,7 +2513,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-2.94401318006358820268e-18),
             static_cast<RealType>(-2.73260616170245224789e-23),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.41357843707822974161e-3),
             static_cast<RealType>(1.10082540037527566536e-5),
@@ -2522,7 +2526,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
-        result = -std::numeric_limits<RealType>::infinity();
+        result = -boost::math::numeric_limits<RealType>::infinity();
     }
 
     return result;
@@ -2530,7 +2534,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
 
 
 template <class RealType>
-inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2541,7 +2545,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 4.2901e-35
         // LCOV_EXCL_START
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.48344198262277235851026749871350753173e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.18249834490570496537675012473572546187e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.20191368895639224466285643454767208281e1),
@@ -2553,7 +2557,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.16683694881010716925933071465043323946e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.04356966421177683585461937085598186805e1),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.75444066345435020043849341970820565274e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.95105673975812427406540024601734210826e0),
@@ -2575,7 +2579,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 2.8433e-36
         // LCOV_EXCL_START
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.17326074020471664204142312429732771661e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23412560010002723970559712941124583385e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83665111310407767293290698145068379130e1),
@@ -2588,7 +2592,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.14713948941614711932063053969010219677e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.62979741122708118776725634304028246971e0),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.10550060286464202595779024353437346419e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.15893254630199957990897452211066782021e0),
@@ -2609,7 +2613,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 5.9072e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63281240925531315038207673147576291783e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72733898245766165408685147762489513406e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.48666841594842113608962500631836790675e1),
@@ -2624,7 +2628,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.48386631313725080746815524770260451090e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.03293129698111279047104766073456412318e1),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.29511778027351594854005887702013466376e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.66155745848864270109281703659789474448e1),
@@ -2648,7 +2652,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 9.9092e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467019660e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16991481696416567893311341049825218287e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.25497491118598918048058751362064598010e3),
@@ -2665,7 +2669,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.68917274690585744147547352309416731690e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.96914697182030973966321601422851730384e4),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98063872144867195074924232601423646991e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65911346382127464683324945513128779971e2),
@@ -2691,7 +2695,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 3.9653e-35
         // LCOV_EXCL_START
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18765177572396470161180571018467025793e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.94718878144788678915739777385667044494e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.01760622104142726407095836139719210570e0),
@@ -2704,7 +2708,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.23852908701349250480831167491889740823e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.61008160195204632725691076288641221707e-10),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59109221235949005113322202980300291082e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07119192591092503378838510797916225920e0),
@@ -2726,7 +2730,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 6.7872e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.59822399410385083283727681965013517187e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.30676107401101401386206170152508285083e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.14999782004905950712290914501961213222e0),
@@ -2743,7 +2747,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.16259632533790175212174199386945953139e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51102540845397821195190063256442894688e-18),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51733661576324699382035973518172469602e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01435607980568082538278883569729476204e0),
@@ -2768,7 +2772,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 7.6679e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.67354365380697578246790709817724831418e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.98681625368564496421038758088088788795e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07310677200866436332040539417232353673e0),
@@ -2785,7 +2789,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.69717198111130468014375331439613690658e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54464319402577486444841981479085908190e-22),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.56568169258142086426383908572004868200e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52144703581828715720555168887427064424e-1),
@@ -2810,7 +2814,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 8.6323e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.92187819510636694694450607724165689649e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.97763858433958798529675258052376253402e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51315096979196319830162238831654165509e-1),
@@ -2827,7 +2831,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.46989755992471397407520449698676945629e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.84098833615882764168840211033822541979e-26),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.76933186134913044021577076301874622292e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.25794095712489484166470336696962749356e-2),
@@ -2852,7 +2856,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 9.8799e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.41443550638291131009585191506467028820e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.27887396494095561461365753577189254063e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12752633002089885479040650194288302309e-1),
@@ -2869,7 +2873,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.62195354664281744711336666974567406606e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.34400562353945663460416286570988365992e-30),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.87838171063584994806998206766890809367e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55395225505766120991458653457272783334e-2),
@@ -2894,7 +2898,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 1.1548e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.23500806363233607692361021471929016922e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.16747938711332885952564885548768072606e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.58252672740225210061031286151136185818e-2),
@@ -2911,7 +2915,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.36559452694774774399884349254686988041e-30),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.92396730553947142987611521115040472261e-35),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.36599681872296382199486815169747516110e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.86330544720458446620644055149504593514e-3),
@@ -2936,7 +2940,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 1.3756e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.04845570631944023525776899386112795330e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.18146685146173151383718092529868406030e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.13255476532916847606354932879190731233e-2),
@@ -2953,7 +2957,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.02313300749670214384591200940841254958e-34),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.40321396496046206171642334628524367374e-39),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.67292043485384876322219919215413286868e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.61652550158809553935603664087740554258e-4),
@@ -2978,7 +2982,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 1.6639e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.32865827226175697711590794217590458484e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.27551166309670994513910580518431041518e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.57161482253140058637495100797888501265e-3),
@@ -2995,7 +2999,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.20881889651487527801970182542596258873e-37),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56848486878078288956741060120464349537e-43),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.33267370502089423930888060969568705647e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39632352029900752622967578086289898150e-4),
@@ -3020,7 +3024,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 2.0360e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.67937186583822375017526293948703697225e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.06681764321003187068904973985967908140e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.12508887240195683379004033347903251977e-3),
@@ -3037,7 +3041,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.83187517541957887917067558455828915184e-41),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.21480186561579326423946788448005430367e-47),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16494591376838053609854716130343599036e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.97651667629616309497454026431358820357e-5),
@@ -3062,7 +3066,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 2.5130e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.11959316095291435774375635827672517008e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.30292575371366023255165927527306483022e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.54260157439166096303943109715675142318e-4),
@@ -3079,7 +3083,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.78815984551154095621830792130401294111e-45),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.20516030880916148179297554212609531432e-51),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.81973541224235020744673910266545976833e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49156990107280109344880219729275939242e-5),
@@ -3104,7 +3108,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 3.1220e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.67307564006689676593687414536012112755e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.21005690250741024744367516466433711478e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.11537345869365655126739041291119096558e-4),
@@ -3121,7 +3125,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.25766346856943928908756472385992861288e-49),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.44601448994095786447982489957909713982e-55),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.90814053669730896497462224007523900520e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.72450689508305973756255440356759005330e-6),
@@ -3146,7 +3150,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 3.8974e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.36960987939726803544369406181770745475e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.17239311695985070524235502979761682692e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.51192208811996535244435318068035492922e-5),
@@ -3163,7 +3167,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.51767319872105260145583037426067406953e-53),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.87159268409640967747617639113346310759e-59),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.45350026842128595165328480395513258721e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.30398532102631290226106936127181928207e-7),
@@ -3188,7 +3192,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 4.8819e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.24662793339079714510108682543625432532e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25841960642102016210295419419373971750e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.10589156998251704634852108689102850747e-5),
@@ -3205,7 +3209,7 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.99466700145428173772768099494881455874e-57),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.43473066278196981345209422626769148425e-63),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.26570199429958856038191879713341034013e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32484776300757286079244074394356908390e-7),
@@ -3225,14 +3229,14 @@ inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::in
         result = tools::evaluate_polynomial(P, t) / tools::evaluate_polynomial(Q, t);
     }
     else {
-        result = -std::numeric_limits<RealType>::infinity();
+        result = -boost::math::numeric_limits<RealType>::infinity();
     }
 
     return result;
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3242,7 +3246,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Absolute Error: 1.8559e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.81512108276093785320e-1),
             static_cast<RealType>(-2.74296316128959647914e0),
             static_cast<RealType>(-3.29973875964825685757e1),
@@ -3252,7 +3256,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-6.66681853240657307279e1),
             static_cast<RealType>(-4.28101952511581488588e1),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.20189490825315245036e0),
             static_cast<RealType>(1.63469912146101848441e1),
@@ -3272,7 +3276,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Absolute Error: 4.6019e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.70276979914029733585e0),
             static_cast<RealType>(2.09991992116646276165e1),
             static_cast<RealType>(2.26775403775298867998e1),
@@ -3281,7 +3285,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(-7.08748473959943943929e1),
             static_cast<RealType>(1.54245210917147215257e3),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.13092357122115486375e1),
             static_cast<RealType>(1.57318281834689144053e2),
@@ -3299,7 +3303,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 1.2193e-19
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.25692449785074345588e-1),
             static_cast<RealType>(3.10963501706596356267e-1),
             static_cast<RealType>(2.91357806215297069863e-2),
@@ -3309,7 +3313,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(1.59538372221030642757e-4),
             static_cast<RealType>(4.74040834029330213692e-6),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.14801234415100707213e-1),
             static_cast<RealType>(1.04693730144480856638e-1),
@@ -3327,7 +3331,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 4.4418e-17
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             static_cast<RealType>(5.07341098045260541890e-1),
             static_cast<RealType>(3.11771145411143166935e-1),
             static_cast<RealType>(1.74515601081894060888e-1),
@@ -3340,7 +3344,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(4.53513191985642134268e-6),
             static_cast<RealType>(2.62304611053075404923e-7),
         };
-        static const RealType Q[11] = {
+        BOOST_MATH_STATIC const RealType Q[11] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.28225379952156944029e-1),
             static_cast<RealType>(3.49662079845715371907e-1),
@@ -3361,7 +3365,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 5.7932e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(5.41774626094491510395e-1),
             static_cast<RealType>(4.11060141334529017898e-1),
             static_cast<RealType>(1.48195601801946264526e-1),
@@ -3373,7 +3377,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(7.77428184258777394627e-8),
             static_cast<RealType>(2.51255632629650930196e-14),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.58341767924960527280e-1),
             static_cast<RealType>(2.73511775500642961539e-1),
@@ -3392,7 +3396,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
         // Rational Approximation
         // Maximum Relative Error: 9.0396e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(5.41926067826974905066e-1),
             static_cast<RealType>(4.86926556246548518715e-1),
             static_cast<RealType>(2.11963908288176005856e-1),
@@ -3403,7 +3407,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             static_cast<RealType>(1.50444847316426133872e-5),
             static_cast<RealType>(1.87458213915373906356e-6),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.98511036742503939380e-1),
             static_cast<RealType>(3.91130673008184655152e-1),
@@ -3427,7 +3431,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             result = 1 / (cbrt(p) * cbrt(p) * cbrt(constants::two_pi<RealType>()));
         }
         else {
-            result = std::numeric_limits<RealType>::infinity();
+            result = boost::math::numeric_limits<RealType>::infinity();
         }
     }
 
@@ -3436,7 +3440,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 
 
 template <class RealType>
-inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3447,7 +3451,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Absolute Error: 4.0835e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.00474815142578902619056852805926666121e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56422290947427848191079775267512708223e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.70103710180837859003070678080056933649e1),
@@ -3462,7 +3466,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06758225510372847658316203115073730186e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10895417312529385966062255102265009972e0),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.88252553879196710256650370298744093367e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54875259600848880869571364891152935969e0),
@@ -3485,7 +3489,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Absolute Error: 5.7633e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81512108276093787175849069715334402323e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24417080443497141096829831516758083481e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.67006165991083501886186268944009973084e1),
@@ -3501,7 +3505,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.42750073722992463087082849671338957023e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.54255748148299874514839812717054396793e2),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64823387375875361292425741663822893626e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02973633484731117050245517938177308809e2),
@@ -3525,7 +3529,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Absolute Error: 2.1140e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70276979914029738186601698003670175907e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.63126762626382548478172664328434577553e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.04190225271045202674546813475341133174e3),
@@ -3542,7 +3546,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.56839957539576784391036362196229047625e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95604329277359828898502487252547842378e6),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79208640567193066236912382037923299779e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.94775812217734059201656828286490832145e2),
@@ -3569,7 +3573,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 1.1409e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25692449785074345466504245009175450649e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75679137667345136118441108839649360362e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06171803174020856964914440692439080669e-2),
@@ -3585,7 +3589,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30857042700765443668305406695750760693e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.10466412567107519640190849286913680449e-10),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31914248618040435028023418981527961171e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.73578090645412656850163531828709850171e-2),
@@ -3610,7 +3614,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 1.2521e-35
         // LCOV_EXCL_START
-        static const RealType P[23] = {
+        BOOST_MATH_STATIC const RealType P[23] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.07341098045260497471001948654506267614e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16518383383878659278973043343250842753e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.10029094208424121908983949243560936013e-1),
@@ -3635,7 +3639,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.39027665085346558512961348663034579801e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05739751797738770096482688062542436470e-15),
         };
-        static const RealType Q[23] = {
+        BOOST_MATH_STATIC const RealType Q[23] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43370372582239919321785765900615222895e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.52872159582703775260145036441128318159e-1),
@@ -3669,7 +3673,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 2.0703e-35
         // LCOV_EXCL_START
-        static const RealType P[21] = {
+        BOOST_MATH_STATIC const RealType P[21] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41774626094491452462664949805613444094e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96383089261273022706449773421031102175e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.16315295073029174376617863024082371446e-1),
@@ -3692,7 +3696,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39869585157420474301450400944478312794e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.82128612844034824876694595066123093042e-27),
         };
-        static const RealType Q[20] = {
+        BOOST_MATH_STATIC const RealType Q[20] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65414405277042133067228113526697909557e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32179221250476209346757936207079534440e0),
@@ -3723,7 +3727,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 3.4124e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926067826974814669251179264786585885e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.21141529920003643675474888047093566280e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59964592861304582755436075901659426485e-1),
@@ -3744,7 +3748,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47286214854389274681661944885238913581e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.73701196181204039400706651811524874455e-34),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.77119890916406072259446489508263892540e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95177888809731859578167185583119074026e-1),
@@ -3773,7 +3777,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
         // Rational Approximation
         // Maximum Relative Error: 2.1680e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.41926070139289008206183757488364846894e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.78434820569480998586988738136492447574e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.07939171933509333571821660328723436210e-1),
@@ -3793,7 +3797,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.26635728806398747570910072594323836441e-17),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.96470010392255781222480229189380065951e-18),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.82841492468725267177870050157374330523e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.83703946702662950408034486958999188355e-1),
@@ -3826,7 +3830,7 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
             result = 1 / (cbrt(p) * cbrt(p) * cbrt(constants::two_pi<RealType>()));
         }
         else {
-            result = std::numeric_limits<RealType>::infinity();
+            result = boost::math::numeric_limits<RealType>::infinity();
         }
     }
 
@@ -3834,32 +3838,32 @@ inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::in
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
-        return mapairy_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? mapairy_quantile_upper_imp_prec(1 - p, tag) : mapairy_quantile_lower_imp_prec(1 - p, tag);
     }
 
     return complement ? mapairy_quantile_upper_imp_prec(p, tag) : mapairy_quantile_lower_imp_prec(p, tag);
 }
 
 template <class RealType>
-inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
-        return mapairy_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? mapairy_quantile_upper_imp_prec(1 - p, tag) : mapairy_quantile_lower_imp_prec(1 - p, tag);
     }
 
     return complement ? mapairy_quantile_upper_imp_prec(p, tag) : mapairy_quantile_lower_imp_prec(p, tag);
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_quantile_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp(const mapairy_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
 {
     // This routine implements the quantile for the Map-Airy distribution,
     // the value p may be the probability, or its complement if complement=true.
 
-    static const char* function = "boost::math::quantile(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(mapairy<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -3895,23 +3899,23 @@ inline RealType mapairy_quantile_imp(const mapairy_distribution<RealType, Policy
 }
 
 template <class RealType>
-inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-1.16158727113597068525);
 }
 
 template <class RealType>
-inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.1615872711359706852500000803029112987);
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_mode_imp(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp(const mapairy_distribution<RealType, Policy>& dist)
 {
     // This implements the mode for the Map-Airy distribution,
 
-    static const char* function = "boost::math::mode(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::mode(mapairy<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -3943,23 +3947,23 @@ inline RealType mapairy_mode_imp(const mapairy_distribution<RealType, Policy>& d
 }
 
 template <class RealType>
-inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-0.71671068545502205332);
 }
 
 template <class RealType>
-inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.71671068545502205331700196278067230944440);
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_median_imp(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp(const mapairy_distribution<RealType, Policy>& dist)
 {
     // This implements the median for the Map-Airy distribution,
 
-    static const char* function = "boost::math::median(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::median(mapairy<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -3991,23 +3995,23 @@ inline RealType mapairy_median_imp(const mapairy_distribution<RealType, Policy>&
 }
 
 template <class RealType>
-inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.00727681841065634600);
 }
 
 template <class RealType>
-inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0072768184106563460003025875575283708);
 }
 
 template <class RealType, class Policy>
-inline RealType mapairy_entropy_imp(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp(const mapairy_distribution<RealType, Policy>& dist)
 {
     // This implements the entropy for the Map-Airy distribution,
 
-    static const char* function = "boost::math::entropy(mapairy<%1%>&, %1%)";
+    constexpr auto function = "boost::math::entropy(mapairy<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -4042,20 +4046,20 @@ class mapairy_distribution
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    mapairy_distribution(RealType l_location = 0, RealType l_scale = 1)
+    BOOST_MATH_GPU_ENABLED mapairy_distribution(RealType l_location = 0, RealType l_scale = 1)
         : mu(l_location), c(l_scale)
     {
-        static const char* function = "boost::math::mapairy_distribution<%1%>::mapairy_distribution";
+        constexpr auto function = "boost::math::mapairy_distribution<%1%>::mapairy_distribution";
         RealType result = 0;
         detail::check_location(function, l_location, &result, Policy());
         detail::check_scale(function, l_scale, &result, Policy());
     } // mapairy_distribution
 
-    RealType location()const
+    BOOST_MATH_GPU_ENABLED RealType location()const
     {
         return mu;
     }
-    RealType scale()const
+    BOOST_MATH_GPU_ENABLED RealType scale()const
     {
         return c;
     }
@@ -4075,90 +4079,90 @@ mapairy_distribution(RealType, RealType) -> mapairy_distribution<typename boost:
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const mapairy_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const mapairy_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const mapairy_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const mapairy_distribution<RealType, Policy>&)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::mapairy_pdf_imp(dist, x);
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const mapairy_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::mapairy_cdf_imp(dist, x, false);
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const mapairy_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const mapairy_distribution<RealType, Policy>& dist, const RealType& p)
 {
     return detail::mapairy_quantile_imp(dist, p, false);
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::mapairy_cdf_imp(c.dist, c.param, true);
 } //  cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<mapairy_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::mapairy_quantile_imp(c.dist, c.param, true);
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const mapairy_distribution<RealType, Policy> &dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const mapairy_distribution<RealType, Policy> &dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const mapairy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
-    return std::numeric_limits<RealType>::infinity();
+    return boost::math::numeric_limits<RealType>::infinity();
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const mapairy_distribution<RealType, Policy>& dist)
 {
     return detail::mapairy_mode_imp(dist);
 }
 
 template <class RealType, class Policy>
-inline RealType median(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const mapairy_distribution<RealType, Policy>& dist)
 {
     return detail::mapairy_median_imp(dist);
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const mapairy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4168,11 +4172,11 @@ inline RealType skewness(const mapairy_distribution<RealType, Policy>& /*dist*/)
         "boost::math::skewness(mapairy<%1%>&)",
         "The Map-Airy distribution does not have a skewness: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const mapairy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4182,11 +4186,11 @@ inline RealType kurtosis(const mapairy_distribution<RealType, Policy>& /*dist*/)
         "boost::math::kurtosis(mapairy<%1%>&)",
         "The Map-Airy distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const mapairy_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const mapairy_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -4196,11 +4200,11 @@ inline RealType kurtosis_excess(const mapairy_distribution<RealType, Policy>& /*
         "boost::math::kurtosis_excess(mapairy<%1%>&)",
         "The Map-Airy distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const mapairy_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const mapairy_distribution<RealType, Policy>& dist)
 {
     return detail::mapairy_entropy_imp(dist);
 }

From 4f914304c9cc14b34e0391cf401aa0c2bcfa638e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:12:21 -0400
Subject: [PATCH 158/399] Add CUDA testing to mapairy dist

---
 test/cuda_jamfile                |   6 ++
 test/test_mapairy_cdf_double.cu  | 110 +++++++++++++++++++++++++++++++
 test/test_mapairy_cdf_float.cu   | 110 +++++++++++++++++++++++++++++++
 test/test_mapairy_pdf_double.cu  | 110 +++++++++++++++++++++++++++++++
 test/test_mapairy_pdf_float.cu   | 110 +++++++++++++++++++++++++++++++
 test/test_mapairy_quan_double.cu | 110 +++++++++++++++++++++++++++++++
 test/test_mapairy_quan_float.cu  | 110 +++++++++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_mapairy_cdf_double.cu
 create mode 100644 test/test_mapairy_cdf_float.cu
 create mode 100644 test/test_mapairy_pdf_double.cu
 create mode 100644 test/test_mapairy_pdf_float.cu
 create mode 100644 test/test_mapairy_quan_double.cu
 create mode 100644 test/test_mapairy_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 3a109e0955..ba7f8d153c 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -52,6 +52,12 @@ run test_landau_pdf_double.cu ;
 run test_landau_pdf_float.cu ;
 run test_landau_quan_double.cu;
 run test_landau_quan_float.cu ;
+run test_mapairy_cdf_double.cu ;
+run test_mapairy_cdf_float.cu ;
+run test_mapairy_pdf_double.cu ;
+run test_mapairy_pdf_float.cu ;
+run test_mapairy_quan_double.cu ;
+run test_mapairy_quan_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_mapairy_cdf_double.cu b/test/test_mapairy_cdf_double.cu
new file mode 100644
index 0000000000..1494181bf5
--- /dev/null
+++ b/test/test_mapairy_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_mapairy_cdf_float.cu b/test/test_mapairy_cdf_float.cu
new file mode 100644
index 0000000000..41dd4615aa
--- /dev/null
+++ b/test/test_mapairy_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_mapairy_pdf_double.cu b/test/test_mapairy_pdf_double.cu
new file mode 100644
index 0000000000..ad3abfbeea
--- /dev/null
+++ b/test/test_mapairy_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_mapairy_pdf_float.cu b/test/test_mapairy_pdf_float.cu
new file mode 100644
index 0000000000..cabee4a2f6
--- /dev/null
+++ b/test/test_mapairy_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_mapairy_quan_double.cu b/test/test_mapairy_quan_double.cu
new file mode 100644
index 0000000000..fe6265effe
--- /dev/null
+++ b/test/test_mapairy_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_mapairy_quan_float.cu b/test/test_mapairy_quan_float.cu
new file mode 100644
index 0000000000..ad2f6b5eb4
--- /dev/null
+++ b/test/test_mapairy_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::mapairy_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 15000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 0ab09dd1f2fac1957024c13d1a4ec5315429566d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:19:10 -0400
Subject: [PATCH 159/399] Add sycl testing and adjust a few tolerances

---
 test/sycl_jamfile     |  1 +
 test/test_mapairy.cpp | 36 ++++++++++++++++++++++++++++++++++--
 2 files changed, 35 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index ae4742c47d..9ea1095cd4 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -15,6 +15,7 @@ run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
 run test_exponential_dist.cpp ;
 run test_landau.cpp ;
+run test_mapairy.cpp ;
 
 # Special Functions
 run pow_test.cpp ;
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index 2dcd1cfdaf..c1d1c739b0 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -1,13 +1,14 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
 #define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsMapAiryTest
+#include <boost/math/tools/config.hpp>
 #include <boost/test/included/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
-#include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/mapairy.hpp>
 
@@ -16,7 +17,11 @@
 #endif
 
 using boost::math::mapairy_distribution;
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#include <boost/multiprecision/cpp_bin_float.hpp>
 using boost::multiprecision::cpp_bin_float_quad;
+#endif
 
 template<class RealType, int N>
 void do_test_mapairy_pdf(){
@@ -58,9 +63,16 @@ void do_test_mapairy_pdf(){
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-7)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.50933920988971071711086365057147867083089476835078e-12), tolerance * 10);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.93525639583557913222186453754518161964863338679333e-10), tolerance * 10);
 
+    #ifndef BOOST_MATH_HAS_GPU_SUPPORT
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.34369873917936310843493426518284206307542912325702e-8), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77757355685380561185988935905104213909281485602180e-6), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.67935873875498302175093073530783568485155988744416e-5), tolerance);
+    #else
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 7.34369873917936310843493426518284206307542912325702e-8), tolerance*10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 2.77757355685380561185988935905104213909281485602180e-6), tolerance*10);
+    BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 5.67935873875498302175093073530783568485155988744416e-5), tolerance*10);
+    #endif
+    
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 6.63150314678587224494834533488274597847689803128076e-4), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 4.66981984951457236403520646020207894651500649740558e-3), tolerance);
     BOOST_CHECK_CLOSE(pdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.04268591430185285447948956767040247962753669747157e-2), tolerance);
@@ -284,8 +296,14 @@ void do_test_mapairy_cdf() {
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.03383983622833649608546095853620837892086215933298e-10), tolerance * 10);
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-6)), BOOST_MATH_BIG_CONSTANT(RealType, N, 8.91537779419133030075704775849634109699414218730481e-9), tolerance * 10);
 
+    #ifndef BOOST_MATH_HAS_GPU_SUPPORT
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.98085764775551392183308859729746156105641469279537e-7), tolerance);
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.74005376900861403666100209810033834996576655180465e-6), tolerance);
+    #else
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.98085764775551392183308859729746156105641469279537e-7), tolerance * 10);
+    BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 9.74005376900861403666100209810033834996576655180465e-6), tolerance * 10);
+    #endif
+
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4.5)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.38210242545410097936371084112947842536958832190953e-4), tolerance);
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-4)), BOOST_MATH_BIG_CONSTANT(RealType, N, 1.20388922732913226923590659641162717163243937441333e-3), tolerance);
     BOOST_CHECK_CLOSE(cdf(dist, static_cast<RealType>(-3.75)), BOOST_MATH_BIG_CONSTANT(RealType, N, 3.01190141003747964176020229987886598385662366685178e-3), tolerance);
@@ -809,10 +827,12 @@ BOOST_AUTO_TEST_CASE(mapairy_pdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_pdf_fp128)
 {
     do_test_mapairy_pdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_cdf_fp64)
 {
@@ -826,10 +846,12 @@ BOOST_AUTO_TEST_CASE(mapairy_cdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_cdf_fp128)
 {
     do_test_mapairy_cdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp64)
 {
@@ -843,10 +865,12 @@ BOOST_AUTO_TEST_CASE(mapairy_ccdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_ccdf_fp128)
 {
     do_test_mapairy_ccdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp64)
 {
@@ -860,10 +884,12 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_quantile_nearzero_fp128)
 {
     do_test_mapairy_quantile_nearzero<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp64)
 {
@@ -877,10 +903,12 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_quantile_lower_fp128)
 {
     do_test_mapairy_quantile_lower<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp64)
 {
@@ -894,10 +922,12 @@ BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_quantile_upper_fp128)
 {
     do_test_mapairy_quantile_upper<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(mapairy_locscale_fp64)
 {
@@ -911,7 +941,9 @@ BOOST_AUTO_TEST_CASE(mapairy_locscale_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(mapairy_locscale_fp128)
 {
     do_test_mapairy_locscale_param<cpp_bin_float_quad, 113>();
 }
+#endif

From 548bed0bf332d809017147c43a15333affc140e4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:35:40 -0400
Subject: [PATCH 160/399] Add GPU support to holtsmark dist

---
 .../boost/math/distributions/holtsmark.hpp    | 340 +++++++++---------
 1 file changed, 172 insertions(+), 168 deletions(-)

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index 2649663bdf..8041cf8cf7 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -1,4 +1,5 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,6 +12,9 @@
 #pragma warning(disable : 4127) // conditional expression is constant
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -29,7 +33,7 @@ class holtsmark_distribution;
 namespace detail {
 
 template <class RealType>
-inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -37,7 +41,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 1) {
         // Rational Approximation
         // Maximum Relative Error: 4.7894e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.87352751452164445024e-1),
             static_cast<RealType>(1.18577398160636011811e-3),
             static_cast<RealType>(-2.16526599226820153260e-2),
@@ -47,7 +51,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.04197836740809694657e-4),
             static_cast<RealType>(1.74679078247026597959e-5),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.12654472808214997252e-3),
             static_cast<RealType>(2.93891863033354755743e-1),
@@ -65,7 +69,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.0925e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.02038159607840130389e-1),
             static_cast<RealType>(-1.20368541260123112191e-2),
             static_cast<RealType>(-3.19235497414059987151e-3),
@@ -75,7 +79,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(9.19551014849109417931e-5),
             static_cast<RealType>(-8.45210544648986348854e-6),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.11634701234079515138e-1),
             static_cast<RealType>(4.39922162828115412952e-1),
@@ -93,7 +97,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.4499e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(8.45396231261375200568e-2),
             static_cast<RealType>(-9.15509628797205847643e-3),
             static_cast<RealType>(1.82052933284907579374e-2),
@@ -105,7 +109,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.73979640146948858436e-7),
             static_cast<RealType>(7.24351142163396584236e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.88099527896838765666e-1),
             static_cast<RealType>(6.53896948546877341992e-1),
@@ -124,7 +128,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.5259e-17
-        static const RealType P[11] = {
+        BOOST_MATH_STATIC const RealType P[11] = {
             static_cast<RealType>(1.36729417918039395222e-2),
             static_cast<RealType>(1.19749117683408419115e-2),
             static_cast<RealType>(6.26780921592414207398e-3),
@@ -137,7 +141,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.55422885338760255125e-11),
             static_cast<RealType>(-4.12196487201928768038e-13),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.61334003864149486454e0),
             static_cast<RealType>(1.28348868912975898501e0),
@@ -156,7 +160,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.5084e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.90649774685568282390e-3),
             static_cast<RealType>(7.43708409389806210196e-4),
             static_cast<RealType>(9.53777347766128955847e-5),
@@ -166,7 +170,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(8.56789906419220801109e-13),
             static_cast<RealType>(-4.17784858891714869163e-15),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.29383849235788831455e-1),
             static_cast<RealType>(2.16287201867831015266e-1),
@@ -183,7 +187,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.4660e-19
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(3.07231582988207590928e-4),
             static_cast<RealType>(5.16108848485823513911e-5),
             static_cast<RealType>(3.05776014220862257678e-6),
@@ -194,7 +198,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(5.11204601013038698192e-18),
             static_cast<RealType>(-9.00826023095223871551e-21),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.28966789835486457746e-1),
             static_cast<RealType>(4.46981634258601621625e-2),
@@ -212,7 +216,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 4.2292e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(5.25741312407933720817e-5),
             static_cast<RealType>(2.34425802342454046697e-6),
             static_cast<RealType>(3.30042747965497652847e-8),
@@ -222,7 +226,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(8.14099948000080417199e-20),
             static_cast<RealType>(-4.61828164399178360925e-23),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.23544974283127158019e-1),
             static_cast<RealType>(6.01210465184576626802e-3),
@@ -239,13 +243,13 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.3004e-17
-        static const RealType P[4] = {
+        BOOST_MATH_STATIC const RealType P[4] = {
             static_cast<RealType>(2.99206710301074508455e-1),
             static_cast<RealType>(-8.62469397757826072306e-1),
             static_cast<RealType>(1.74661995423629075890e-1),
             static_cast<RealType>(8.75909164947413479137e-1),
         };
-        static const RealType Q[3] = {
+        BOOST_MATH_STATIC const RealType Q[3] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(-6.07405848111002255020e0),
             static_cast<RealType>(1.34068401972703571636e1),
@@ -259,7 +263,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -268,7 +272,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 4.5215e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87352751452164445024482162286994868262e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.07622509000285763173795736744991173600e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75004930885780661923539070646503039258e-2),
@@ -284,7 +288,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.18994723428163008965406453309272880204e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.49208308902369087634036371223527932419e-11),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.07053963271862256947338846403373278592e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.30146528469038357598785392812229655811e-1),
@@ -310,7 +314,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.3996e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.02038159607840130388931544845552929992e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85240836242909590376775233472494840074e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92928437142375928121954427888812334305e-2),
@@ -326,7 +330,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.97810512763454658214572490850146305033e-10),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.77430867682132459087084564268263825239e-11),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.30030169049261634787262795838348954434e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.45935676273909940847479638179887855033e-1),
@@ -352,7 +356,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.6834e-35
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.45396231261375200568114750897618690566e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.83107635287140466760500899510899613385e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71690205829238281191309321676655995475e-2),
@@ -371,7 +375,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.85474213475378978699789357283744252832e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.05561259222780127064607109581719435800e-15),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.08902510590064634965634560548380735284e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.60127698266075086782895988567899172787e-1),
@@ -399,7 +403,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 5.6207e-35
         // LCOV_EXCL_START
-        static const RealType P[20] = {
+        BOOST_MATH_STATIC const RealType P[20] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36729417918039395222067998266923903488e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.05780369334958736210688756060527042344e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88449456199223796440901487003885388570e-2),
@@ -421,7 +425,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.89266184062176002518506060373755160893e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.22157263424086267338486564980223658130e-22),
         };
-        static const RealType Q[19] = {
+        BOOST_MATH_STATIC const RealType Q[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.24254809760594824834854946949546737102e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.66740386908805016172202899592418717176e0),
@@ -451,7 +455,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.8882e-35
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90649774685568282389553481307707005425e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70151946710788532273869130544473159961e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76188245008605985768921328976193346788e-3),
@@ -470,7 +474,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62842837946576938669447109511449827857e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33878078951302606409419167741041897986e-26),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.75629880937514507004822969528240262723e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43883005193126748135739157335919076027e0),
@@ -498,7 +502,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 2.7988e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07231582988207590928480356376941073734e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.35574911514921623999866392865480652576e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.60219401814297026945664630716309317015e-5),
@@ -515,7 +519,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.99957357701259203151690416786669242677e-28),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46357124817620384236108395837490629563e-31),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.02259092175256156108200465685980768901e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63438230616954606028022008517920766366e-1),
@@ -541,7 +545,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.9688e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25741312407933720816582583160953651639e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.04434146174674791036848306058526901384e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.68959516304795838166182070164492846877e-7),
@@ -558,7 +562,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70711310565669331853925519429988855964e-34),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.72047006026700174884151916064158941262e-38),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.50985661940624198574968436548711898948e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.81705882167596649186405364717835589894e-2),
@@ -583,7 +587,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 3.0545e-39
         // LCOV_EXCL_START
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99206710301074508454959544950786401357e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.75243304700875633383991614142545185173e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.69652690455351600373808930804785330828e1),
@@ -593,7 +597,7 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.28767698270323629107775935552991333781e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.80591252844738626580182351673066365090e1),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.57593243741246726197476469913307836496e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.99458751269722094414105565700775283458e2),
@@ -611,27 +615,27 @@ inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType>
-inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType, class Policy>
-inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x) {
     //
     // This calculates the pdf of the Holtsmark distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::pdf(holtsmark<%1%>&, %1%)";
+    constexpr auto function = "boost::math::pdf(holtsmark<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -667,7 +671,7 @@ inline RealType holtsmark_pdf_imp(const holtsmark_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -675,7 +679,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.5) {
         // Rational Approximation
         // Maximum Relative Error: 1.3147e-17
-        static const RealType P[6] = {
+        BOOST_MATH_STATIC const RealType P[6] = {
             static_cast<RealType>(5.0e-1),
             static_cast<RealType>(-1.34752580674786639030e-1),
             static_cast<RealType>(1.86318418252163378528e-2),
@@ -683,7 +687,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.60831910014592923855e-3),
             static_cast<RealType>(1.38823662364438342844e-4),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.05200341554753776087e-1),
             static_cast<RealType>(2.12663999430421346175e-1),
@@ -700,7 +704,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.6265e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(3.60595773518728397351e-1),
             static_cast<RealType>(5.75238626843218819756e-1),
             static_cast<RealType>(-3.31245319943021227117e-1),
@@ -709,7 +713,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.08038303148835575624e-3),
             static_cast<RealType>(6.01511310581302829460e-6),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.32264360456739861886e0),
             static_cast<RealType>(6.39715443864749851087e-1),
@@ -726,7 +730,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 7.4398e-20
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.43657975600729535515e-1),
             static_cast<RealType>(-6.02286263626532324632e-2),
             static_cast<RealType>(4.68361231392743283350e-2),
@@ -736,7 +740,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-1.22652173865646814676e-6),
             static_cast<RealType>(2.29521832683440044997e-6),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.82002427359748247121e-1),
             static_cast<RealType>(3.96529686558825119743e-1),
@@ -755,7 +759,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.6148e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(1.05039829654829164883e-1),
             static_cast<RealType>(1.66621813028423002562e-2),
             static_cast<RealType>(2.93820049104275137099e-2),
@@ -766,7 +770,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.12164734714059446913e-7),
             static_cast<RealType>(1.69306881760242775488e-8),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.63461239051296108254e-1),
             static_cast<RealType>(6.54183344973801096611e-1),
@@ -785,7 +789,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.5866e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.05754562114095142887e-2),
             static_cast<RealType>(3.25462617990002726083e-2),
             static_cast<RealType>(1.78205524297204753048e-2),
@@ -795,7 +799,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.94302107205379334662e-6),
             static_cast<RealType>(1.09016076876928010898e-8),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.51164395622515150122e0),
             static_cast<RealType>(1.09391911233213526071e0),
@@ -814,7 +818,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.6575e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(9.47408470248235718880e-3),
             static_cast<RealType>(4.70888722333356024081e-3),
             static_cast<RealType>(8.66397831692913140221e-4),
@@ -824,7 +828,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(8.32182844837952178153e-11),
             static_cast<RealType>(-8.80541360484428526226e-14),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.98261117346347123707e-1),
             static_cast<RealType>(1.97823959738695249267e-1),
@@ -842,7 +846,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.4164e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.19610991747326729867e-3),
             static_cast<RealType>(5.11880074251341162590e-4),
             static_cast<RealType>(2.80704092977662888563e-5),
@@ -852,7 +856,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-9.16761719448360345363e-15),
             static_cast<RealType>(1.20433396121606479712e-17),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.56283944667056551858e-1),
             static_cast<RealType>(2.56811818304462676948e-2),
@@ -869,7 +873,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.2537e-18
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(1.11172037056341397612e-3),
             static_cast<RealType>(7.84545643188695076893e-5),
             static_cast<RealType>(1.94862940242223222641e-6),
@@ -879,7 +883,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-3.18234118727325492149e-17),
             static_cast<RealType>(2.03424457039308806437e-20),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.17861198759233241198e-1),
             static_cast<RealType>(5.45962263583663240699e-3),
@@ -897,13 +901,13 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 4.2897e-18
-        static const RealType P[4] = {
+        BOOST_MATH_STATIC const RealType P[4] = {
             static_cast<RealType>(1.99471140200716338970e-1),
             static_cast<RealType>(-6.90933799347184400422e-1),
             static_cast<RealType>(4.30385245884336871950e-1),
             static_cast<RealType>(3.52790131116013716885e-1),
         };
-        static const RealType Q[3] = {
+        BOOST_MATH_STATIC const RealType Q[3] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(-5.05959751628952574534e0),
             static_cast<RealType>(8.04408113719341786819e0),
@@ -916,7 +920,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -925,7 +929,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 8.6635e-36
        // LCOV_EXCL_START
-        static const RealType P[12] = {
+        BOOST_MATH_STATIC const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.48548242430636907136192799540229598637e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.31541453581608245475805834922621529866e-1),
@@ -939,7 +943,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62777995800923647521692709390412901586e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.63937253747323898965514197114021890186e-8),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.76090180430550757765787254935343576341e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07685236907561593034104428156351640194e-1),
@@ -962,7 +966,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 7.1235e-35
         // LCOV_EXCL_START
-        static const RealType P[12] = {
+        BOOST_MATH_STATIC const RealType P[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.60595773518728397925852903878144761766e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46999595154527091473427440379143006753e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36962313432466566724352608642383560211e-2),
@@ -976,7 +980,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.62800430658278408539398798888955969345e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.22300086876618079439960709120163780513e-8),
         };
-        static const RealType Q[12] = {
+        BOOST_MATH_STATIC const RealType Q[12] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19740977756009966244249035150363085180e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39394884078938560974435920719979860046e-1),
@@ -999,7 +1003,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.7659e-38
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.43657975600729535499895880792984203140e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.37090874182351552816526775008685285108e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70793783828569126853147999925198280654e-2),
@@ -1015,7 +1019,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.53890585580518120552628221662318725825e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.59245311730292556271235324976832000740e-10),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.49800491033591771256676595185869442663e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35827615015880595229881139361463765537e-1),
@@ -1042,7 +1046,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.9091e-35
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05039829654829170780787685299556996311e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28948022754388615368533934448107849329e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.34139151583225691775740839359914493385e-2),
@@ -1061,7 +1065,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40116391931116431686557163556034777896e-12),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.43891156389092896219387988411277617045e-15),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30840297297890638941129884491157396207e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.16059271948787750556465175239345182035e0),
@@ -1089,7 +1093,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 3.2255e-36
         // LCOV_EXCL_START
-        static const RealType P[20] = {
+        BOOST_MATH_STATIC const RealType P[20] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05754562114095147060025732340404111260e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.29082907781747007723015304584383528212e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.15736486393536930535038719804968063752e-2),
@@ -1111,7 +1115,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.95933262363502031836408613043245164787e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.23007623135952181561484264810647517912e-21),
         };
-        static const RealType Q[19] = {
+        BOOST_MATH_STATIC const RealType Q[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.17760389606658547971193065026711073898e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49565543987559264712057768584303008339e0),
@@ -1141,7 +1145,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 2.0174e-36
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47408470248235665279366712356669210597e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32149712567170349164953101675315481096e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.39806230477579028722350422669222849223e-3),
@@ -1160,7 +1164,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.05806999626031246519161395419216393127e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.37645700309533972676063947195650607935e-26),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59608758824065179587008165265773042260e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17347162462484266250945490058846704988e0),
@@ -1187,7 +1191,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 4.5109e-36
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.19610991747326725339429696634365932643e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.74646611039453235739153286141429338461e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.13331430865337412098234177873337036811e-4),
@@ -1205,7 +1209,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.18316957049006338447926554380706108087e-28),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.47298013808154174645356607027685011183e-32),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.42561659771176310412113991024326129105e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.83353398513931409985504410958429204317e-1),
@@ -1231,7 +1235,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.2707e-35
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.11172037056341396583040940446061501972e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.09383362521204903801686281772843962372e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71440982391172647693486692131238237524e-5),
@@ -1248,7 +1252,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.25341184125872354328990441812668510029e-32),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.54663422572657744572284839697818435372e-36),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35632539169215377884393376342532721825e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.46975491055790597767445011183622230556e-2),
@@ -1274,7 +1278,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 5.4677e-35
         // LCOV_EXCL_START
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.48481268366645066801385595379873318648e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.64087860141734943856373451877569284231e1),
@@ -1283,7 +1287,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.63011127597770211743774689830589568544e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.61127812511057623691896118746981066174e0),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90660291309478542795359451748753358123e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.60631500002415936739518466837931659008e2),
@@ -1299,7 +1303,7 @@ inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integr
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
     }
@@ -1307,12 +1311,12 @@ inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const
         return complement ? 1 - holtsmark_cdf_plus_imp_prec(-x, tag) : holtsmark_cdf_plus_imp_prec(-x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
     }
@@ -1320,18 +1324,18 @@ inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const
         return complement ? 1 - holtsmark_cdf_plus_imp_prec(-x, tag) : holtsmark_cdf_plus_imp_prec(-x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
     //
     // This calculates the cdf of the Holtsmark distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::cdf(holtsmark<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(holtsmark<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -1367,7 +1371,7 @@ inline RealType holtsmark_cdf_imp(const holtsmark_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1377,7 +1381,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 5.8068e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(7.59789769759814986929e-1),
             static_cast<RealType>(1.27515008642985381862e0),
             static_cast<RealType>(4.38619247097275579086e-1),
@@ -1387,7 +1391,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-1.36753104188136881229e-3),
             static_cast<RealType>(6.57491277860092595148e-5),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.48696501912062288766e0),
             static_cast<RealType>(2.06239370128871696850e0),
@@ -1406,7 +1410,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 1.0339e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.84521387984759064238e-1),
             static_cast<RealType>(4.15763727809667641126e-1),
             static_cast<RealType>(-1.73610240124046440578e-2),
@@ -1416,7 +1420,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-3.11382403581073580481e-4),
             static_cast<RealType>(3.93093062843177374871e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.76193897442484823754e-1),
             static_cast<RealType>(3.70953499602257825764e-2),
@@ -1433,7 +1437,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 1.4431e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(4.46943301497773314460e-1),
             static_cast<RealType>(-1.07267614417424412546e-2),
             static_cast<RealType>(-7.21097021064631831756e-2),
@@ -1443,7 +1447,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(2.95410432808739478857e-4),
             static_cast<RealType>(-2.88688017391292485867e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(-2.72809429017073648893e-2),
             static_cast<RealType>(-7.85526213469762960803e-2),
@@ -1460,7 +1464,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.8871e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(4.25344469980677332786e-1),
             static_cast<RealType>(3.42055470008289997369e-2),
             static_cast<RealType>(9.33607217644370441642e-2),
@@ -1472,7 +1476,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(6.98960839033991110525e-5),
             static_cast<RealType>(9.66690587477825432174e-6),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.60044610004497775009e-1),
             static_cast<RealType>(2.41675490962065446592e-1),
@@ -1492,7 +1496,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.8173e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(3.68520435599726877886e-1),
             static_cast<RealType>(8.26682725061327242371e-1),
             static_cast<RealType>(6.85235826889543887309e-1),
@@ -1503,7 +1507,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(9.78919203915954346945e-5),
             static_cast<RealType>(9.71371309261213597491e-8),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.29132755303753682133e0),
             static_cast<RealType>(1.95530118226232968288e0),
@@ -1521,7 +1525,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 6.0376e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(3.48432718168951419458e-1),
             static_cast<RealType>(2.99680703419193973028e-1),
             static_cast<RealType>(1.09531896991852433149e-1),
@@ -1533,7 +1537,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(3.08821091232356755783e-8),
             static_cast<RealType>(5.58003465656339818416e-10),
         };
-        static const RealType Q[10] = {
+        BOOST_MATH_STATIC const RealType Q[10] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.73938978582311007855e-1),
             static_cast<RealType>(3.21771888210250878162e-1),
@@ -1553,7 +1557,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 2.2804e-17
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(3.41419813138786920868e-1),
             static_cast<RealType>(1.30219412019722274099e-1),
             static_cast<RealType>(2.36047671342109636195e-2),
@@ -1565,7 +1569,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(2.25766283556816829070e-10),
             static_cast<RealType>(-8.46510608386806647654e-18),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.81461950831351846380e-1),
             static_cast<RealType>(6.91390438866520696447e-2),
@@ -1584,7 +1588,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.8545e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(3.41392032051575965049e-1),
             static_cast<RealType>(1.53372256183388434238e-1),
             static_cast<RealType>(3.33822240038718319714e-2),
@@ -1595,7 +1599,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(7.40424342670289242177e-8),
             static_cast<RealType>(4.61294046336533026640e-9),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.49255524669251621744e-1),
             static_cast<RealType>(9.77826688966262423974e-2),
@@ -1621,7 +1625,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             result = 1 / (cbrt(p) * cbrt(p) * c);
         }
         else {
-            result = std::numeric_limits<RealType>::infinity();
+            result = boost::math::numeric_limits<RealType>::infinity();
         }
     }
 
@@ -1630,7 +1634,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 
 
 template <class RealType>
-inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1642,7 +1646,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 1.7987e-35
            // LCOV_EXCL_START
-            static const RealType P[14] = {
+            BOOST_MATH_STATIC const RealType P[14] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.59789769759815031687162026655576575384e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.23247138049619855169890925442523844619e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.35351935489348780511227763760731136136e0),
@@ -1658,7 +1662,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.39406616773257816628641556843884616119e-6),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54871597065387376666252643921309051097e-7),
             };
-            static const RealType Q[13] = {
+            BOOST_MATH_STATIC const RealType Q[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.06310038178166385607814371094968073940e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06144046990424238286303107360481469219e1),
@@ -1682,7 +1686,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 2.5554e-35
             // LCOV_EXCL_START
-            static const RealType P[13] = {
+            BOOST_MATH_STATIC const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.63490994331899195346399558699533994243e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.68682839419340144322747963938810505658e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.63089084712442063245295709191126453412e-1),
@@ -1697,7 +1701,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.52830681121195099547078704713089681353e-7),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91383571211375811878311159248551586411e-8),
             };
-            static const RealType Q[12] = {
+            BOOST_MATH_STATIC const RealType Q[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96820655322136936855997114940653763917e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.30209571878469737819039455443404070107e0),
@@ -1722,7 +1726,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 1.0297e-35
             // LCOV_EXCL_START
-            static const RealType P[12] = {
+            BOOST_MATH_STATIC const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.84521387984759060262188972210005114936e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.70837834325236202821328032137877091515e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.53856963029219911450181095566096563059e-1),
@@ -1736,7 +1740,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.02908228738160003274584644834000176496e-6),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.05702214080592377840761032481067834813e-7),
             };
-            static const RealType Q[12] = {
+            BOOST_MATH_STATIC const RealType Q[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33954869248363301881659953529609341564e0),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.73738626674455393272550888585363920917e-1),
@@ -1759,7 +1763,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 1.3688e-35
             // LCOV_EXCL_START
-            static const RealType P[12] = {
+            BOOST_MATH_STATIC const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34418795581931891732555950599385666106e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.13006013029934051875748102515422669897e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.27990072710518465265454549585803147529e-2),
@@ -1773,7 +1777,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23649928279010039670034778778065846828e-6),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.99636080473697209793683863161785312159e-8),
             };
-            static const RealType Q[12] = {
+            BOOST_MATH_STATIC const RealType Q[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.95056572065373808001002483348789719155e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -7.55702988004729812458415992666809422570e-2),
@@ -1797,7 +1801,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 6.6020e-36
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46943301497773318715008398224877079279e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.85403413700924949902626248891615772650e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.02791895890363892816315784780533893399e-1),
@@ -1814,7 +1818,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.64549285026064221742294542922996905241e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72723306533295983872420985773212608299e-9),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.23756826160440280076231428938184359865e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.46557011055563840763437682311082689407e-1),
@@ -1841,7 +1845,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 5.0596e-35
             // LCOV_EXCL_START
-            static const RealType P[12] = {
+            BOOST_MATH_STATIC const RealType P[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.25344469980677353573160570139298422046e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.41915371584999983192100443156935649063e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.02829239548689190780023994008688591230e-1),
@@ -1855,7 +1859,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.57770758189194396236862269776507019313e-7),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.29311341249565125992213260043135188072e-8),
             };
-            static const RealType Q[12] = {
+            BOOST_MATH_STATIC const RealType Q[12] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.54021943144355190773797361537886598583e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30965787836836308380896385568728211303e-1),
@@ -1878,7 +1882,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 8.3743e-35
             // LCOV_EXCL_START
-            static const RealType P[13] = {
+            BOOST_MATH_STATIC const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08071367192424306005939751362206079160e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.94625900993512461462097316785202943274e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55970241156822104458842450713854737857e-1),
@@ -1893,7 +1897,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.90495731447121207951661931979310025968e-7),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.23210708203609461650368387780135568863e-8),
             };
-            static const RealType Q[11] = {
+            BOOST_MATH_STATIC const RealType Q[11] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.93402256203255215539822867473993726421e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.42452702043886045884356307934634512995e-1),
@@ -1916,7 +1920,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 2.4734e-35
         // LCOV_EXCL_START
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.92042979500197776619414802317216082414e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.94742044285563829335663810275331541585e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14525306632578654372860377652983462776e-1),
@@ -1934,7 +1938,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72119240610740992234979508242967886200e-8),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17836139198065889244530078295061548097e-10),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.78065342260594920160228973261455037923e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.08575070304822733863613657779515344137e-1),
@@ -1960,7 +1964,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 1.1570e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.68520435599726860132888599110871216319e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.01076105507184082206031922185510102322e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39912455237662038937400667644545834191e0),
@@ -1980,7 +1984,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.61400097324698003962179537436043636306e-9),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.88084230973635340409728710734906398080e-11),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.49319798750825059930589954921919984293e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.90218243410186000622818205955425584848e0),
@@ -2009,7 +2013,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 1.1362e-35
         // LCOV_EXCL_START
-        static const RealType P[22] = {
+        BOOST_MATH_STATIC const RealType P[22] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48432718168951398420402661878962745094e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.55946442453078865766668586202885528338e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.54912640113904816247923987542554486059e-1),
@@ -2033,7 +2037,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.01916800572423194619358228507804954863e-20),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72241483171311778625855302356391965266e-26),
         };
-        static const RealType Q[21] = {
+        BOOST_MATH_STATIC const RealType Q[21] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18341916009800042837726003154518652168e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19215655980509256344434487727207541208e0),
@@ -2065,7 +2069,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 9.1729e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41419813138786928653984591611599949126e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.94225020281693988785012368481961427155e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.28967134188573605597955859185818311256e-2),
@@ -2086,7 +2090,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.85122374200561402546731933480737679849e-30),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.79744248200459077556218062241428072826e-32),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.68930884381361438749954611436694811868e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.54944129151720429074748655153760118465e-1),
@@ -2114,7 +2118,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 1.8330e-35
         // LCOV_EXCL_START
-        static const RealType P[19] = {
+        BOOST_MATH_STATIC const RealType P[19] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392032051575981622151194498090952488e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.32651097995974052731414709779952524875e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.51927763729719814565225981452897995722e-2),
@@ -2135,7 +2139,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.07829060832934383885234817363480653925e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21485411177823993142696645934560017341e-40),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.88559444380290379529260819350179144435e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.37942717465159991856146428659881557553e-2),
@@ -2164,7 +2168,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 5.9085e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.41392031627647840832213878541731833340e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.48256908849985263191468999842405689327e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.16515822909144946601084169745484248278e-2),
@@ -2184,7 +2188,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05630817682870951728748696694117980745e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.13881361534205323565985756195674181203e-50),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239599863811873205236246e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849060586077266046297964e-2),
@@ -2218,7 +2222,7 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
             result = 1 / (cbrt(p) * cbrt(p) * c);
         }
         else {
-            result = std::numeric_limits<RealType>::infinity();
+            result = boost::math::numeric_limits<RealType>::infinity();
         }
     }
 
@@ -2226,32 +2230,32 @@ inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::
 }
 
 template <class RealType>
-inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
-        return holtsmark_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? holtsmark_quantile_upper_imp_prec(1 - p, tag) : -holtsmark_quantile_upper_imp_prec(1 - p, tag);
     }
 
     return complement ? holtsmark_quantile_upper_imp_prec(p, tag) : -holtsmark_quantile_upper_imp_prec(p, tag);
 }
 
 template <class RealType>
-inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
-        return holtsmark_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? holtsmark_quantile_upper_imp_prec(1 - p, tag) : -holtsmark_quantile_upper_imp_prec(1 - p, tag);
     }
 
     return complement ? holtsmark_quantile_upper_imp_prec(p, tag) : -holtsmark_quantile_upper_imp_prec(p, tag);
 }
 
 template <class RealType, class Policy>
-inline RealType holtsmark_quantile_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
 {
     // This routine implements the quantile for the Holtsmark distribution,
     // the value p may be the probability, or its complement if complement=true.
 
-    static const char* function = "boost::math::quantile(holtsmark<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(holtsmark<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -2287,23 +2291,23 @@ inline RealType holtsmark_quantile_imp(const holtsmark_distribution<RealType, Po
 }
 
 template <class RealType>
-inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.06944850513462440032);
 }
 
 template <class RealType>
-inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0694485051346244003155800384542166381);
 }
 
 template <class RealType, class Policy>
-inline RealType holtsmark_entropy_imp(const holtsmark_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp(const holtsmark_distribution<RealType, Policy>& dist)
 {
     // This implements the entropy for the Holtsmark distribution,
 
-    static const char* function = "boost::math::entropy(holtsmark<%1%>&, %1%)";
+    constexpr auto function = "boost::math::entropy(holtsmark<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -2338,20 +2342,20 @@ class holtsmark_distribution
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    holtsmark_distribution(RealType l_location = 0, RealType l_scale = 1)
+    BOOST_MATH_GPU_ENABLED holtsmark_distribution(RealType l_location = 0, RealType l_scale = 1)
         : mu(l_location), c(l_scale)
     {
-        static const char* function = "boost::math::holtsmark_distribution<%1%>::holtsmark_distribution";
+        constexpr auto function = "boost::math::holtsmark_distribution<%1%>::holtsmark_distribution";
         RealType result = 0;
         detail::check_location(function, l_location, &result, Policy());
         detail::check_scale(function, l_scale, &result, Policy());
     } // holtsmark_distribution
 
-    RealType location()const
+    BOOST_MATH_GPU_ENABLED RealType location()const
     {
         return mu;
     }
-    RealType scale()const
+    BOOST_MATH_GPU_ENABLED RealType scale()const
     {
         return c;
     }
@@ -2371,90 +2375,90 @@ holtsmark_distribution(RealType, RealType) -> holtsmark_distribution<typename bo
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const holtsmark_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const holtsmark_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const holtsmark_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const holtsmark_distribution<RealType, Policy>&)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::holtsmark_pdf_imp(dist, x);
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const holtsmark_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::holtsmark_cdf_imp(dist, x, false);
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const holtsmark_distribution<RealType, Policy>& dist, const RealType& p)
 {
     return detail::holtsmark_quantile_imp(dist, p, false);
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::holtsmark_cdf_imp(c.dist, c.param, true);
 } //  cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<holtsmark_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::holtsmark_quantile_imp(c.dist, c.param, true);
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const holtsmark_distribution<RealType, Policy> &dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const holtsmark_distribution<RealType, Policy> &dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const holtsmark_distribution<RealType, Policy>& /*dist*/)
 {
-    return std::numeric_limits<RealType>::infinity();
+    return boost::math::numeric_limits<RealType>::infinity();
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const holtsmark_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const holtsmark_distribution<RealType, Policy>& dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const holtsmark_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const holtsmark_distribution<RealType, Policy>& dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const holtsmark_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2464,11 +2468,11 @@ inline RealType skewness(const holtsmark_distribution<RealType, Policy>& /*dist*
         "boost::math::skewness(holtsmark<%1%>&)",
         "The Holtsmark distribution does not have a skewness: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const holtsmark_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2478,11 +2482,11 @@ inline RealType kurtosis(const holtsmark_distribution<RealType, Policy>& /*dist*
         "boost::math::kurtosis(holtsmark<%1%>&)",
         "The Holtsmark distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const holtsmark_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const holtsmark_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2492,11 +2496,11 @@ inline RealType kurtosis_excess(const holtsmark_distribution<RealType, Policy>&
         "boost::math::kurtosis_excess(holtsmark<%1%>&)",
         "The Holtsmark distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const holtsmark_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const holtsmark_distribution<RealType, Policy>& dist)
 {
     return detail::holtsmark_entropy_imp(dist);
 }

From 1d7d373bd96e0ffb94408f80f84c194caeecd0f0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:46:30 -0400
Subject: [PATCH 161/399] Fix static local variable

---
 include/boost/math/distributions/holtsmark.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index 8041cf8cf7..8c976b8c82 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -1614,7 +1614,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const R
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else {
-        const static RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
+        const BOOST_MATH_STATIC_LOCAL_VARIABLE RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
 
         RealType p_square = p * p;
 
@@ -2211,7 +2211,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const R
         result = tools::evaluate_polynomial(P, t) / (tools::evaluate_polynomial(Q, t) * cbrt(p * p));
     }
     else {
-        const static RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
+        const BOOST_MATH_STATIC_LOCAL_VARIABLE RealType c = ldexp(cbrt(constants::pi<RealType>()), 1);
 
         RealType p_square = p * p;
 

From 3036b4f12f830813a6995a6a49df752613ab6734 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:46:35 -0400
Subject: [PATCH 162/399] Add CUDA testing to holtsmark dist

---
 test/cuda_jamfile                 |   4 ++
 test/test_holtsmark_cdf_double.cu | 110 ++++++++++++++++++++++++++++++
 test/test_holtsmark_cdf_float.cu  | 110 ++++++++++++++++++++++++++++++
 test/test_holtsmark_pdf_double.cu | 110 ++++++++++++++++++++++++++++++
 test/test_holtsmark_pdf_float.cu  | 110 ++++++++++++++++++++++++++++++
 5 files changed, 444 insertions(+)
 create mode 100644 test/test_holtsmark_cdf_double.cu
 create mode 100644 test/test_holtsmark_cdf_float.cu
 create mode 100644 test/test_holtsmark_pdf_double.cu
 create mode 100644 test/test_holtsmark_pdf_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index ba7f8d153c..62dcbe6f00 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -46,6 +46,10 @@ run test_exponential_quan_double.cu ;
 run test_exponential_quan_float.cu ;
 run test_exponential_range_support_double.cu ;
 run test_exponential_range_support_float.cu ;
+run test_holtsmark_cdf_double.cu ;
+run test_holtsmark_cdf_float.cu ;
+run test_holtsmark_pdf_double.cu ;
+run test_holtsmark_pdf_float.cu ;
 run test_landau_cdf_double.cu ;
 run test_landau_cdf_float.cu ;
 run test_landau_pdf_double.cu ;
diff --git a/test/test_holtsmark_cdf_double.cu b/test/test_holtsmark_cdf_double.cu
new file mode 100644
index 0000000000..5a02b7ddb5
--- /dev/null
+++ b/test/test_holtsmark_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::holtsmark_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_holtsmark_cdf_float.cu b/test/test_holtsmark_cdf_float.cu
new file mode 100644
index 0000000000..71ae21f731
--- /dev/null
+++ b/test/test_holtsmark_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::holtsmark_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_holtsmark_pdf_double.cu b/test/test_holtsmark_pdf_double.cu
new file mode 100644
index 0000000000..b883515a76
--- /dev/null
+++ b/test/test_holtsmark_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::holtsmark_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_holtsmark_pdf_float.cu b/test/test_holtsmark_pdf_float.cu
new file mode 100644
index 0000000000..c568159739
--- /dev/null
+++ b/test/test_holtsmark_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::holtsmark_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From c02d5d64e03ce38a700d8d6c4f9f538d7c84572c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 11:50:46 -0400
Subject: [PATCH 163/399] Add SYCL testing for holtsmark dist

---
 test/sycl_jamfile       |  1 +
 test/test_holtsmark.cpp | 23 +++++++++++++++++++++--
 2 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 9ea1095cd4..095babcc29 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -14,6 +14,7 @@ run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
 run test_exponential_dist.cpp ;
+run test_holtsmark.cpp ;
 run test_landau.cpp ;
 run test_mapairy.cpp ;
 
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index 35307ef6af..6aa3577868 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -1,13 +1,14 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
 #define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsHoltsmarkTest
+#include <boost/math/tools/config.hpp>
 #include <boost/test/included/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
-#include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/holtsmark.hpp>
 
@@ -16,7 +17,11 @@
 #endif
 
 using boost::math::holtsmark_distribution;
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#include <boost/multiprecision/cpp_bin_float.hpp>
 using boost::multiprecision::cpp_bin_float_quad;
+#endif
 
 template<class RealType, int N>
 void do_test_holtsmark_pdf(){
@@ -782,10 +787,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_pdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_pdf_fp128)
 {
     do_test_holtsmark_pdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp64)
 {
@@ -799,10 +806,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_cdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_cdf_fp128)
 {
     do_test_holtsmark_cdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp64)
 {
@@ -816,10 +825,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_ccdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_ccdf_fp128)
 {
     do_test_holtsmark_ccdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp64)
 {
@@ -833,10 +844,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_nearzero_fp128)
 {
     do_test_holtsmark_quantile_nearzero<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp64)
 {
@@ -850,10 +863,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_lower_fp128)
 {
     do_test_holtsmark_quantile_lower<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp64)
 {
@@ -867,10 +882,12 @@ BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_quantile_upper_fp128)
 {
     do_test_holtsmark_quantile_upper<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp64)
 {
@@ -884,7 +901,9 @@ BOOST_AUTO_TEST_CASE(holtsmark_locscale_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(holtsmark_locscale_fp128)
 {
     do_test_holtsmark_locscale_param<cpp_bin_float_quad, 113>();
 }
+#endif

From 09d0eb8ee1a3829c3c98944d1767dcce4c2ff4a4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 12:02:42 -0400
Subject: [PATCH 164/399] Add GPU support to saspoint5 dist

---
 .../boost/math/distributions/saspoint5.hpp    | 362 +++++++++---------
 1 file changed, 183 insertions(+), 179 deletions(-)

diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
index f21f52d9a2..fd9ff6f13b 100644
--- a/include/boost/math/distributions/saspoint5.hpp
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -1,4 +1,5 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,6 +12,9 @@
 #pragma warning(disable : 4127) // conditional expression is constant
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -28,7 +32,7 @@ class saspoint5_distribution;
 namespace detail {
 
 template <class RealType>
-inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -36,7 +40,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.125) {
         // Rational Approximation
         // Maximum Relative Error: 7.8747e-17
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             static_cast<RealType>(6.36619772367581343076e-1),
             static_cast<RealType>(2.17275699713513462507e2),
             static_cast<RealType>(3.49063163361344578910e4),
@@ -51,7 +55,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.85883041942144306222e15),
             static_cast<RealType>(4.19828222275972713819e14),
         };
-        static const RealType Q[15] = {
+        BOOST_MATH_STATIC const RealType Q[15] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.41295871011779138155e2),
             static_cast<RealType>(5.48907134827349102297e4),
@@ -76,7 +80,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.1471e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(4.35668401768623200524e-1),
             static_cast<RealType>(7.12477357389655327116e0),
             static_cast<RealType>(4.02466317948738993787e1),
@@ -85,7 +89,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.26950253999694502457e1),
             static_cast<RealType>(-6.59304802132933325219e-1),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.98623818041545101115e1),
             static_cast<RealType>(1.52856383017632616759e2),
@@ -102,7 +106,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.3265e-17
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(2.95645445681747568732e-1),
             static_cast<RealType>(2.23779537590791610124e0),
             static_cast<RealType>(5.01302198171248036052e0),
@@ -112,7 +116,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(-7.53979800555375661516e-3),
             static_cast<RealType>(1.37294648777729527395e-3),
         };
-        static const RealType Q[6] = {
+        BOOST_MATH_STATIC const RealType Q[6] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.02879626214781666701e1),
             static_cast<RealType>(3.85125274509784615691e1),
@@ -128,7 +132,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.7947e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.70762401725206223811e-1),
             static_cast<RealType>(8.43343631021918972436e-1),
             static_cast<RealType>(1.39703819152564365627e0),
@@ -137,7 +141,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(7.35858280181579907616e-3),
             static_cast<RealType>(-1.03693607694266081126e-4),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.73363440952557318819e0),
             static_cast<RealType>(1.74288966619209299976e1),
@@ -154,7 +158,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 1.7051e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(8.61071469126041183247e-2),
             static_cast<RealType>(1.69689585946245345838e-1),
             static_cast<RealType>(1.09494833291892212033e-1),
@@ -163,7 +167,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(4.09853605772288438003e-5),
             static_cast<RealType>(-2.63561415158954865283e-7),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.04082856018856244947e0),
             static_cast<RealType>(3.52558663323956252986e0),
@@ -180,7 +184,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.9247e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(3.91428580496513429479e-2),
             static_cast<RealType>(4.07162484034780126757e-2),
             static_cast<RealType>(1.43342733342753081931e-2),
@@ -189,7 +193,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(9.51545046750892356441e-7),
             static_cast<RealType>(-3.56598940936439037087e-9),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.63904431617187026619e0),
             static_cast<RealType>(1.03812003196677309121e0),
@@ -206,7 +210,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.6547e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.65057384221262866484e-2),
             static_cast<RealType>(8.05429762031495873704e-3),
             static_cast<RealType>(1.35249234647852784985e-3),
@@ -215,7 +219,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.03176916111395079569e-8),
             static_cast<RealType>(-1.94913182592441292094e-11),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.10113554189626079232e-1),
             static_cast<RealType>(2.54175325409968367580e-1),
@@ -232,7 +236,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.5484e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(6.60044810497290557553e-3),
             static_cast<RealType>(1.59342644994950292031e-3),
             static_cast<RealType>(1.32429706922966110874e-4),
@@ -241,7 +245,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.22293787679910067873e-10),
             static_cast<RealType>(-1.16300443044165216564e-13),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.10446485803039594111e-1),
             static_cast<RealType>(6.51887342399859289520e-2),
@@ -258,7 +262,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.9866e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.54339461777955741686e-3),
             static_cast<RealType>(3.10069525357852579756e-4),
             static_cast<RealType>(1.30082682796085732756e-5),
@@ -267,7 +271,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.53505360463827994365e-12),
             static_cast<RealType>(-7.42649416356965421308e-16),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.09203384450859785642e-1),
             static_cast<RealType>(1.69422626897631306130e-2),
@@ -284,7 +288,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.3581e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(9.55085695067883584460e-4),
             static_cast<RealType>(5.86125496733202756668e-5),
             static_cast<RealType>(1.23753971325810931282e-6),
@@ -293,7 +297,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.85366144680157942079e-14),
             static_cast<RealType>(-4.53975807317403152058e-18),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.05980850386474826374e-1),
             static_cast<RealType>(4.34966042652000070674e-3),
@@ -310,14 +314,14 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 4.7450e-19
-        static const RealType P[5] = {
+        BOOST_MATH_STATIC const RealType P[5] = {
             static_cast<RealType>(1.99471140200716338970e-1),
             static_cast<RealType>(-1.93310094131437487158e-2),
             static_cast<RealType>(-8.44282614309073196195e-3),
             static_cast<RealType>(3.47296024282356038069e-3),
             static_cast<RealType>(-4.05398011689821941383e-4),
         };
-        static const RealType Q[5] = {
+        BOOST_MATH_STATIC const RealType Q[5] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(7.00973251258577238892e-1),
             static_cast<RealType>(2.66969681258835723157e-1),
@@ -333,7 +337,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -342,7 +346,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 8.8841e-35
         // LCOV_EXCL_START
-        static const RealType P[27] = {
+        BOOST_MATH_STATIC const RealType P[27] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.36619772367581343075535053490057448138e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.57459506929453385798277946154823008327e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.46717322844023441698710451505816706570e5),
@@ -371,7 +375,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.48064966533519934186356663849904556319e36),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.64877082086372991309408001661535573441e35),
         };
-        static const RealType Q[28] = {
+        BOOST_MATH_STATIC const RealType Q[28] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18981461118065892086304195732751798634e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.01761929839041982958990681130944341399e5),
@@ -410,7 +414,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 3.4585e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.46416716200748206779925127900698754119e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.41771273526123373239570033672829787791e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56142610225585235535211648703534340871e3),
@@ -426,7 +430,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.88896160275915786487519266368539625326e5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05543800791717482823610940401201712196e4),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.44407579416524903840331499438398472639e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15911780811299460009161345260146251462e3),
@@ -450,7 +454,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.9278e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35668401768623200524372663239480799018e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.30066509937988171489091367354416214000e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.05924026744937322690717755156090122074e2),
@@ -466,7 +470,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.32201781975497810173532067354797097401e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.96874547436310030183519174847668703774e0),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.63164311578114868477819520857286165076e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.34964379844144961683927306966955217328e3),
@@ -490,7 +494,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.9378e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95645445681747568731488283573032414811e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.83246437763964151893665752064650172391e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.85333417559435252576820440080930004674e1),
@@ -506,7 +510,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54064889901609722583601330171719819660e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.72254289950537680833853394958874977464e-3),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.58291085070053442257438623486099473087e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95618461039379226195473938654286975682e2),
@@ -531,7 +535,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.4363e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70762401725206223811383500786268939645e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.19353011456197635663058525904929358535e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22974648900600015961253465796487372402e1),
@@ -547,7 +551,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.07739227340181463034286653569468171767e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.02669738424010290973023004028523684766e-7),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46404480283267324138113869370306506431e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.54550184643308468933661600211579108422e1),
@@ -572,7 +576,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.1244e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.61071469126041183247373313827161939454e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.35837460186564880289965856498718321896e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.47783071967681246738651796742079530382e-1),
@@ -587,7 +591,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.09089653391032945883918434200567278139e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21403900721572475664926557233205232491e-10),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.13172035933794917563324458011617112124e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65687100738157412154132860910003018338e1),
@@ -612,7 +616,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 8.1110e-35
         // LCOV_EXCL_START
-        static const RealType P[13] = {
+        BOOST_MATH_STATIC const RealType P[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.91428580496513429479068747515164587814e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.69015019070193436467106672180804948494e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.03147451266231819912643754579290008651e-1),
@@ -627,7 +631,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.06637401794693307359898089790558771957e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.08663671047376684678494625068451888284e-14),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.07443397096591141329212291707948432414e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.16665031056584124503224711639009530348e0),
@@ -652,7 +656,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 2.5228e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.65057384221262866484014802392420311075e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.92801687242885330588201777283015178448e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.65508815862861196424333614846876229064e-3),
@@ -668,7 +672,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -6.39396206221935864416563232680283312796e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.37760675743046300528308203869876086823e-22),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49023284463742780238035958819642738891e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.76284367953836866133894756472541395734e-1),
@@ -692,7 +696,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.6732e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.60044810497290557552736366450372523266e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27034183360438185616541260923634443241e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.19813403884333707962156711479716066536e-3),
@@ -708,7 +712,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.95046217952146113063614290717113024410e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.46784746963816915795587433372284530785e-25),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.16012189991825507132967712656930682478e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.95202772611563835130347051925062280272e-1),
@@ -733,7 +737,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.0113e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.54339461777955741686401041938275102207e-3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.17747085249877439037826121862689145081e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.14104576580586095462211756659036062930e-4),
@@ -749,7 +753,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.76883960167449461476228984331517762578e-25),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.03558202009465610972808653993060437679e-29),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.08809672969012756295937194823378109391e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.41148083436617376855422685448827300528e-2),
@@ -774,7 +778,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.7056e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.55085695067883584460317653567009454037e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.52919532248638251721278667010429548877e-4),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.06266842295477991789450356745903177571e-5),
@@ -790,7 +794,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.55238112862817593053765898004447484717e-29),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -8.93970406521541790658675747195982964585e-34),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04722757068068234153968603374387493579e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.85854131835804458353300285777969427206e-2),
@@ -815,7 +819,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 7.1032e-36
         // LCOV_EXCL_START
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99471140200716338969973029967190934238e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82846732476244747063962056024672844211e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -3.69724475658159099827638225237895868258e-3),
@@ -825,7 +829,7 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.72986150007117100707304201395140411630e-6),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -2.53567129749337040254350979652515879881e-7),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.89815449697874475254942178935516387239e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.21223228867921988134838870379132038419e-1),
@@ -845,27 +849,27 @@ inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType>
-inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType, class Policy>
-inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x) {
     //
     // This calculates the pdf of the Saspoint5 distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::pdf(saspoint5<%1%>&, %1%)";
+    constexpr auto function = "boost::math::pdf(saspoint5<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -901,7 +905,7 @@ inline RealType saspoint5_pdf_imp(const saspoint5_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -909,7 +913,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
     if (x < 0.5) {
         // Rational Approximation
         // Maximum Relative Error: 2.6225e-17
-        static const RealType P[16] = {
+        BOOST_MATH_STATIC const RealType P[16] = {
             static_cast<RealType>(5.0e-1),
             static_cast<RealType>(1.11530082549581486148e2),
             static_cast<RealType>(1.18564167533523512811e4),
@@ -927,7 +931,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.36220966258718212359e11),
             static_cast<RealType>(1.70766655065405022702e9),
         };
-        static const RealType Q[16] = {
+        BOOST_MATH_STATIC const RealType Q[16] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.24333404643898143947e2),
             static_cast<RealType>(2.39984636687021023600e4),
@@ -953,7 +957,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 9.2135e-19
-        static const RealType P[8] = {
+        BOOST_MATH_STATIC const RealType P[8] = {
             static_cast<RealType>(3.31309550000758082456e-1),
             static_cast<RealType>(1.63012162307622129396e0),
             static_cast<RealType>(2.97763161467248770571e0),
@@ -963,7 +967,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(4.00812864075652334798e-3),
             static_cast<RealType>(-4.82051978765960490940e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(5.43565383128046471592e0),
             static_cast<RealType>(1.13265160672130133152e1),
@@ -980,7 +984,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.4688e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.71280312689343248819e-1),
             static_cast<RealType>(7.44610837974139249205e-1),
             static_cast<RealType>(7.17844128359406982825e-1),
@@ -989,7 +993,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(3.06447984437786430265e-3),
             static_cast<RealType>(2.60407071021044908690e-5),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.06221257507188300824e0),
             static_cast<RealType>(3.44827372231472308047e0),
@@ -1006,7 +1010,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 8.2289e-18
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(2.13928162275383716645e-1),
             static_cast<RealType>(2.35139109235828185307e-1),
             static_cast<RealType>(9.35967515134932733243e-2),
@@ -1015,7 +1019,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(3.13500969261032539402e-5),
             static_cast<RealType>(1.17021346758965979212e-7),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.28212183177829510267e0),
             static_cast<RealType>(6.17321009406850420793e-1),
@@ -1032,7 +1036,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 3.7284e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.63772802979087193656e-1),
             static_cast<RealType>(9.69009603942214234119e-2),
             static_cast<RealType>(2.08261725719828138744e-2),
@@ -1041,7 +1045,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.11401971145777879684e-6),
             static_cast<RealType>(2.25932082770588727842e-9),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.92463563872865541733e-1),
             static_cast<RealType>(1.80720987166755982366e-1),
@@ -1058,7 +1062,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 4.9609e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(1.22610122564874280532e-1),
             static_cast<RealType>(3.70273222121572231593e-2),
             static_cast<RealType>(4.06083618461789591121e-3),
@@ -1067,7 +1071,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(2.87707419853226244584e-8),
             static_cast<RealType>(2.96850126180387702894e-11),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.55825191301363023576e-1),
             static_cast<RealType>(4.77251766176046719729e-2),
@@ -1084,7 +1088,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 5.6559e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(9.03056141356415077080e-2),
             static_cast<RealType>(1.37568904417652631821e-2),
             static_cast<RealType>(7.60947271383247418831e-4),
@@ -1093,7 +1097,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(6.90524093915996283104e-10),
             static_cast<RealType>(3.58808434477817122371e-13),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(1.80501347735272292079e-1),
             static_cast<RealType>(1.22807958286146936376e-2),
@@ -1110,7 +1114,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 6.0653e-17
-        static const RealType P[7] = {
+        BOOST_MATH_STATIC const RealType P[7] = {
             static_cast<RealType>(6.57333571766941474226e-2),
             static_cast<RealType>(5.02795551798163084224e-3),
             static_cast<RealType>(1.39633616037997111325e-4),
@@ -1119,7 +1123,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             static_cast<RealType>(1.60229460572297160486e-11),
             static_cast<RealType>(4.17711709622960498456e-15),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(9.10198637347368265508e-2),
             static_cast<RealType>(3.12263472357578263712e-3),
@@ -1136,14 +1140,14 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
         // Rational Approximation
         // Maximum Relative Error: 2.0104e-20
-        static const RealType P[5] = {
+        BOOST_MATH_STATIC const RealType P[5] = {
             static_cast<RealType>(3.98942280401432677940e-1),
             static_cast<RealType>(8.12222388783621449146e-2),
             static_cast<RealType>(1.68515703707271703934e-2),
             static_cast<RealType>(2.19801627205374824460e-3),
             static_cast<RealType>(-5.63321705854968264807e-5),
         };
-        static const RealType Q[5] = {
+        BOOST_MATH_STATIC const RealType Q[5] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(6.02536240902768558315e-1),
             static_cast<RealType>(1.99284471400121092380e-1),
@@ -1159,7 +1163,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 
 
 template <class RealType>
-inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1168,7 +1172,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 6.9340e-35
         // LCOV_EXCL_START
-        static const RealType P[30] = {
+        BOOST_MATH_STATIC const RealType P[30] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.0e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.25520067710293108163697513129883130648e2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.70866020657515874782126804139443323023e5),
@@ -1200,7 +1204,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.71625432346533320597285660433110657670e35),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.54662474187354179772157464533408058525e33),
         };
-        static const RealType Q[31] = {
+        BOOST_MATH_STATIC const RealType Q[31] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.05231337496532137901354609636674085703e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.43071888317491317900094470796567113997e5),
@@ -1242,7 +1246,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.6106e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.31887921568009055676985827521151969069e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62791448964529380666250180886203090183e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18238045199893937316918299064825702894e2),
@@ -1258,7 +1262,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.27181379647139697258984772894869505788e3),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.73617450590346508706222885401965820190e1),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.18558935411552146390814444666395959919e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49210559503096368944407109881023223654e3),
@@ -1282,7 +1286,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 3.1519e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.87119665000174806422420129219814467874e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.60769554551148293079169764245570645155e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.49181979810834706538329284478129952168e1),
@@ -1298,7 +1302,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.19652234873414609727168969049557770989e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -5.73529976407853894192156335785920329181e-4),
         };
-        static const RealType Q[13] = {
+        BOOST_MATH_STATIC const RealType Q[13] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.04157569499592889296640733909653747983e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.82248883130787159161541119440215325308e2),
@@ -1322,7 +1326,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 7.1196e-37
         // LCOV_EXCL_START
-        static const RealType P[15] = {
+        BOOST_MATH_STATIC const RealType P[15] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.31309550000758082761278726632760756847e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.07242222531117199094690544171275415854e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.18286763141875580859241637334381199648e1),
@@ -1339,7 +1343,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.93943913630044161720796150617166047233e-5),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -9.76395009419307902351328300308365369814e-8),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28073115520716780203055949058270715651e1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.20245752585870752942356137496087189194e1),
@@ -1364,7 +1368,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.5605e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.71280312689343266367958859259591541365e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49628636612698702680819948707479820292e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.61090930375686902075245639803646265081e0),
@@ -1380,7 +1384,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.18976033102817074104109472578202752346e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.22093548539863254922531707899658394458e-10),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.83305694892673455436552817409325835774e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.49922543669955056754932640312490112609e1),
@@ -1405,7 +1409,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.1494e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.13928162275383718405630406427822960090e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.90742307267701162395764574873947997211e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.13821826367941514387521090205756466068e-1),
@@ -1421,7 +1425,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35934159016861180185992558083703785765e-11),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21044098237798939057079316997065892072e-14),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.94437702178976797218081686254875998984e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.82068837586514484653828718675654460991e0),
@@ -1446,7 +1450,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.9710e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.63772802979087199762340235165979751298e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31941534705372320785274994658709390116e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.43643960022585762678456016437621064500e-1),
@@ -1462,7 +1466,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.71832232038263988173042637335112603365e-15),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.72380245500539326441037770757072641975e-18),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.51702400281458104713682413542736419584e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01375164846907815766683647295932603968e0),
@@ -1487,7 +1491,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 5.2049e-36
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.22610122564874286614786819620499101143e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.30352481858382230273216195795534959290e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.45933050053542949214164590814846222512e-2),
@@ -1503,7 +1507,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.17133505681224996657291059553060754343e-19),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41010917905686427164414364663355769988e-22),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.31062773739451672808456319166347015167e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35386721434011881226168110614121649232e-1),
@@ -1528,7 +1532,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 1.7434e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03056141356415128156562790092782153630e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.15331583242023443256381237551843296356e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.81847913073640285776566199343276995613e-3),
@@ -1544,7 +1548,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.66081982641748223969990279975752576675e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.96483118060215455299182487430511998831e-26),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.77347004038951368607085827825968614455e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.27559305780716801070924630708599448466e-2),
@@ -1569,7 +1573,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 2.0402e-35
         // LCOV_EXCL_START
-        static const RealType P[14] = {
+        BOOST_MATH_STATIC const RealType P[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.57333571766941514095434647381791040479e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.15416685251021339933358981066948923001e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86806753164417557035166075399588122481e-4),
@@ -1585,7 +1589,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.14658948592500290756690769268766876322e-26),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.86984591055448991335081550609451649866e-30),
         };
-        static const RealType Q[14] = {
+        BOOST_MATH_STATIC const RealType Q[14] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.90112824856612652807095815199496602262e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59291524937386142936420775839969648652e-2),
@@ -1610,7 +1614,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
         // Rational Approximation
         // Maximum Relative Error: 9.2612e-35
         // LCOV_EXCL_START
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.98942280401432677939946059934381868476e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.33908701314796522684603310107061150444e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.92120397142832495974006972404741124398e-2),
@@ -1621,7 +1625,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
             BOOST_MATH_BIG_CONSTANT(RealType, 113, -4.75092244933846337077999183310087492887e-7),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35099582728548602389917143511323566818e-8),
         };
-        static const RealType Q[7] = {
+        BOOST_MATH_STATIC const RealType Q[7] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.34601617336219074065534356705298927390e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.82954035780824611941899463895040327299e-1),
@@ -1638,7 +1642,7 @@ inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integr
 }
 
 template <class RealType>
-inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
     }
@@ -1646,12 +1650,12 @@ inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const
         return complement ? 1 - saspoint5_cdf_plus_imp_prec(-x, tag) : saspoint5_cdf_plus_imp_prec(-x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType>
-inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
     }
@@ -1659,18 +1663,18 @@ inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const
         return complement ? 1 - saspoint5_cdf_plus_imp_prec(-x, tag) : saspoint5_cdf_plus_imp_prec(-x, tag);
     }
     else {
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
     }
 }
 
 template <class RealType, class Policy>
-inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x, bool complement) {
     //
     // This calculates the cdf of the Saspoint5 distribution and/or its complement.
     //
 
     BOOST_MATH_STD_USING // for ADL of std functions
-    static const char* function = "boost::math::cdf(saspoint5<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(saspoint5<%1%>&, %1%)";
     RealType result = 0;
     RealType location = dist.location();
     RealType scale = dist.scale();
@@ -1706,7 +1710,7 @@ inline RealType saspoint5_cdf_imp(const saspoint5_distribution<RealType, Policy>
 }
 
 template <class RealType>
-inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1717,7 +1721,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         if (u < 0.125) {
             // Rational Approximation
             // Maximum Relative Error: 4.2616e-17
-            static const RealType P[13] = {
+            BOOST_MATH_STATIC const RealType P[13] = {
                 static_cast<RealType>(1.36099130643975127045e-1),
                 static_cast<RealType>(2.19634434498311523885e1),
                 static_cast<RealType>(1.70276954848343179287e3),
@@ -1732,7 +1736,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(1.49986408149520127078e10),
                 static_cast<RealType>(-6.17325587219357123900e8),
             };
-            static const RealType Q[13] = {
+            BOOST_MATH_STATIC const RealType Q[13] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.63111146753825227716e2),
                 static_cast<RealType>(1.27864461509685444043e4),
@@ -1755,7 +1759,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 2.3770e-19
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(1.46698650748920243698e-2),
                 static_cast<RealType>(3.58380131788385557227e-1),
                 static_cast<RealType>(3.39153750029553194566e0),
@@ -1765,7 +1769,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(2.77679052294606319767e0),
                 static_cast<RealType>(-7.76665288232972435969e-2),
             };
-            static const RealType Q[7] = {
+            BOOST_MATH_STATIC const RealType Q[7] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(1.72584280323876188464e1),
                 static_cast<RealType>(1.11983518800147654866e2),
@@ -1782,7 +1786,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 9.2445e-18
-            static const RealType P[8] = {
+            BOOST_MATH_STATIC const RealType P[8] = {
                 static_cast<RealType>(2.69627866689346445458e-2),
                 static_cast<RealType>(3.23091180507445216811e-1),
                 static_cast<RealType>(1.42164019533549860681e0),
@@ -1792,7 +1796,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(-2.55816250186301841152e-2),
                 static_cast<RealType>(3.02683750470398342224e-3),
             };
-            static const RealType Q[6] = {
+            BOOST_MATH_STATIC const RealType Q[6] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(8.55049920135376003042e0),
                 static_cast<RealType>(2.48726119139047911316e1),
@@ -1808,7 +1812,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
             // Rational Approximation
             // Maximum Relative Error: 2.2918e-20
-            static const RealType P[9] = {
+            BOOST_MATH_STATIC const RealType P[9] = {
                 static_cast<RealType>(4.79518653373241051274e-2),
                 static_cast<RealType>(3.81837125793765918564e-1),
                 static_cast<RealType>(1.13370353708146321188e0),
@@ -1819,7 +1823,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 static_cast<RealType>(1.73314614571009160225e-3),
                 static_cast<RealType>(-3.63491208733876986098e-5),
             };
-            static const RealType Q[8] = {
+            BOOST_MATH_STATIC const RealType Q[8] = {
                 static_cast<RealType>(1.),
                 static_cast<RealType>(6.36954463000253710936e0),
                 static_cast<RealType>(1.40601897306833147611e1),
@@ -1838,7 +1842,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.2057e-18
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(8.02395484493329835881e-2),
             static_cast<RealType>(2.46132933068351274622e-1),
             static_cast<RealType>(2.81820176867119231101e-1),
@@ -1850,7 +1854,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(-2.06151396745690348445e-7),
             static_cast<RealType>(6.77986548138011345849e-9),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(2.39244329037830026691e0),
             static_cast<RealType>(2.12683465416376620896e0),
@@ -1868,7 +1872,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 3.3944e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(1.39293493266195561875e-1),
             static_cast<RealType>(1.26741380938661691592e-1),
             static_cast<RealType>(4.31117040307200265931e-2),
@@ -1879,7 +1883,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(9.63513655399980075083e-8),
             static_cast<RealType>(-6.40223609013005302318e-11),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(8.11234548272888947555e-1),
             static_cast<RealType>(2.63525516991753831892e-1),
@@ -1897,7 +1901,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 4.1544e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(1.57911660613037760235e-1),
             static_cast<RealType>(5.59740955695099219682e-2),
             static_cast<RealType>(8.92895854008560399142e-3),
@@ -1908,7 +1912,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(7.62193242864380357931e-10),
             static_cast<RealType>(-7.82035413331699873450e-14),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.49007782566002620811e-1),
             static_cast<RealType>(5.65303702876260444572e-2),
@@ -1926,7 +1930,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 8.5877e-18
-        static const RealType P[10] = {
+        BOOST_MATH_STATIC const RealType P[10] = {
             static_cast<RealType>(1.59150086070234563099e-1),
             static_cast<RealType>(6.07144002506911115092e-2),
             static_cast<RealType>(1.10026443723891740392e-2),
@@ -1938,7 +1942,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(1.05110361316230054467e-10),
             static_cast<RealType>(1.48083450629432857655e-18),
         };
-        static const RealType Q[9] = {
+        BOOST_MATH_STATIC const RealType Q[9] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(3.81470315977341203351e-1),
             static_cast<RealType>(6.91330250512167919573e-2),
@@ -1957,7 +1961,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
         // Rational Approximation
         // Maximum Relative Error: 8.7254e-17
-        static const RealType P[9] = {
+        BOOST_MATH_STATIC const RealType P[9] = {
             static_cast<RealType>(1.59154943017783026201e-1),
             static_cast<RealType>(6.91506515614472069475e-2),
             static_cast<RealType>(1.44590186111155933843e-2),
@@ -1968,7 +1972,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             static_cast<RealType>(3.50107118687544980820e-8),
             static_cast<RealType>(-1.47102592933729597720e-22),
         };
-        static const RealType Q[8] = {
+        BOOST_MATH_STATIC const RealType Q[8] = {
             static_cast<RealType>(1.),
             static_cast<RealType>(4.34486357752330500669e-1),
             static_cast<RealType>(9.08486933075320995164e-2),
@@ -1990,7 +1994,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 
 
 template <class RealType>
-inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2002,7 +2006,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 2.5675e-36
             // LCOV_EXCL_START
-            static const RealType P[31] = {
+            BOOST_MATH_STATIC const RealType P[31] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.36099130643975133156293056139850872219e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.03940482189350763127508703926866548690e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.00518276893354880480781640750482315271e4),
@@ -2035,7 +2039,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.62706943144847786115732327787879709587e32),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.32129438774563059735783287456769609571e31),
             };
-            static const RealType Q[32] = {
+            BOOST_MATH_STATIC const RealType Q[32] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.65910866673514847742559406762379054364e2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.21954860438789969160116317316418373146e5),
@@ -2078,7 +2082,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 9.0663e-36
             // LCOV_EXCL_START
-            static const RealType P[13] = {
+            BOOST_MATH_STATIC const RealType P[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.46698650748920243663487731226111319705e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.39021286045890143123252180276484388346e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.21933242816562043224009451007344301143e1),
@@ -2093,7 +2097,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.41565791250614170744069436181282300453e2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.35838723365672196069179944509778281549e1),
             };
-            static const RealType Q[13] = {
+            BOOST_MATH_STATIC const RealType Q[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.63888803456697300467924455320638435538e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.74785179836182339383932806919167693991e2),
@@ -2117,7 +2121,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 7.1265e-35
             // LCOV_EXCL_START
-            static const RealType P[14] = {
+            BOOST_MATH_STATIC const RealType P[14] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.69627866689346442965083437425920959525e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.28948812330446670380449765578224539665e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.38832694133021352110245148952631526683e0),
@@ -2133,7 +2137,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.81260575060831053615857196033574207714e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.26783311530618626413866321968979725353e-3),
             };
-            static const RealType Q[13] = {
+            BOOST_MATH_STATIC const RealType Q[13] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.98941943311823528497840052715295329781e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.70142252619301982454969690308614487433e2),
@@ -2157,7 +2161,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             // Rational Approximation
             // Maximum Relative Error: 2.7048e-37
             // LCOV_EXCL_START
-            static const RealType P[15] = {
+            BOOST_MATH_STATIC const RealType P[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.79518653373241051262822702930040975338e-2),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.62230291299220868262265687829866364204e-1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.87315544620612697712513318458226575394e0),
@@ -2174,7 +2178,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.99365265557355974918712592061740510276e-4),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.66467016868206844419002547523627548705e-6),
             };
-            static const RealType Q[15] = {
+            BOOST_MATH_STATIC const RealType Q[15] = {
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.01315080955831561204744043759079263546e1),
                 BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.43409077070585581955481063438385546913e1),
@@ -2201,7 +2205,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 3.8969e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.02395484493329839255216366819344305871e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.02703992140456336967688958960484716694e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.38779662796374026809611637926067177436e0),
@@ -2221,7 +2225,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.13496588267213644899739513941375650458e-13),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.75224691413667093006312591320754720811e-14),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.59000688626663121310675150262772434285e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.37518060227321498297232252379976917550e1),
@@ -2249,7 +2253,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 4.0176e-35
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.39293493266195566603513288406748830312e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.75724665658983779947977436518056682748e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.42437549740894393207094008058345312893e-1),
@@ -2268,7 +2272,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.40274507498190913768918372242285652373e-14),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.48644117815971872777609922455371868747e-16),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.88079839671202113888025645668230104601e0),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.58898753182105924446845274197682915131e0),
@@ -2296,7 +2300,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 4.1682e-36
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.57911660613037766795694241662819364797e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.28799302413396670477035614399187456630e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.87488304496324715063356722168914018093e-2),
@@ -2315,7 +2319,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.31679318790012894619592273346600264199e-18),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.97289727214495789126072009268721022605e-20),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.10184661848812835285809771940181522329e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.06179300560230499194426573196970342618e-1),
@@ -2343,7 +2347,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 6.2158e-37
         // LCOV_EXCL_START
-        static const RealType P[17] = {
+        BOOST_MATH_STATIC const RealType P[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59150086070234561732507586188017224084e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.80849532387385837583114307010320459997e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.41158479406270598752210344238285334672e-2),
@@ -2362,7 +2366,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.17863064141234633971470839644872485483e-21),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 5.58768205048500915346781559321978174829e-24),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.27782279546086824129750042200649907991e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.86934772625607907724733810228981095894e-2),
@@ -2390,7 +2394,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 9.8515e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943017783040087729009335921759322e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.35955784629344586058432079844665517425e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.24333525582177610783141409282489279582e-2),
@@ -2410,7 +2414,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.56200324658873566425094389271790730206e-23),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.35526648761411463124801128103381691418e-26),
         };
-        static const RealType Q[18] = {
+        BOOST_MATH_STATIC const RealType Q[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.99582804063194774835771688139366152937e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 7.81210581320456331960539046132284190053e-2),
@@ -2439,7 +2443,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
         // Rational Approximation
         // Maximum Relative Error: 2.2157e-35
         // LCOV_EXCL_START
-        static const RealType P[18] = {
+        BOOST_MATH_STATIC const RealType P[18] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.59154943091895335751628149866310390641e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 6.91164927854420277537616294413463565970e-2),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.47557801928232619499125670863084398577e-2),
@@ -2459,7 +2463,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.35722092370326505616747155207965300634e-22),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 8.98381676423023212724768510437325359364e-51),
         };
-        static const RealType Q[17] = {
+        BOOST_MATH_STATIC const RealType Q[17] = {
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 1.),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 4.34271731953273239691423485699928257808e-1),
             BOOST_MATH_BIG_CONSTANT(RealType, 113, 9.27133013035186849140772481980360839559e-2),
@@ -2489,7 +2493,7 @@ inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::
 }
 
 template <class RealType>
-inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
         return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
@@ -2499,7 +2503,7 @@ inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement,
 }
 
 template <class RealType>
-inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
         return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
@@ -2509,12 +2513,12 @@ inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement,
 }
 
 template <class RealType, class Policy>
-inline RealType saspoint5_quantile_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p, bool complement)
 {
     // This routine implements the quantile for the Saspoint5 distribution,
     // the value p may be the probability, or its complement if complement=true.
 
-    static const char* function = "boost::math::quantile(saspoint5<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(saspoint5<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -2550,23 +2554,23 @@ inline RealType saspoint5_quantile_imp(const saspoint5_distribution<RealType, Po
 }
 
 template <class RealType>
-inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(3.63992444568030649573);
 }
 
 template <class RealType>
-inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.6399244456803064957308496039071853510);
 }
 
 template <class RealType, class Policy>
-inline RealType saspoint5_entropy_imp(const saspoint5_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp(const saspoint5_distribution<RealType, Policy>& dist)
 {
     // This implements the entropy for the Saspoint5 distribution,
 
-    static const char* function = "boost::math::entropy(saspoint5<%1%>&, %1%)";
+    constexpr auto function = "boost::math::entropy(saspoint5<%1%>&, %1%)";
     BOOST_MATH_STD_USING // for ADL of std functions
 
     RealType result = 0;
@@ -2601,20 +2605,20 @@ class saspoint5_distribution
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    saspoint5_distribution(RealType l_location = 0, RealType l_scale = 1)
+    BOOST_MATH_GPU_ENABLED saspoint5_distribution(RealType l_location = 0, RealType l_scale = 1)
         : mu(l_location), c(l_scale)
     {
-        static const char* function = "boost::math::saspoint5_distribution<%1%>::saspoint5_distribution";
+        constexpr auto function = "boost::math::saspoint5_distribution<%1%>::saspoint5_distribution";
         RealType result = 0;
         detail::check_location(function, l_location, &result, Policy());
         detail::check_scale(function, l_scale, &result, Policy());
     } // saspoint5_distribution
 
-    RealType location()const
+    BOOST_MATH_GPU_ENABLED RealType location()const
     {
         return mu;
     }
-    RealType scale()const
+    BOOST_MATH_GPU_ENABLED RealType scale()const
     {
         return c;
     }
@@ -2634,66 +2638,66 @@ saspoint5_distribution(RealType, RealType) -> saspoint5_distribution<typename bo
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const saspoint5_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const saspoint5_distribution<RealType, Policy>&)
 { // Range of permissible values for random variable x.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const saspoint5_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const saspoint5_distribution<RealType, Policy>&)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-    if (std::numeric_limits<RealType>::has_infinity)
+    BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
     {
-        return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+        return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
     }
     else
     { // Can only use max_value.
         using boost::math::tools::max_value;
-        return std::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
+        return boost::math::pair<RealType, RealType>(-tools::max_value<RealType>(), max_value<RealType>()); // - to + max.
     }
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::saspoint5_pdf_imp(dist, x);
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const saspoint5_distribution<RealType, Policy>& dist, const RealType& x)
 {
     return detail::saspoint5_cdf_imp(dist, x, false);
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const saspoint5_distribution<RealType, Policy>& dist, const RealType& p)
 {
     return detail::saspoint5_quantile_imp(dist, p, false);
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::saspoint5_cdf_imp(c.dist, c.param, true);
 } //  cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<saspoint5_distribution<RealType, Policy>, RealType>& c)
 {
     return detail::saspoint5_quantile_imp(c.dist, c.param, true);
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const saspoint5_distribution<RealType, Policy> &dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const saspoint5_distribution<RealType, Policy> &dist)
 {
     // There is no mean:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2703,11 +2707,11 @@ inline RealType mean(const saspoint5_distribution<RealType, Policy> &dist)
         "boost::math::mean(saspoint5<%1%>&)",
         "The SaS point5 distribution does not have a mean: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const saspoint5_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no variance:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2717,23 +2721,23 @@ inline RealType variance(const saspoint5_distribution<RealType, Policy>& /*dist*
         "boost::math::variance(saspoint5<%1%>&)",
         "The SaS point5 distribution does not have a variance: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const saspoint5_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const saspoint5_distribution<RealType, Policy>& dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const saspoint5_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const saspoint5_distribution<RealType, Policy>& dist)
 {
     return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const saspoint5_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no skewness:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2743,11 +2747,11 @@ inline RealType skewness(const saspoint5_distribution<RealType, Policy>& /*dist*
         "boost::math::skewness(saspoint5<%1%>&)",
         "The SaS point5 distribution does not have a skewness: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const saspoint5_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2757,11 +2761,11 @@ inline RealType kurtosis(const saspoint5_distribution<RealType, Policy>& /*dist*
         "boost::math::kurtosis(saspoint5<%1%>&)",
         "The SaS point5 distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const saspoint5_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const saspoint5_distribution<RealType, Policy>& /*dist*/)
 {
     // There is no kurtosis excess:
     typedef typename Policy::assert_undefined_type assert_type;
@@ -2771,11 +2775,11 @@ inline RealType kurtosis_excess(const saspoint5_distribution<RealType, Policy>&
         "boost::math::kurtosis_excess(saspoint5<%1%>&)",
         "The SaS point5 distribution does not have a kurtosis: "
         "the only possible return value is %1%.",
-        std::numeric_limits<RealType>::quiet_NaN(), Policy());
+        boost::math::numeric_limits<RealType>::quiet_NaN(), Policy());
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const saspoint5_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const saspoint5_distribution<RealType, Policy>& dist)
 {
     return detail::saspoint5_entropy_imp(dist);
 }

From 3cf8dc21cb80ab506843989bb370d8b7f9c25d19 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 12:02:52 -0400
Subject: [PATCH 165/399] Add CUDA testing to saspoint5 dist

---
 test/cuda_jamfile                  |   6 ++
 test/test_saspoint5_cdf_double.cu  | 110 +++++++++++++++++++++++++++++
 test/test_saspoint5_cdf_float.cu   | 110 +++++++++++++++++++++++++++++
 test/test_saspoint5_pdf_double.cu  | 110 +++++++++++++++++++++++++++++
 test/test_saspoint5_pdf_float.cu   | 110 +++++++++++++++++++++++++++++
 test/test_saspoint5_quan_double.cu | 110 +++++++++++++++++++++++++++++
 test/test_saspoint5_quan_float.cu  | 110 +++++++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_saspoint5_cdf_double.cu
 create mode 100644 test/test_saspoint5_cdf_float.cu
 create mode 100644 test/test_saspoint5_pdf_double.cu
 create mode 100644 test/test_saspoint5_pdf_float.cu
 create mode 100644 test/test_saspoint5_quan_double.cu
 create mode 100644 test/test_saspoint5_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 62dcbe6f00..52fa7e4c47 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -62,6 +62,12 @@ run test_mapairy_pdf_double.cu ;
 run test_mapairy_pdf_float.cu ;
 run test_mapairy_quan_double.cu ;
 run test_mapairy_quan_float.cu ;
+run test_saspoint5_cdf_double.cu ;
+run test_saspoint5_cdf_float.cu ;
+run test_saspoint5_pdf_double.cu ;
+run test_saspoint5_pdf_float.cu ;
+run test_saspoint5_quan_double.cu ;
+run test_saspoint5_quan_float.cu ;
 
 # Special Functions
 # run test_beta_simple.cpp ;
diff --git a/test/test_saspoint5_cdf_double.cu b/test/test_saspoint5_cdf_double.cu
new file mode 100644
index 0000000000..745ca2bf80
--- /dev/null
+++ b/test/test_saspoint5_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_saspoint5_cdf_float.cu b/test/test_saspoint5_cdf_float.cu
new file mode 100644
index 0000000000..51bc2e8705
--- /dev/null
+++ b/test/test_saspoint5_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_saspoint5_pdf_double.cu b/test/test_saspoint5_pdf_double.cu
new file mode 100644
index 0000000000..948a092600
--- /dev/null
+++ b/test/test_saspoint5_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_saspoint5_pdf_float.cu b/test/test_saspoint5_pdf_float.cu
new file mode 100644
index 0000000000..4980e9070c
--- /dev/null
+++ b/test/test_saspoint5_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_saspoint5_quan_double.cu b/test/test_saspoint5_quan_double.cu
new file mode 100644
index 0000000000..764c278993
--- /dev/null
+++ b/test/test_saspoint5_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_saspoint5_quan_float.cu b/test/test_saspoint5_quan_float.cu
new file mode 100644
index 0000000000..a65958fb81
--- /dev/null
+++ b/test/test_saspoint5_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::saspoint5_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 3e296563bb3dd6101adad5d467c17cc450eabea9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 12:07:15 -0400
Subject: [PATCH 166/399] Eliminate recursion in quantile

---
 include/boost/math/distributions/saspoint5.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
index fd9ff6f13b..3e78fca974 100644
--- a/include/boost/math/distributions/saspoint5.hpp
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -2496,7 +2496,7 @@ template <class RealType>
 BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
-        return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? saspoint5_quantile_upper_imp_prec(1 - p, tag) : -saspoint5_quantile_upper_imp_prec(1 - p, tag);
     }
 
     return complement ? saspoint5_quantile_upper_imp_prec(p, tag) : -saspoint5_quantile_upper_imp_prec(p, tag);
@@ -2506,7 +2506,7 @@ template <class RealType>
 BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
-        return saspoint5_quantile_imp_prec(1 - p, !complement, tag);
+        return !complement ? saspoint5_quantile_upper_imp_prec(1 - p, tag) : -saspoint5_quantile_upper_imp_prec(1 - p, tag);
     }
 
     return complement ? saspoint5_quantile_upper_imp_prec(p, tag) : -saspoint5_quantile_upper_imp_prec(p, tag);

From 16657385ffb20083300092537b83d3026d0d28c6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 12:07:23 -0400
Subject: [PATCH 167/399] Add saspoint5 CUDA testing

---
 test/sycl_jamfile       |  1 +
 test/test_saspoint5.cpp | 23 +++++++++++++++++++++--
 2 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 095babcc29..b8f91ded0f 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -17,6 +17,7 @@ run test_exponential_dist.cpp ;
 run test_holtsmark.cpp ;
 run test_landau.cpp ;
 run test_mapairy.cpp ;
+run test_saspoint5.cpp ;
 
 # Special Functions
 run pow_test.cpp ;
diff --git a/test/test_saspoint5.cpp b/test/test_saspoint5.cpp
index c734ecde7e..0703b3c547 100644
--- a/test/test_saspoint5.cpp
+++ b/test/test_saspoint5.cpp
@@ -1,13 +1,14 @@
-// Copyright Takuma Yoshimura 2024.
+//  Copyright Takuma Yoshimura 2024.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
 #define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsSaSpoint5Test
+#include <boost/math/tools/config.hpp>
 #include <boost/test/included/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
-#include <boost/multiprecision/cpp_bin_float.hpp>
 
 #include <boost/math/distributions/saspoint5.hpp>
 
@@ -16,7 +17,11 @@
 #endif
 
 using boost::math::saspoint5_distribution;
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#include <boost/multiprecision/cpp_bin_float.hpp>
 using boost::multiprecision::cpp_bin_float_quad;
+#endif
 
 template<class RealType, int N>
 void do_test_saspoint5_pdf(){
@@ -860,10 +865,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_pdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_pdf_fp128)
 {
     do_test_saspoint5_pdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp64)
 {
@@ -877,10 +884,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_cdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_cdf_fp128)
 {
     do_test_saspoint5_cdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp64)
 {
@@ -894,10 +903,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_ccdf_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_ccdf_fp128)
 {
     do_test_saspoint5_ccdf<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp64)
 {
@@ -911,10 +922,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_nearzero_fp128)
 {
     do_test_saspoint5_quantile_nearzero<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp64)
 {
@@ -928,10 +941,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_lower_fp128)
 {
     do_test_saspoint5_quantile_lower<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp64)
 {
@@ -945,10 +960,12 @@ BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_quantile_upper_fp128)
 {
     do_test_saspoint5_quantile_upper<cpp_bin_float_quad, 113>();
 }
+#endif
 
 BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp64)
 {
@@ -962,7 +979,9 @@ BOOST_AUTO_TEST_CASE(saspoint5_locscale_std64)
 }
 #endif
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 BOOST_AUTO_TEST_CASE(saspoint5_locscale_fp128)
 {
     do_test_saspoint5_locscale_param<cpp_bin_float_quad, 113>();
 }
+#endif

From 4284c9d1a34b2ae6d18f33c1f87093d315a3aa34 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 12:19:41 -0400
Subject: [PATCH 168/399] Replace workaround macro with new numeric_limits

---
 include/boost/math/policies/error_handling.hpp | 6 +++---
 include/boost/math/tools/config.hpp            | 9 ---------
 2 files changed, 3 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index f3811d9193..0f85023be0 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -211,7 +211,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
 #else
    raise_error<std::domain_error, T>(function, message, val);
    // we never get here:
-   return BOOST_MATH_QUIET_NAN(T);
+   return boost::math::numeric_limits<T>::quiet_NaN();
 #endif
 }
 
@@ -224,7 +224,7 @@ BOOST_MATH_GPU_ENABLED constexpr T raise_domain_error(
 {
    // This may or may not do the right thing, but the user asked for the error
    // to be ignored so here we go anyway:
-   return BOOST_MATH_QUIET_NAN(T);
+   return boost::math::numeric_limits<T>::quiet_NaN();
 }
 
 template <class T>
@@ -237,7 +237,7 @@ BOOST_MATH_GPU_ENABLED inline T raise_domain_error(
    errno = EDOM;
    // This may or may not do the right thing, but the user asked for the error
    // to be silent so here we go anyway:
-   return BOOST_MATH_QUIET_NAN(T);
+   return boost::math::numeric_limits<T>::quiet_NaN();
 }
 
 template <class T>
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index c03f6170a8..152edfa0ee 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -683,9 +683,6 @@ namespace boost{ namespace math{
 #  undef BOOST_MATH_FORCEINLINE
 #  define BOOST_MATH_FORCEINLINE __forceinline__
 
-// We can't use return std::numeric_limits<T>::quiet_NaN()
-#  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
-
 #elif defined(SYCL_LANGUAGE_VERSION)
 
 #  define BOOST_MATH_SYCL_ENABLED SYCL_EXTERNAL
@@ -706,8 +703,6 @@ namespace boost{ namespace math{
 #  undef BOOST_MATH_FORCEINLINE
 #  define BOOST_MATH_FORCEINLINE inline
 
-#  define BOOST_MATH_QUIET_NAN(T) static_cast<T>(NAN);
-
 #endif
 
 #ifndef BOOST_MATH_CUDA_ENABLED
@@ -718,10 +713,6 @@ namespace boost{ namespace math{
 #  define BOOST_MATH_SYCL_ENABLED
 #endif
 
-#ifndef BOOST_MATH_QUIET_NAN
-#  define BOOST_MATH_QUIET_NAN(T) std::numeric_limits<T>::quiet_NaN();
-#endif
-
 // Not all functions that allow CUDA allow SYCL (e.g. Recursion is disallowed by SYCL)
 #  define BOOST_MATH_GPU_ENABLED BOOST_MATH_CUDA_ENABLED BOOST_MATH_SYCL_ENABLED
 

From 6b92d0c692407baa19de106a3754c6aac1ec4c5b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 13:14:10 -0400
Subject: [PATCH 169/399] Add GPU support to extreme value dist

---
 .../math/distributions/extreme_value.hpp      | 68 ++++++++++---------
 1 file changed, 36 insertions(+), 32 deletions(-)

diff --git a/include/boost/math/distributions/extreme_value.hpp b/include/boost/math/distributions/extreme_value.hpp
index 1bde2743c0..d3249908a6 100644
--- a/include/boost/math/distributions/extreme_value.hpp
+++ b/include/boost/math/distributions/extreme_value.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -6,6 +7,9 @@
 #ifndef BOOST_STATS_EXTREME_VALUE_HPP
 #define BOOST_STATS_EXTREME_VALUE_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/log1p.hpp>
@@ -35,7 +39,7 @@ namespace detail{
 // Error check:
 //
 template <class RealType, class Policy>
-inline bool verify_scale_b(const char* function, RealType b, RealType* presult, const Policy& pol)
+BOOST_GPU_ENABLED inline bool verify_scale_b(const char* function, RealType b, RealType* presult, const Policy& pol)
 {
    if((b <= 0) || !(boost::math::isfinite)(b))
    {
@@ -56,7 +60,7 @@ class extreme_value_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit extreme_value_distribution(RealType a = 0, RealType b = 1)
+   BOOST_MATH_GPU_ENABLED explicit extreme_value_distribution(RealType a = 0, RealType b = 1)
       : m_a(a), m_b(b)
    {
       RealType err;
@@ -64,8 +68,8 @@ class extreme_value_distribution
       detail::check_finite("boost::math::extreme_value_distribution<%1%>::extreme_value_distribution", a, &err, Policy());
    } // extreme_value_distribution
 
-   RealType location()const { return m_a; }
-   RealType scale()const { return m_b; }
+   BOOST_MATH_GPU_ENABLED RealType location()const { return m_a; }
+   BOOST_MATH_GPU_ENABLED RealType scale()const { return m_b; }
 
 private:
    RealType m_a;
@@ -82,28 +86,28 @@ extreme_value_distribution(RealType,RealType)->extreme_value_distribution<typena
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(
-      std::numeric_limits<RealType>::has_infinity ? -std::numeric_limits<RealType>::infinity() : -max_value<RealType>(), 
-      std::numeric_limits<RealType>::has_infinity ? std::numeric_limits<RealType>::infinity() : max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(
+      boost::math::numeric_limits<RealType>::has_infinity ? -boost::math::numeric_limits<RealType>::infinity() : -max_value<RealType>(), 
+      boost::math::numeric_limits<RealType>::has_infinity ? boost::math::numeric_limits<RealType>::infinity() : max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(-max_value<RealType>(),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(-max_value<RealType>(),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_GPU_ENABLED inline RealType pdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const extreme_value_distribution<%1%>&, %1%)";
 
    RealType a = dist.location();
    RealType b = dist.scale();
@@ -124,15 +128,15 @@ inline RealType pdf(const extreme_value_distribution<RealType, Policy>& dist, co
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_GPU_ENABLED inline RealType logpdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logpdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logpdf(const extreme_value_distribution<%1%>&, %1%)";
 
    RealType a = dist.location();
    RealType b = dist.scale();
-   RealType result = -std::numeric_limits<RealType>::infinity();
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
    if(0 == detail::verify_scale_b(function, b, &result, Policy()))
       return result;
    if(0 == detail::check_finite(function, a, &result, Policy()))
@@ -149,11 +153,11 @@ inline RealType logpdf(const extreme_value_distribution<RealType, Policy>& dist,
 } // logpdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_GPU_ENABLED inline RealType cdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const extreme_value_distribution<%1%>&, %1%)";
 
    if((boost::math::isinf)(x))
       return x < 0 ? 0.0f : 1.0f;
@@ -175,11 +179,11 @@ inline RealType cdf(const extreme_value_distribution<RealType, Policy>& dist, co
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType logcdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_GPU_ENABLED inline RealType logcdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const extreme_value_distribution<%1%>&, %1%)";
 
    if((boost::math::isinf)(x))
       return x < 0 ? 0.0f : 1.0f;
@@ -205,7 +209,7 @@ RealType quantile(const extreme_value_distribution<RealType, Policy>& dist, cons
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const extreme_value_distribution<%1%>&, %1%)";
 
    RealType a = dist.location();
    RealType b = dist.scale();
@@ -228,11 +232,11 @@ RealType quantile(const extreme_value_distribution<RealType, Policy>& dist, cons
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
+BOOST_GPU_ENABLED inline RealType cdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const extreme_value_distribution<%1%>&, %1%)";
 
    if((boost::math::isinf)(c.param))
       return c.param < 0 ? 1.0f : 0.0f;
@@ -252,11 +256,11 @@ inline RealType cdf(const complemented2_type<extreme_value_distribution<RealType
 }
 
 template <class RealType, class Policy>
-inline RealType logcdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
+BOOST_GPU_ENABLED inline RealType logcdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const extreme_value_distribution<%1%>&, %1%)";
 
    if((boost::math::isinf)(c.param))
       return c.param < 0 ? 1.0f : 0.0f;
@@ -280,7 +284,7 @@ RealType quantile(const complemented2_type<extreme_value_distribution<RealType,
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const extreme_value_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const extreme_value_distribution<%1%>&, %1%)";
 
    RealType a = c.dist.location();
    RealType b = c.dist.scale();
@@ -304,7 +308,7 @@ RealType quantile(const complemented2_type<extreme_value_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_GPU_ENABLED inline RealType mean(const extreme_value_distribution<RealType, Policy>& dist)
 {
    RealType a = dist.location();
    RealType b = dist.scale();
@@ -317,7 +321,7 @@ inline RealType mean(const extreme_value_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType standard_deviation(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_GPU_ENABLED inline RealType standard_deviation(const extreme_value_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING // for ADL of std functions.
 
@@ -331,20 +335,20 @@ inline RealType standard_deviation(const extreme_value_distribution<RealType, Po
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_GPU_ENABLED inline RealType mode(const extreme_value_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_GPU_ENABLED inline RealType median(const extreme_value_distribution<RealType, Policy>& dist)
 {
   using constants::ln_ln_two;
    return dist.location() - dist.scale() * ln_ln_two<RealType>();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_GPU_ENABLED inline RealType skewness(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    //
    // This is 12 * sqrt(6) * zeta(3) / pi^3:
@@ -354,14 +358,14 @@ inline RealType skewness(const extreme_value_distribution<RealType, Policy>& /*d
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_GPU_ENABLED inline RealType kurtosis(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
    return RealType(27) / 5;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_GPU_ENABLED inline RealType kurtosis_excess(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
    return RealType(12) / 5;

From d195e2b55bc64e83df7a87783402886cacc6a656 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 13:26:08 -0400
Subject: [PATCH 170/399] Fix GPU support for extreme value dist quantile

---
 include/boost/math/distributions/extreme_value.hpp |  2 +-
 include/boost/math/tools/precision.hpp             | 12 ++++++------
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/include/boost/math/distributions/extreme_value.hpp b/include/boost/math/distributions/extreme_value.hpp
index d3249908a6..c6ee7a59f8 100644
--- a/include/boost/math/distributions/extreme_value.hpp
+++ b/include/boost/math/distributions/extreme_value.hpp
@@ -205,7 +205,7 @@ BOOST_GPU_ENABLED inline RealType logcdf(const extreme_value_distribution<RealTy
 } // logcdf
 
 template <class RealType, class Policy>
-RealType quantile(const extreme_value_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED RealType quantile(const extreme_value_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index d82144466d..b9577efeee 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -133,19 +133,19 @@ BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<in
 // 80 and 128-bit long doubles:
 //
 template <class T>
-inline constexpr T log_max_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return 11356.0L;
 }
 
 template <class T>
-inline constexpr T log_min_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
 {
    return -11355.0L;
 }
 
 template <class T>
-inline T log_max_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+BOOST_MATH_GPU_ENABLED inline T log_max_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    BOOST_MATH_STD_USING
 #ifdef __SUNPRO_CC
@@ -158,7 +158,7 @@ inline T log_max_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_E
 }
 
 template <class T>
-inline T log_min_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+BOOST_MATH_GPU_ENABLED inline T log_min_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    BOOST_MATH_STD_USING
 #ifdef __SUNPRO_CC
@@ -249,7 +249,7 @@ struct log_limit_noexcept_traits : public log_limit_noexcept_traits_imp<T, std::
 #endif
 
 template <class T>
-inline constexpr T log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::log_max_value<T>(typename detail::log_limit_traits<T>::tag_type());
@@ -262,7 +262,7 @@ inline constexpr T log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(
 }
 
 template <class T>
-inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::log_min_value<T>(typename detail::log_limit_traits<T>::tag_type());

From 44bad32b76fd6f775a7b2c4cbd293f1b0bffca89 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 13:26:20 -0400
Subject: [PATCH 171/399] Add CUDA testing of extreme value dist

---
 test/cuda_jamfile                      |   6 ++
 test/test_extreme_value_cdf_double.cu  | 110 +++++++++++++++++++++++++
 test/test_extreme_value_cdf_float.cu   | 110 +++++++++++++++++++++++++
 test/test_extreme_value_pdf_double.cu  | 110 +++++++++++++++++++++++++
 test/test_extreme_value_pdf_float.cu   | 110 +++++++++++++++++++++++++
 test/test_extreme_value_quan_double.cu | 110 +++++++++++++++++++++++++
 test/test_extreme_value_quan_float.cu  | 110 +++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_extreme_value_cdf_double.cu
 create mode 100644 test/test_extreme_value_cdf_float.cu
 create mode 100644 test/test_extreme_value_pdf_double.cu
 create mode 100644 test/test_extreme_value_pdf_float.cu
 create mode 100644 test/test_extreme_value_quan_double.cu
 create mode 100644 test/test_extreme_value_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 52fa7e4c47..9bc7429c7e 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -46,6 +46,12 @@ run test_exponential_quan_double.cu ;
 run test_exponential_quan_float.cu ;
 run test_exponential_range_support_double.cu ;
 run test_exponential_range_support_float.cu ;
+run test_extreme_value_cdf_double.cu ;
+run test_extreme_value_cdf_float.cu ;
+run test_extreme_value_pdf_double.cu ;
+run test_extreme_value_pdf_float.cu ;
+run test_extreme_value_quan_double.cu ;
+run test_extreme_value_quan_float.cu ;
 run test_holtsmark_cdf_double.cu ;
 run test_holtsmark_cdf_float.cu ;
 run test_holtsmark_pdf_double.cu ;
diff --git a/test/test_extreme_value_cdf_double.cu b/test/test_extreme_value_cdf_double.cu
new file mode 100644
index 0000000000..8f7f366b3b
--- /dev/null
+++ b/test/test_extreme_value_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_extreme_value_cdf_float.cu b/test/test_extreme_value_cdf_float.cu
new file mode 100644
index 0000000000..d1b6cc7624
--- /dev/null
+++ b/test/test_extreme_value_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_extreme_value_pdf_double.cu b/test/test_extreme_value_pdf_double.cu
new file mode 100644
index 0000000000..4cf3fc2d0f
--- /dev/null
+++ b/test/test_extreme_value_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_extreme_value_pdf_float.cu b/test/test_extreme_value_pdf_float.cu
new file mode 100644
index 0000000000..c0c5da7eeb
--- /dev/null
+++ b/test/test_extreme_value_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_extreme_value_quan_double.cu b/test/test_extreme_value_quan_double.cu
new file mode 100644
index 0000000000..703d2054f3
--- /dev/null
+++ b/test/test_extreme_value_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 1000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_extreme_value_quan_float.cu b/test/test_extreme_value_quan_float.cu
new file mode 100644
index 0000000000..25d982cd0f
--- /dev/null
+++ b/test/test_extreme_value_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::extreme_value_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 2000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 92a99048e6d9c332e1b27a9166c64a8250952ae7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 13:28:30 -0400
Subject: [PATCH 172/399] Add extreme value dist SYCL testing

---
 test/sycl_jamfile           | 1 +
 test/test_extreme_value.cpp | 4 ++--
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index b8f91ded0f..9bf3579806 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -14,6 +14,7 @@ run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
 run test_exponential_dist.cpp ;
+run test_extreme_value.cpp ;
 run test_holtsmark.cpp ;
 run test_landau.cpp ;
 run test_mapairy.cpp ;
diff --git a/test/test_extreme_value.cpp b/test/test_extreme_value.cpp
index fd8d928630..cb758e8f5b 100644
--- a/test/test_extreme_value.cpp
+++ b/test/test_extreme_value.cpp
@@ -1,5 +1,5 @@
 // Copyright John Maddock 2006.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -7,7 +7,7 @@
 
 // test_extreme_value.cpp
 
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 #include <boost/math/distributions/extreme_value.hpp>
     using boost::math::extreme_value_distribution;

From 77ab76ed962399093ec4f1eb73d71c6de55ce4ef Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:03:48 -0400
Subject: [PATCH 173/399] Add GPU support to laplace dist

---
 include/boost/math/distributions/laplace.hpp | 84 ++++++++++----------
 1 file changed, 44 insertions(+), 40 deletions(-)

diff --git a/include/boost/math/distributions/laplace.hpp b/include/boost/math/distributions/laplace.hpp
index 81ae8fed9d..55e2236f99 100644
--- a/include/boost/math/distributions/laplace.hpp
+++ b/include/boost/math/distributions/laplace.hpp
@@ -1,6 +1,7 @@
 //  Copyright Thijs van den Berg, 2008.
 //  Copyright John Maddock 2008.
 //  Copyright Paul A. Bristow 2008, 2014.
+//  Copyright Matt Borland 2024.
 
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
@@ -17,6 +18,9 @@
 #ifndef BOOST_STATS_LAPLACE_HPP
 #define BOOST_STATS_LAPLACE_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -43,7 +47,7 @@ class laplace_distribution
    // ----------------------------------
    // Constructor(s)
    // ----------------------------------
-   explicit laplace_distribution(RealType l_location = 0, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED explicit laplace_distribution(RealType l_location = 0, RealType l_scale = 1)
       : m_location(l_location), m_scale(l_scale)
    {
       RealType result;
@@ -55,17 +59,17 @@ class laplace_distribution
    // Public functions
    // ----------------------------------
 
-   RealType location() const
+   BOOST_MATH_GPU_ENABLED RealType location() const
    {
       return m_location;
    }
 
-   RealType scale() const
+   BOOST_MATH_GPU_ENABLED RealType scale() const
    {
       return m_scale;
    }
 
-   bool check_parameters(const char* function, RealType* result) const
+   BOOST_MATH_GPU_ENABLED bool check_parameters(const char* function, RealType* result) const
    {
          if(false == detail::check_scale(function, m_scale, result, Policy())) return false;
          if(false == detail::check_location(function, m_location, result, Policy())) return false;
@@ -91,42 +95,42 @@ laplace_distribution(RealType,RealType)->laplace_distribution<typename boost::ma
 //
 // Non-member functions.
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const laplace_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const laplace_distribution<RealType, Policy>&)
 {
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   {  // Can use infinity.
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   { // Can only use max_value.
     using boost::math::tools::max_value;
-    return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
+    return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
   }
 
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const laplace_distribution<RealType, Policy>&)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const laplace_distribution<RealType, Policy>&)
 {
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { // Can Use infinity.
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   { // Can only use max_value.
     using boost::math::tools::max_value;
-    return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
+    return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
   }
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    // Checking function argument
    RealType result = 0;
-   const char* function = "boost::math::pdf(const laplace_distribution<%1%>&, %1%))";
+   constexpr auto function = "boost::math::pdf(const laplace_distribution<%1%>&, %1%))";
 
    // Check scale and location.
    if (false == dist.check_parameters(function, &result)) return result;
@@ -152,13 +156,13 @@ inline RealType pdf(const laplace_distribution<RealType, Policy>& dist, const Re
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    // Checking function argument
-   RealType result = -std::numeric_limits<RealType>::infinity();
-   const char* function = "boost::math::logpdf(const laplace_distribution<%1%>&, %1%))";
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
+   constexpr auto function = "boost::math::logpdf(const laplace_distribution<%1%>&, %1%))";
 
    // Check scale and location.
    if (false == dist.check_parameters(function, &result))
@@ -179,7 +183,7 @@ inline RealType logpdf(const laplace_distribution<RealType, Policy>& dist, const
    const RealType b = dist.location();
 
    // if b is 0 avoid divde by 0 error
-   if(abs(b) < std::numeric_limits<RealType>::epsilon())
+   if(abs(b) < boost::math::numeric_limits<RealType>::epsilon())
    {
       result = log(pdf(dist, x));
    }
@@ -194,13 +198,13 @@ inline RealType logpdf(const laplace_distribution<RealType, Policy>& dist, const
 } // logpdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // For ADL of std functions.
 
    RealType result = 0;
    // Checking function argument.
-   const char* function = "boost::math::cdf(const laplace_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const laplace_distribution<%1%>&, %1%)";
    // Check scale and location.
    if (false == dist.check_parameters(function, &result)) return result;
 
@@ -228,13 +232,13 @@ inline RealType cdf(const laplace_distribution<RealType, Policy>& dist, const Re
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType logcdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const laplace_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // For ADL of std functions.
 
    RealType result = 0;
    // Checking function argument.
-   const char* function = "boost::math::logcdf(const laplace_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const laplace_distribution<%1%>&, %1%)";
    // Check scale and location.
    if (false == dist.check_parameters(function, &result)) 
    {
@@ -273,13 +277,13 @@ inline RealType logcdf(const laplace_distribution<RealType, Policy>& dist, const
 } // logcdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const laplace_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const laplace_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING // for ADL of std functions.
 
    // Checking function argument
    RealType result = 0;
-   const char* function = "boost::math::quantile(const laplace_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const laplace_distribution<%1%>&, %1%)";
    if (false == dist.check_parameters(function, &result)) return result;
    if(false == detail::check_probability(function, p, &result, Policy())) return result;
 
@@ -311,7 +315,7 @@ inline RealType quantile(const laplace_distribution<RealType, Policy>& dist, con
 
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
 {
    // Calculate complement of cdf.
    BOOST_MATH_STD_USING // for ADL of std functions
@@ -322,7 +326,7 @@ inline RealType cdf(const complemented2_type<laplace_distribution<RealType, Poli
    RealType result = 0;
 
    // Checking function argument.
-   const char* function = "boost::math::cdf(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
+   constexpr auto function = "boost::math::cdf(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
 
    // Check scale and location.
     if (false == c.dist.check_parameters(function, &result)) return result;
@@ -348,7 +352,7 @@ inline RealType cdf(const complemented2_type<laplace_distribution<RealType, Poli
 } // cdf complement
 
 template <class RealType, class Policy>
-inline RealType logcdf(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
 {
    // Calculate complement of logcdf.
    BOOST_MATH_STD_USING // for ADL of std functions
@@ -359,7 +363,7 @@ inline RealType logcdf(const complemented2_type<laplace_distribution<RealType, P
    RealType result = 0;
 
    // Checking function argument.
-   const char* function = "boost::math::logcdf(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
+   constexpr auto function = "boost::math::logcdf(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
 
    // Check scale and location.
     if (false == c.dist.check_parameters(function, &result)) return result;
@@ -389,7 +393,7 @@ inline RealType logcdf(const complemented2_type<laplace_distribution<RealType, P
 } // cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<laplace_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions.
 
@@ -400,17 +404,17 @@ inline RealType quantile(const complemented2_type<laplace_distribution<RealType,
    RealType result = 0;
 
    // Checking function argument.
-   const char* function = "quantile(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
+   constexpr auto function = "quantile(const complemented2_type<laplace_distribution<%1%>, %1%>&)";
    if (false == c.dist.check_parameters(function, &result)) return result;
    
    // Extreme values.
    if(q == 0)
    {
-       return std::numeric_limits<RealType>::infinity();
+       return boost::math::numeric_limits<RealType>::infinity();
    }
    if(q == 1)
    {
-       return -std::numeric_limits<RealType>::infinity();
+       return -boost::math::numeric_limits<RealType>::infinity();
    }
    if(false == detail::check_probability(function, q, &result, Policy())) return result;
 
@@ -424,49 +428,49 @@ inline RealType quantile(const complemented2_type<laplace_distribution<RealType,
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType mean(const laplace_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const laplace_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType standard_deviation(const laplace_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType standard_deviation(const laplace_distribution<RealType, Policy>& dist)
 {
    return constants::root_two<RealType>() * dist.scale();
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const laplace_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const laplace_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const laplace_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const laplace_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const laplace_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const laplace_distribution<RealType, Policy>& /*dist*/)
 {
    return 0;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const laplace_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const laplace_distribution<RealType, Policy>& /*dist*/)
 {
    return 6;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const laplace_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const laplace_distribution<RealType, Policy>& /*dist*/)
 {
    return 3;
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const laplace_distribution<RealType, Policy> & dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const laplace_distribution<RealType, Policy> & dist)
 {
    using std::log;
    return log(2*dist.scale()*constants::e<RealType>());

From a1d08a514caf49efb73efa3e98beb557a3b8ae2e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:04:02 -0400
Subject: [PATCH 174/399] Add laplace dist CUDA testing

---
 test/cuda_jamfile                |   6 ++
 test/test_laplace_cdf_double.cu  | 110 +++++++++++++++++++++++++++++++
 test/test_laplace_cdf_float.cu   | 110 +++++++++++++++++++++++++++++++
 test/test_laplace_pdf_double.cu  | 110 +++++++++++++++++++++++++++++++
 test/test_laplace_pdf_float.cu   | 110 +++++++++++++++++++++++++++++++
 test/test_laplace_quan_double.cu | 110 +++++++++++++++++++++++++++++++
 test/test_laplace_quan_float.cu  | 110 +++++++++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_laplace_cdf_double.cu
 create mode 100644 test/test_laplace_cdf_float.cu
 create mode 100644 test/test_laplace_pdf_double.cu
 create mode 100644 test/test_laplace_pdf_float.cu
 create mode 100644 test/test_laplace_quan_double.cu
 create mode 100644 test/test_laplace_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 9bc7429c7e..58b5d91729 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -62,6 +62,12 @@ run test_landau_pdf_double.cu ;
 run test_landau_pdf_float.cu ;
 run test_landau_quan_double.cu;
 run test_landau_quan_float.cu ;
+run test_laplace_cdf_double.cu ;
+run test_laplace_cdf_float.cu ;
+run test_laplace_pdf_double.cu ;
+run test_laplace_pdf_float.cu ;
+run test_laplace_quan_double.cu ;
+run test_laplace_quan_float.cu ;
 run test_mapairy_cdf_double.cu ;
 run test_mapairy_cdf_float.cu ;
 run test_mapairy_pdf_double.cu ;
diff --git a/test/test_laplace_cdf_double.cu b/test/test_laplace_cdf_double.cu
new file mode 100644
index 0000000000..cddcfa2bc0
--- /dev/null
+++ b/test/test_laplace_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_laplace_cdf_float.cu b/test/test_laplace_cdf_float.cu
new file mode 100644
index 0000000000..2af43f9f5e
--- /dev/null
+++ b/test/test_laplace_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_laplace_pdf_double.cu b/test/test_laplace_pdf_double.cu
new file mode 100644
index 0000000000..2f53c0dd10
--- /dev/null
+++ b/test/test_laplace_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_laplace_pdf_float.cu b/test/test_laplace_pdf_float.cu
new file mode 100644
index 0000000000..a8d673dba5
--- /dev/null
+++ b/test/test_laplace_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_laplace_quan_double.cu b/test/test_laplace_quan_double.cu
new file mode 100644
index 0000000000..cddcfa2bc0
--- /dev/null
+++ b/test/test_laplace_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_laplace_quan_float.cu b/test/test_laplace_quan_float.cu
new file mode 100644
index 0000000000..2af43f9f5e
--- /dev/null
+++ b/test/test_laplace_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::laplace_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 1aae539ed3718d77e9b2d6596d748282ea1641ea Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:31:39 -0400
Subject: [PATCH 175/399] Add laplace dist SYCL testing

---
 test/sycl_jamfile     | 1 +
 test/test_laplace.cpp | 4 ++--
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 9bf3579806..184920e68d 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -17,6 +17,7 @@ run test_exponential_dist.cpp ;
 run test_extreme_value.cpp ;
 run test_holtsmark.cpp ;
 run test_landau.cpp ;
+run test_laplace.cpp ;
 run test_mapairy.cpp ;
 run test_saspoint5.cpp ;
 
diff --git a/test/test_laplace.cpp b/test/test_laplace.cpp
index df79c8a584..965c4c6575 100644
--- a/test/test_laplace.cpp
+++ b/test/test_laplace.cpp
@@ -1,7 +1,7 @@
 //  Copyright Thijs van den Berg, 2008.
 //  Copyright John Maddock 2008.
 //  Copyright Paul A. Bristow 2008, 2009, 2014.
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -62,7 +62,7 @@ Test 8: test_extreme_function_arguments()
 
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/distributions/laplace.hpp>
 #include "test_out_of_range.hpp"

From 212c47933ca022f78bd007a244f95b7bb2d3b22b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:41:58 -0400
Subject: [PATCH 176/399] Add GPU support to logistic dist

---
 include/boost/math/distributions/logistic.hpp | 69 ++++++++++---------
 1 file changed, 36 insertions(+), 33 deletions(-)

diff --git a/include/boost/math/distributions/logistic.hpp b/include/boost/math/distributions/logistic.hpp
index d12de48c59..4f94bd8a4f 100644
--- a/include/boost/math/distributions/logistic.hpp
+++ b/include/boost/math/distributions/logistic.hpp
@@ -1,5 +1,5 @@
 // Copyright 2008 Gautam Sewani
-//
+// Copyright 2024 Matt Borland
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -8,6 +8,9 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_LOGISTIC
 #define BOOST_MATH_DISTRIBUTIONS_LOGISTIC
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -24,22 +27,22 @@ namespace boost { namespace math {
       typedef RealType value_type;
       typedef Policy policy_type;
       
-      logistic_distribution(RealType l_location=0, RealType l_scale=1) // Constructor.
+      BOOST_MATH_GPU_ENABLED logistic_distribution(RealType l_location=0, RealType l_scale=1) // Constructor.
         : m_location(l_location), m_scale(l_scale) 
       {
-        static const char* function = "boost::math::logistic_distribution<%1%>::logistic_distribution";
+        constexpr auto function = "boost::math::logistic_distribution<%1%>::logistic_distribution";
         
         RealType result;
         detail::check_scale(function, l_scale, &result, Policy());
         detail::check_location(function, l_location, &result, Policy());
       }
       // Accessor functions.
-      RealType scale()const
+      BOOST_MATH_GPU_ENABLED RealType scale()const
       {
         return m_scale;
       }
       
-      RealType location()const
+      BOOST_MATH_GPU_ENABLED RealType location()const
       {
         return m_location;
       }
@@ -60,26 +63,26 @@ namespace boost { namespace math {
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const logistic_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const logistic_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(
-         std::numeric_limits<RealType>::has_infinity ? -std::numeric_limits<RealType>::infinity() : -max_value<RealType>(), 
-         std::numeric_limits<RealType>::has_infinity ? std::numeric_limits<RealType>::infinity() : max_value<RealType>());
+      return boost::math::pair<RealType, RealType>(
+         boost::math::numeric_limits<RealType>::has_infinity ? -boost::math::numeric_limits<RealType>::infinity() : -max_value<RealType>(), 
+         boost::math::numeric_limits<RealType>::has_infinity ? boost::math::numeric_limits<RealType>::infinity() : max_value<RealType>());
     }
     
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const logistic_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const logistic_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + infinity
+      return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + infinity
     }
      
     template <class RealType, class Policy>
-    inline RealType pdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
     {
-       static const char* function = "boost::math::pdf(const logistic_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::pdf(const logistic_distribution<%1%>&, %1%)";
        RealType scale = dist.scale();
        RealType location = dist.location();
        RealType result = 0;
@@ -114,12 +117,12 @@ namespace boost { namespace math {
     } 
     
     template <class RealType, class Policy>
-    inline RealType cdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
     {
        RealType scale = dist.scale();
        RealType location = dist.location();
        RealType result = 0; // of checks.
-       static const char* function = "boost::math::cdf(const logistic_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::cdf(const logistic_distribution<%1%>&, %1%)";
        if(false == detail::check_scale(function, scale, &result, Policy()))
        {
           return result;
@@ -149,12 +152,12 @@ namespace boost { namespace math {
     }
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const logistic_distribution<RealType, Policy>& dist, const RealType& x)
     {
        RealType scale = dist.scale();
        RealType location = dist.location();
        RealType result = 0; // of checks.
-       static const char* function = "boost::math::cdf(const logistic_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::cdf(const logistic_distribution<%1%>&, %1%)";
        if(false == detail::check_scale(function, scale, &result, Policy()))
        {
           return result;
@@ -192,13 +195,13 @@ namespace boost { namespace math {
     } 
     
     template <class RealType, class Policy>
-    inline RealType quantile(const logistic_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const logistic_distribution<RealType, Policy>& dist, const RealType& p)
     {
        BOOST_MATH_STD_USING
        RealType location = dist.location();
        RealType scale = dist.scale();
 
-       static const char* function = "boost::math::quantile(const logistic_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::quantile(const logistic_distribution<%1%>&, %1%)";
 
        RealType result = 0;
        if(false == detail::check_scale(function, scale, &result, Policy()))
@@ -228,13 +231,13 @@ namespace boost { namespace math {
      } // RealType quantile(const logistic_distribution<RealType, Policy>& dist, const RealType& p)
     
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
     {
        BOOST_MATH_STD_USING
        RealType location = c.dist.location();
        RealType scale = c.dist.scale();
        RealType x = c.param;
-       static const char* function = "boost::math::cdf(const complement(logistic_distribution<%1%>&), %1%)";
+       constexpr auto function = "boost::math::cdf(const complement(logistic_distribution<%1%>&), %1%)";
 
        RealType result = 0;
        if(false == detail::check_scale(function, scale, &result, Policy()))
@@ -263,13 +266,13 @@ namespace boost { namespace math {
     } 
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
     {
        BOOST_MATH_STD_USING
        RealType location = c.dist.location();
        RealType scale = c.dist.scale();
        RealType x = c.param;
-       static const char* function = "boost::math::cdf(const complement(logistic_distribution<%1%>&), %1%)";
+       constexpr auto function = "boost::math::cdf(const complement(logistic_distribution<%1%>&), %1%)";
 
        RealType result = 0;
        if(false == detail::check_scale(function, scale, &result, Policy()))
@@ -299,12 +302,12 @@ namespace boost { namespace math {
     }  
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<logistic_distribution<RealType, Policy>, RealType>& c)
     {
        BOOST_MATH_STD_USING
        RealType scale = c.dist.scale();
        RealType location = c.dist.location();
-       static const char* function = "boost::math::quantile(const complement(logistic_distribution<%1%>&), %1%)";
+       constexpr auto function = "boost::math::quantile(const complement(logistic_distribution<%1%>&), %1%)";
        RealType result = 0;
        if(false == detail::check_scale(function, scale, &result, Policy()))
           return result;
@@ -335,13 +338,13 @@ namespace boost { namespace math {
     } 
     
     template <class RealType, class Policy>
-    inline RealType mean(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const logistic_distribution<RealType, Policy>& dist)
     {
       return dist.location();
     } // RealType mean(const logistic_distribution<RealType, Policy>& dist)
     
     template <class RealType, class Policy>
-    inline RealType variance(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const logistic_distribution<RealType, Policy>& dist)
     {
       BOOST_MATH_STD_USING
       RealType scale = dist.scale();
@@ -349,36 +352,36 @@ namespace boost { namespace math {
     } // RealType variance(const logistic_distribution<RealType, Policy>& dist)
     
     template <class RealType, class Policy>
-    inline RealType mode(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const logistic_distribution<RealType, Policy>& dist)
     {
       return dist.location();
     }
     
     template <class RealType, class Policy>
-    inline RealType median(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType median(const logistic_distribution<RealType, Policy>& dist)
     {
       return dist.location();
     }
     template <class RealType, class Policy>
-    inline RealType skewness(const logistic_distribution<RealType, Policy>& /*dist*/)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const logistic_distribution<RealType, Policy>& /*dist*/)
     {
       return 0;
     } // RealType skewness(const logistic_distribution<RealType, Policy>& dist)
     
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const logistic_distribution<RealType, Policy>& /*dist*/)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const logistic_distribution<RealType, Policy>& /*dist*/)
     {
       return static_cast<RealType>(6)/5; 
     } // RealType kurtosis_excess(const logistic_distribution<RealType, Policy>& dist)
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const logistic_distribution<RealType, Policy>& dist)
     {
       return kurtosis_excess(dist) + 3;
     } // RealType kurtosis_excess(const logistic_distribution<RealType, Policy>& dist)
 
     template <class RealType, class Policy>
-    inline RealType entropy(const logistic_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType entropy(const logistic_distribution<RealType, Policy>& dist)
     {
        using std::log;
        return 2 + log(dist.scale());

From 418207d922d1519eef8278d60fad28271a77c236 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:46:59 -0400
Subject: [PATCH 177/399] Add logistic dist CUDA testing

---
 test/cuda_jamfile                 |   6 ++
 test/test_logistic_cdf_double.cu  | 110 ++++++++++++++++++++++++++++++
 test/test_logistic_cdf_float.cu   | 110 ++++++++++++++++++++++++++++++
 test/test_logistic_pdf_double.cu  | 110 ++++++++++++++++++++++++++++++
 test/test_logistic_pdf_float.cu   | 110 ++++++++++++++++++++++++++++++
 test/test_logistic_quan_double.cu | 110 ++++++++++++++++++++++++++++++
 test/test_logistic_quan_float.cu  | 110 ++++++++++++++++++++++++++++++
 7 files changed, 666 insertions(+)
 create mode 100644 test/test_logistic_cdf_double.cu
 create mode 100644 test/test_logistic_cdf_float.cu
 create mode 100644 test/test_logistic_pdf_double.cu
 create mode 100644 test/test_logistic_pdf_float.cu
 create mode 100644 test/test_logistic_quan_double.cu
 create mode 100644 test/test_logistic_quan_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 58b5d91729..824b0ae735 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -68,6 +68,12 @@ run test_laplace_pdf_double.cu ;
 run test_laplace_pdf_float.cu ;
 run test_laplace_quan_double.cu ;
 run test_laplace_quan_float.cu ;
+run test_logistic_cdf_double.cu ;
+run test_logistic_cdf_float.cu ;
+run test_logistic_pdf_double.cu ;
+run test_logistic_pdf_float.cu ;
+run test_logistic_quan_double.cu ;
+run test_logistic_quan_float.cu ;
 run test_mapairy_cdf_double.cu ;
 run test_mapairy_cdf_float.cu ;
 run test_mapairy_pdf_double.cu ;
diff --git a/test/test_logistic_cdf_double.cu b/test/test_logistic_cdf_double.cu
new file mode 100644
index 0000000000..5dd3723c57
--- /dev/null
+++ b/test/test_logistic_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_logistic_cdf_float.cu b/test/test_logistic_cdf_float.cu
new file mode 100644
index 0000000000..89d05747b9
--- /dev/null
+++ b/test/test_logistic_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_logistic_pdf_double.cu b/test/test_logistic_pdf_double.cu
new file mode 100644
index 0000000000..39aaa1597a
--- /dev/null
+++ b/test/test_logistic_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_logistic_pdf_float.cu b/test/test_logistic_pdf_float.cu
new file mode 100644
index 0000000000..279112b995
--- /dev/null
+++ b/test/test_logistic_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(-10000, 10000);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_logistic_quan_double.cu b/test/test_logistic_quan_double.cu
new file mode 100644
index 0000000000..ad929d4424
--- /dev/null
+++ b/test/test_logistic_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_logistic_quan_float.cu b/test/test_logistic_quan_float.cu
new file mode 100644
index 0000000000..81c22ea4b6
--- /dev/null
+++ b/test/test_logistic_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist(0, 1);
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::logistic_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}

From 29c8db5755d5090a694f35b7efd11a562dd56257 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 14:49:29 -0400
Subject: [PATCH 178/399] Add logistic dist SYCL testing

---
 test/sycl_jamfile           |  1 +
 test/test_logistic_dist.cpp | 13 ++++++++-----
 2 files changed, 9 insertions(+), 5 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 184920e68d..6423298069 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -18,6 +18,7 @@ run test_extreme_value.cpp ;
 run test_holtsmark.cpp ;
 run test_landau.cpp ;
 run test_laplace.cpp ;
+run test_logistic_dist.cpp ;
 run test_mapairy.cpp ;
 run test_saspoint5.cpp ;
 
diff --git a/test/test_logistic_dist.cpp b/test/test_logistic_dist.cpp
index 3bb092ce7e..c5114adbd4 100644
--- a/test/test_logistic_dist.cpp
+++ b/test/test_logistic_dist.cpp
@@ -1,6 +1,6 @@
 // Copyright 2008 Gautam Sewani
 // Copyright 2013 Paul A. Bristow
-
+// Copyright 2024 Matt Borland
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -12,11 +12,14 @@
 #endif
 
 #include <boost/config.hpp>
-#ifndef BOOST_NO_EXCEPTIONS
-#define BOOST_MATH_UNDERFLOW_ERROR_POLICY throw_on_error
-#define BOOST_MATH_OVERFLOW_ERROR_POLICY throw_on_error
+#include <boost/math/tools/config.hpp>
+
+#if !defined(BOOST_NO_EXCEPTIONS) && !defined(BOOST_MATH_NO_EXCEPTIONS)
+#  define BOOST_MATH_UNDERFLOW_ERROR_POLICY throw_on_error
+#  define BOOST_MATH_OVERFLOW_ERROR_POLICY throw_on_error
 #endif
-#include <boost/math/tools/test.hpp>
+
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 #include <boost/math/distributions/logistic.hpp>
     using boost::math::logistic_distribution;

From ba56bb4403e6a8827d4f843b8d753cc4d7f86d40 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 16:10:53 -0400
Subject: [PATCH 179/399] Fix macro naming

---
 .../math/distributions/extreme_value.hpp      | 32 +++++++++----------
 1 file changed, 16 insertions(+), 16 deletions(-)

diff --git a/include/boost/math/distributions/extreme_value.hpp b/include/boost/math/distributions/extreme_value.hpp
index c6ee7a59f8..0d638092b5 100644
--- a/include/boost/math/distributions/extreme_value.hpp
+++ b/include/boost/math/distributions/extreme_value.hpp
@@ -39,7 +39,7 @@ namespace detail{
 // Error check:
 //
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline bool verify_scale_b(const char* function, RealType b, RealType* presult, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline bool verify_scale_b(const char* function, RealType b, RealType* presult, const Policy& pol)
 {
    if((b <= 0) || !(boost::math::isfinite)(b))
    {
@@ -86,7 +86,7 @@ extreme_value_distribution(RealType,RealType)->extreme_value_distribution<typena
 #endif
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
    return boost::math::pair<RealType, RealType>(
@@ -95,7 +95,7 @@ BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const extre
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
@@ -103,7 +103,7 @@ BOOST_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const ext
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType pdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -128,7 +128,7 @@ BOOST_GPU_ENABLED inline RealType pdf(const extreme_value_distribution<RealType,
 } // pdf
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType logpdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -153,7 +153,7 @@ BOOST_GPU_ENABLED inline RealType logpdf(const extreme_value_distribution<RealTy
 } // logpdf
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType cdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -179,7 +179,7 @@ BOOST_GPU_ENABLED inline RealType cdf(const extreme_value_distribution<RealType,
 } // cdf
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType logcdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const extreme_value_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -232,7 +232,7 @@ BOOST_MATH_GPU_ENABLED RealType quantile(const extreme_value_distribution<RealTy
 } // quantile
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType cdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -256,7 +256,7 @@ BOOST_GPU_ENABLED inline RealType cdf(const complemented2_type<extreme_value_dis
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType logcdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -308,7 +308,7 @@ RealType quantile(const complemented2_type<extreme_value_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType mean(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const extreme_value_distribution<RealType, Policy>& dist)
 {
    RealType a = dist.location();
    RealType b = dist.scale();
@@ -321,7 +321,7 @@ BOOST_GPU_ENABLED inline RealType mean(const extreme_value_distribution<RealType
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType standard_deviation(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType standard_deviation(const extreme_value_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING // for ADL of std functions.
 
@@ -335,20 +335,20 @@ BOOST_GPU_ENABLED inline RealType standard_deviation(const extreme_value_distrib
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType mode(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const extreme_value_distribution<RealType, Policy>& dist)
 {
    return dist.location();
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType median(const extreme_value_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const extreme_value_distribution<RealType, Policy>& dist)
 {
   using constants::ln_ln_two;
    return dist.location() - dist.scale() * ln_ln_two<RealType>();
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType skewness(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    //
    // This is 12 * sqrt(6) * zeta(3) / pi^3:
@@ -358,14 +358,14 @@ BOOST_GPU_ENABLED inline RealType skewness(const extreme_value_distribution<Real
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType kurtosis(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
    return RealType(27) / 5;
 }
 
 template <class RealType, class Policy>
-BOOST_GPU_ENABLED inline RealType kurtosis_excess(const extreme_value_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const extreme_value_distribution<RealType, Policy>& /*dist*/)
 {
    // See http://mathworld.wolfram.com/ExtremeValueDistribution.html
    return RealType(12) / 5;

From 344541e2c3edb4c5105103eeceb8b3ae083f6eb1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 2 Aug 2024 10:25:52 -0400
Subject: [PATCH 180/399] Fix unused parameter warning

---
 include/boost/math/special_functions/sin_pi.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/sin_pi.hpp b/include/boost/math/special_functions/sin_pi.hpp
index acb5db29e2..3e16bfc96b 100644
--- a/include/boost/math/special_functions/sin_pi.hpp
+++ b/include/boost/math/special_functions/sin_pi.hpp
@@ -24,7 +24,7 @@
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sin_pi_imp(T x, const Policy&)
 {
    BOOST_MATH_STD_USING // ADL of std names
    // sin of pi*x:

From b9f64052b86d49fa4c909871d454a4214fad6fa3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 16:37:39 -0400
Subject: [PATCH 181/399] Add GPU support to sqrt1pm1

---
 include/boost/math/special_functions/sqrt1pm1.hpp | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/special_functions/sqrt1pm1.hpp b/include/boost/math/special_functions/sqrt1pm1.hpp
index 041916a53f..4d8aeb38cf 100644
--- a/include/boost/math/special_functions/sqrt1pm1.hpp
+++ b/include/boost/math/special_functions/sqrt1pm1.hpp
@@ -10,6 +10,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/expm1.hpp>
@@ -21,7 +22,7 @@
 namespace boost{ namespace math{
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type sqrt1pm1(const T& val, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sqrt1pm1(const T& val, const Policy& pol)
 {
    typedef typename tools::promote_args<T>::type result_type;
    BOOST_MATH_STD_USING
@@ -32,7 +33,7 @@ inline typename tools::promote_args<T>::type sqrt1pm1(const T& val, const Policy
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type sqrt1pm1(const T& val)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sqrt1pm1(const T& val)
 {
    return sqrt1pm1(val, policies::policy<>());
 }

From aa5e7e6549bcf0d4d2ca1d5fc5ed476154824c94 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 17:10:15 -0400
Subject: [PATCH 182/399] Add GPU support to continued fractions and remove
 recursion

---
 include/boost/math/tools/fraction.hpp | 125 ++++++++++++++++++++------
 1 file changed, 96 insertions(+), 29 deletions(-)

diff --git a/include/boost/math/tools/fraction.hpp b/include/boost/math/tools/fraction.hpp
index a64c070258..1970e5ca3f 100644
--- a/include/boost/math/tools/fraction.hpp
+++ b/include/boost/math/tools/fraction.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2005-2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,8 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/complex.hpp>
 #include <type_traits>
@@ -25,7 +28,7 @@ namespace detail
    struct is_pair : public std::false_type{};
 
    template <typename T, typename U>
-   struct is_pair<std::pair<T,U>> : public std::true_type{};
+   struct is_pair<boost::math::pair<T,U>> : public std::true_type{};
 
    template <typename Gen>
    struct fraction_traits_simple
@@ -33,11 +36,11 @@ namespace detail
       using result_type = typename Gen::result_type;
       using  value_type = typename Gen::result_type;
 
-      static result_type a(const value_type&) BOOST_MATH_NOEXCEPT(value_type)
+      BOOST_MATH_GPU_ENABLED static result_type a(const value_type&) BOOST_MATH_NOEXCEPT(value_type)
       {
          return 1;
       }
-      static result_type b(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
+      BOOST_MATH_GPU_ENABLED static result_type b(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
       {
          return v;
       }
@@ -49,11 +52,11 @@ namespace detail
       using  value_type = typename Gen::result_type;
       using result_type = typename value_type::first_type;
 
-      static result_type a(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
+      BOOST_MATH_GPU_ENABLED static result_type a(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
       {
          return v.first;
       }
-      static result_type b(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
+      BOOST_MATH_GPU_ENABLED static result_type b(const value_type& v) BOOST_MATH_NOEXCEPT(value_type)
       {
          return v.second;
       }
@@ -74,7 +77,7 @@ namespace detail
       // For float, double, and long double, 1/min_value<T>() is finite.
       // But for mpfr_float and cpp_bin_float, 1/min_value<T>() is inf.
       // Multiply the min by 16 so that the reciprocal doesn't overflow.
-      static T get() {
+      BOOST_MATH_GPU_ENABLED static T get() {
          return 16*tools::min_value<T>();
       }
    };
@@ -82,13 +85,15 @@ namespace detail
    struct tiny_value<T, true>
    {
       using value_type = typename T::value_type;
-      static T get() {
+      BOOST_MATH_GPU_ENABLED static T get() {
          return 16*tools::min_value<value_type>();
       }
    };
 
 } // namespace detail
 
+namespace detail {
+
 //
 // continued_fraction_b
 // Evaluates:
@@ -103,9 +108,15 @@ namespace detail
 //
 // Note that the first a0 returned by generator Gen is discarded.
 //
+
 template <typename Gen, typename U>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, std::uintmax_t& max_terms)
-      noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, std::uintmax_t& max_terms)
+      noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+      #ifndef BOOST_MATH_ENABLE_SYCL
+      // SYCL can not handle this condition so we only check float on that platform
+      && noexcept(std::declval<Gen>()())
+      #endif
+      )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -148,17 +159,38 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(G
    return f;
 }
 
+} // namespace detail
+
+template <typename Gen, typename U>
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, std::uintmax_t& max_terms)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+         #ifndef BOOST_MATH_ENABLE_SYCL
+         && noexcept(std::declval<Gen>()())
+         #endif
+         )
+{
+   return detail::continued_fraction_b_impl(g, factor, max_terms);
+}
+
 template <typename Gen, typename U>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    std::uintmax_t max_terms = (std::numeric_limits<std::uintmax_t>::max)();
-   return continued_fraction_b(g, factor, max_terms);
+   return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -167,12 +199,16 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(G
 
    result_type factor = ldexp(1.0f, 1 - bits); // 1 / pow(result_type(2), bits);
    std::uintmax_t max_terms = (std::numeric_limits<std::uintmax_t>::max)();
-   return continued_fraction_b(g, factor, max_terms);
+   return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, std::uintmax_t& max_terms)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, std::uintmax_t& max_terms)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -180,9 +216,11 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(G
    using result_type = typename traits::result_type;
 
    result_type factor = ldexp(1.0f, 1 - bits); // 1 / pow(result_type(2), bits);
-   return continued_fraction_b(g, factor, max_terms);
+   return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
+namespace detail {
+
 //
 // continued_fraction_a
 // Evaluates:
@@ -198,8 +236,12 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(G
 // Note that the first a1 and b1 returned by generator Gen are both used.
 //
 template <typename Gen, typename U>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, std::uintmax_t& max_terms)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, std::uintmax_t& max_terms)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -244,17 +286,38 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(G
    return a0/f;
 }
 
+} // namespace detail
+
+template <typename Gen, typename U>
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, std::uintmax_t& max_terms)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
+{
+   return detail::continued_fraction_a_impl(g, factor, max_terms);
+}
+
 template <typename Gen, typename U>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type)
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    std::uintmax_t max_iter = (std::numeric_limits<std::uintmax_t>::max)();
-   return continued_fraction_a(g, factor, max_iter);
+   return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
 template <typename Gen>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -264,12 +327,16 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(G
    result_type factor = ldexp(1.0f, 1-bits); // 1 / pow(result_type(2), bits);
    std::uintmax_t max_iter = (std::numeric_limits<std::uintmax_t>::max)();
 
-   return continued_fraction_a(g, factor, max_iter);
+   return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
 template <typename Gen>
-inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, std::uintmax_t& max_terms)
-   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) && noexcept(std::declval<Gen>()()))
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, std::uintmax_t& max_terms)
+   noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
+   #ifndef BOOST_MATH_ENABLE_SYCL
+   && noexcept(std::declval<Gen>()())
+   #endif
+   )
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -277,7 +344,7 @@ inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(G
    using result_type = typename traits::result_type;
 
    result_type factor = ldexp(1.0f, 1-bits); // 1 / pow(result_type(2), bits);
-   return continued_fraction_a(g, factor, max_terms);
+   return detail::continued_fraction_a_impl(g, factor, max_terms);
 }
 
 } // namespace tools

From 51a49ad979f757ca85bd2f565daa230f501e01f8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 17:10:38 -0400
Subject: [PATCH 183/399] Add GPU support to erf and erfc

---
 include/boost/math/special_functions/erf.hpp  | 90 +++++++++++--------
 .../boost/math/special_functions/math_fwd.hpp | 12 +--
 2 files changed, 60 insertions(+), 42 deletions(-)

diff --git a/include/boost/math/special_functions/erf.hpp b/include/boost/math/special_functions/erf.hpp
index 57ff605299..323a91937a 100644
--- a/include/boost/math/special_functions/erf.hpp
+++ b/include/boost/math/special_functions/erf.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -39,7 +40,7 @@ template <class T>
 struct erf_asympt_series_t
 {
    // LCOV_EXCL_START multiprecision case only, excluded from coverage analysis
-   erf_asympt_series_t(T z) : xx(2 * -z * z), tk(1)
+   BOOST_MATH_GPU_ENABLED erf_asympt_series_t(T z) : xx(2 * -z * z), tk(1)
    {
       BOOST_MATH_STD_USING
       result = -exp(-z * z) / sqrt(boost::math::constants::pi<T>());
@@ -48,7 +49,7 @@ struct erf_asympt_series_t
 
    typedef T result_type;
 
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       BOOST_MATH_STD_USING
       T r = result;
@@ -68,33 +69,33 @@ struct erf_asympt_series_t
 // How large z has to be in order to ensure that the series converges:
 //
 template <class T>
-inline float erf_asymptotic_limit_N(const T&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const T&)
 {
    return (std::numeric_limits<float>::max)();
 }
-inline float erf_asymptotic_limit_N(const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const std::integral_constant<int, 24>&)
 {
    return 2.8F;
 }
-inline float erf_asymptotic_limit_N(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const std::integral_constant<int, 53>&)
 {
    return 4.3F;
 }
-inline float erf_asymptotic_limit_N(const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const std::integral_constant<int, 64>&)
 {
    return 4.8F;
 }
-inline float erf_asymptotic_limit_N(const std::integral_constant<int, 106>&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const std::integral_constant<int, 106>&)
 {
    return 6.5F;
 }
-inline float erf_asymptotic_limit_N(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline float erf_asymptotic_limit_N(const std::integral_constant<int, 113>&)
 {
    return 6.8F;
 }
 
 template <class T, class Policy>
-inline T erf_asymptotic_limit()
+BOOST_MATH_GPU_ENABLED inline T erf_asymptotic_limit()
 {
    typedef typename policies::precision<T, Policy>::type precision_type;
    typedef std::integral_constant<int,
@@ -198,7 +199,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const Tag& t)
 }
 
 template <class T, class Policy>
-T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int, 53>& t)
+BOOST_MATH_GPU_ENABLED T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int, 53>& t)
 {
    BOOST_MATH_STD_USING
 
@@ -207,14 +208,30 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
    if ((boost::math::isnan)(z))
       return policies::raise_domain_error("boost::math::erf<%1%>(%1%)", "Expected a finite argument but got %1%", z, pol);
 
+   int prefix_multiplier = 1;
+   int prefix_adder = 0;
+
    if(z < 0)
    {
+      // Recursion is logically simpler here, but confuses static analyzers that need to be
+      // able to calculate the maximimum program stack size at compile time (ie CUDA).
+      z = -z;
       if(!invert)
-         return -erf_imp(T(-z), invert, pol, t);
-      else if(z < T(-0.5))
-         return 2 - erf_imp(T(-z), invert, pol, t);
+      {
+         prefix_multiplier = -1;
+         // return -erf_imp(T(-z), invert, pol, t);
+      }
+      else if(z < -0.5)
+      {
+         prefix_adder = 2;
+         // return 2 - erf_imp(T(-z), invert, pol, t);
+      }
       else
-         return 1 + erf_imp(T(-z), false, pol, t);
+      {
+         invert = false;
+         prefix_adder = 1;
+         // return 1 + erf_imp(T(-z), false, pol, t);
+      }
    }
 
    T result;
@@ -237,7 +254,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          }
          else
          {
-            static const T c = BOOST_MATH_BIG_CONSTANT(T, 53, 0.003379167095512573896158903121545171688);  // LCOV_EXCL_LINE
+            BOOST_MATH_STATIC_LOCAL_VARIABLE const T c = BOOST_MATH_BIG_CONSTANT(T, 53, 0.003379167095512573896158903121545171688);  // LCOV_EXCL_LINE
             result = static_cast<T>(z * 1.125f + z * c);
          }
       }
@@ -248,15 +265,15 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          // Maximum Relative Change in Control Points:   1.155e-04
          // Max Error found at double precision =        2.961182e-17
          // LCOV_EXCL_START
-         static const T Y = 1.044948577880859375f;
-         static const T P[] = {    
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 1.044948577880859375f;
+         BOOST_MATH_STATIC const T P[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0834305892146531832907),
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.338165134459360935041),
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.0509990735146777432841),
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.00772758345802133288487),
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.000322780120964605683831),
          };
-         static const T Q[] = {    
+         BOOST_MATH_STATIC const T Q[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.455004033050794024546),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0875222600142252549554),
@@ -281,8 +298,8 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          // Maximum Relative Change in Control Points:   2.845e-04
          // Max Error found at double precision =        4.841816e-17
          // LCOV_EXCL_START
-         static const T Y = 0.405935764312744140625f;
-         static const T P[] = {    
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 0.405935764312744140625f;
+         BOOST_MATH_STATIC const T P[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.098090592216281240205),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.178114665841120341155),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.191003695796775433986),
@@ -290,7 +307,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0195049001251218801359),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.00180424538297014223957),
          };
-         static const T Q[] = {    
+         BOOST_MATH_STATIC const T Q[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.84759070983002217845),
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.42628004845511324508),
@@ -316,8 +333,8 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          // Expected Error Term:                         3.909e-18
          // Maximum Relative Change in Control Points:   9.886e-05
          // LCOV_EXCL_START
-         static const T Y = 0.50672817230224609375f;
-         static const T P[] = {    
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 0.50672817230224609375f;
+         BOOST_MATH_STATIC const T P[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.0243500476207698441272),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0386540375035707201728),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.04394818964209516296),
@@ -325,7 +342,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.00323962406290842133584),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.000235839115596880717416),
          };
-         static const T Q[] = {    
+         BOOST_MATH_STATIC const T Q[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.53991494948552447182),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.982403709157920235114),
@@ -351,8 +368,8 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          // Maximum Relative Change in Control Points:   2.222e-04
          // Max Error found at double precision =        2.062515e-17
          // LCOV_EXCL_START
-         static const T Y = 0.5405750274658203125f;
-         static const T P[] = {    
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 0.5405750274658203125f;
+         BOOST_MATH_STATIC const T P[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.00295276716530971662634),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0137384425896355332126),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.00840807615555585383007),
@@ -360,7 +377,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.000250269961544794627958),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.113212406648847561139e-4),
          };
-         static const T Q[] = {    
+         BOOST_MATH_STATIC const T Q[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.04217814166938418171),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.442597659481563127003),
@@ -386,8 +403,8 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
          // Expected Error Term:                         2.859e-17
          // Maximum Relative Change in Control Points:   1.357e-05
          // LCOV_EXCL_START
-         static const T Y = 0.5579090118408203125f;
-         static const T P[] = {    
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 0.5579090118408203125f;
+         BOOST_MATH_STATIC const T P[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.00628057170626964891937),
             BOOST_MATH_BIG_CONSTANT(T, 53, 0.0175389834052493308818),
             BOOST_MATH_BIG_CONSTANT(T, 53, -0.212652252872804219852),
@@ -396,7 +413,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
             BOOST_MATH_BIG_CONSTANT(T, 53, -3.22729451764143718517),
             BOOST_MATH_BIG_CONSTANT(T, 53, -2.8175401114513378771),
          };
-         static const T Q[] = {    
+         BOOST_MATH_STATIC const T Q[] = {    
             BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 53, 2.79257750980575282228),
             BOOST_MATH_BIG_CONSTANT(T, 53, 11.0567237927800161565),
@@ -428,10 +445,11 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
 
    if(invert)
    {
-      result = 1 - result;
+      prefix_adder += prefix_multiplier * 1;
+      prefix_multiplier = -prefix_multiplier;
    }
 
-   return result;
+   return prefix_adder + prefix_multiplier * result;
 } // template <class T, class Lanczos>T erf_imp(T z, bool invert, const Lanczos& l, const std::integral_constant<int, 53>& t)
 
 
@@ -1175,7 +1193,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int,
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type erf(T z, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erf(T z, const Policy& /* pol */)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -1208,7 +1226,7 @@ inline typename tools::promote_args<T>::type erf(T z, const Policy& /* pol */)
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type erfc(T z, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erfc(T z, const Policy& /* pol */)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -1241,13 +1259,13 @@ inline typename tools::promote_args<T>::type erfc(T z, const Policy& /* pol */)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type erf(T z)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erf(T z)
 {
    return boost::math::erf(z, policies::policy<>());
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type erfc(T z)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erfc(T z)
 {
    return boost::math::erfc(z, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 5e8153734d..cbfe27e81a 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -156,14 +156,14 @@ namespace boost
 
    // erf & erfc error functions.
    template <class RT> // Error function.
-   tools::promote_args_t<RT> erf(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erf(RT z);
    template <class RT, class Policy> // Error function.
-   tools::promote_args_t<RT> erf(RT z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erf(RT z, const Policy&);
 
    template <class RT>// Error function complement.
-   tools::promote_args_t<RT> erfc(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erfc(RT z);
    template <class RT, class Policy>// Error function complement.
-   tools::promote_args_t<RT> erfc(RT z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erfc(RT z, const Policy&);
 
    template <class RT>// Error function inverse.
    tools::promote_args_t<RT> erf_inv(RT z);
@@ -1272,10 +1272,10 @@ namespace boost
    template <class T> T binomial_coefficient(unsigned n, unsigned k){ return ::boost::math::binomial_coefficient<T, Policy>(n, k, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> erf(RT z) { return ::boost::math::erf(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erf(RT z) { return ::boost::math::erf(z, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> erfc(RT z){ return ::boost::math::erfc(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erfc(RT z){ return ::boost::math::erfc(z, Policy()); }\
 \
    template <class RT>\
    inline boost::math::tools::promote_args_t<RT> erf_inv(RT z) { return ::boost::math::erf_inv(z, Policy()); }\

From 5ab4837495b6922a417c4935faa9f7fec8a37885 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 17:10:47 -0400
Subject: [PATCH 184/399] Add SYCL erf testing

---
 test/sycl_jamfile |  1 +
 test/test_erf.cpp |  4 ++++
 test/test_erf.hpp | 11 +++++++++--
 3 files changed, 14 insertions(+), 2 deletions(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 6423298069..e336523e6c 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -32,3 +32,4 @@ run test_expm1_simple.cpp ;
 run test_log1p_simple.cpp ;
 run test_digamma_simple.cpp ;
 run test_trigamma.cpp ;
+run test_erf.cpp ;
diff --git a/test/test_erf.cpp b/test/test_erf.cpp
index 5359039834..beb521ac4c 100644
--- a/test/test_erf.cpp
+++ b/test/test_erf.cpp
@@ -4,7 +4,11 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#include <boost/math/special_functions/erf.hpp>
 #include "test_erf.hpp"
 
 //
diff --git a/test/test_erf.hpp b/test/test_erf.hpp
index dc42c81248..b70c739530 100644
--- a/test/test_erf.hpp
+++ b/test/test_erf.hpp
@@ -1,9 +1,11 @@
-// Copyright John Maddock 2006.
-// Copyright Paul A. Bristow 2007, 2009
+//  Copyright John Maddock 2006.
+//  Copyright Paul A. Bristow 2007, 2009
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/concepts/real_concept.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
@@ -21,6 +23,11 @@
 #define SC_(x) static_cast<typename table_type<T>::type>(BOOST_JOIN(x, L))
 #endif
 
+#ifdef BOOST_MATH_NO_EXCEPTIONS
+#  undef BOOST_CHECK_THROW
+#  define BOOST_CHECK_THROW(x, y)
+#endif
+
 template <class Real, class T>
 void do_test_erf(const T& data, const char* type_name, const char* test_name)
 {

From 086ba3cd6f98a49e2eb1354f3b7944816003e350 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 17:18:00 -0400
Subject: [PATCH 185/399] Add sqrt1pm1 to fwd

---
 include/boost/math/special_functions/math_fwd.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index cbfe27e81a..c789d82df7 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -600,10 +600,10 @@ namespace boost
 
    // sqrt(1+x) - 1
    template <class T>
-   tools::promote_args_t<T> sqrt1pm1(const T& val);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sqrt1pm1(const T& val);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> sqrt1pm1(const T& val, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sqrt1pm1(const T& val, const Policy&);
 
    // sinus cardinals:
    template <class T>
@@ -1484,7 +1484,7 @@ namespace boost
    powm1(const T1 a, const T2 z){ return boost::math::powm1(a, z, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> sqrt1pm1(const T& val){ return boost::math::sqrt1pm1(val, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sqrt1pm1(const T& val){ return boost::math::sqrt1pm1(val, Policy()); }\
 \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> sinc_pi(T x){ return boost::math::sinc_pi(x, Policy()); }\

From d5b142c0d3988e892ea286c2da26ef8edd198787 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 29 Jul 2024 17:18:42 -0400
Subject: [PATCH 186/399] Add CUDA erf and erfc testing

---
 test/cuda_jamfile        |   4 ++
 test/test_erf_double.cu  | 100 +++++++++++++++++++++++++++++++++++++++
 test/test_erf_float.cu   | 100 +++++++++++++++++++++++++++++++++++++++
 test/test_erfc_double.cu | 100 +++++++++++++++++++++++++++++++++++++++
 test/test_erfc_float.cu  | 100 +++++++++++++++++++++++++++++++++++++++
 5 files changed, 404 insertions(+)
 create mode 100644 test/test_erf_double.cu
 create mode 100644 test/test_erf_float.cu
 create mode 100644 test/test_erfc_double.cu
 create mode 100644 test/test_erfc_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 824b0ae735..2823a966d5 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -99,6 +99,10 @@ run test_cos_pi_double.cu ;
 run test_cos_pi_float.cu ;
 run test_digamma_double.cu ;
 run test_digamma_float.cu ;
+run test_erf_double.cu ;
+run test_erf_float.cu ;
+run test_erfc_double.cu ;
+run test_erfc_float.cu ;
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
 run test_log1p_double.cu ;
diff --git a/test/test_erf_double.cu b/test/test_erf_double.cu
new file mode 100644
index 0000000000..3e8398262a
--- /dev/null
+++ b/test/test_erf_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erf(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erf_float.cu b/test/test_erf_float.cu
new file mode 100644
index 0000000000..6cbd07e6ae
--- /dev/null
+++ b/test/test_erf_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erf(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erfc_double.cu b/test/test_erfc_double.cu
new file mode 100644
index 0000000000..86d3c6e5b4
--- /dev/null
+++ b/test/test_erfc_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erfc(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erfc_float.cu b/test/test_erfc_float.cu
new file mode 100644
index 0000000000..7970063a47
--- /dev/null
+++ b/test/test_erfc_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erfc(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From 00e0aa0fa4fa53aac76a01eca75ea4d842530da8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 08:22:19 -0400
Subject: [PATCH 187/399] Replace integral constant pointers with references

---
 .../boost/math/special_functions/detail/erf_inv.hpp   | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/include/boost/math/special_functions/detail/erf_inv.hpp b/include/boost/math/special_functions/detail/erf_inv.hpp
index 0054a74266..690ea4a44e 100644
--- a/include/boost/math/special_functions/detail/erf_inv.hpp
+++ b/include/boost/math/special_functions/detail/erf_inv.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -23,7 +24,7 @@ namespace detail{
 // this version is for 80-bit long double's and smaller:
 //
 template <class T, class Policy>
-T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constant<int, 64>*)
+T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING // for ADL of std names.
 
@@ -310,12 +311,12 @@ struct erf_roots
 };
 
 template <class T, class Policy>
-T erf_inv_imp(const T& p, const T& q, const Policy& pol, const std::integral_constant<int, 0>*)
+T erf_inv_imp(const T& p, const T& q, const Policy& pol, const std::integral_constant<int, 0>&)
 {
    //
    // Generic version, get a guess that's accurate to 64-bits (10^-19)
    //
-   T guess = erf_inv_imp(p, q, pol, static_cast<std::integral_constant<int, 64> const*>(nullptr));
+   T guess = erf_inv_imp(p, q, pol, std::integral_constant<int, 64>());
    T result;
    //
    // If T has more bit's than 64 in it's mantissa then we need to iterate,
@@ -401,7 +402,7 @@ typename tools::promote_args<T>::type erfc_inv(T z, const Policy& pol)
    // And get the result, negating where required:
    //
    return s * policies::checked_narrowing_cast<result_type, forwarding_policy>(
-      detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), static_cast<tag_type const*>(nullptr)), function);
+      detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), tag_type()), function);
 }
 
 template <class T, class Policy>
@@ -469,7 +470,7 @@ typename tools::promote_args<T>::type erf_inv(T z, const Policy& pol)
    // And get the result, negating where required:
    //
    return s * policies::checked_narrowing_cast<result_type, forwarding_policy>(
-      detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), static_cast<tag_type const*>(nullptr)), function);
+      detail::erf_inv_imp(static_cast<eval_type>(p), static_cast<eval_type>(q), forwarding_policy(), tag_type()), function);
 }
 
 template <class T>

From 623b1fc2fa926d6e4c5852049d747bb0d0514ea6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 08:31:37 -0400
Subject: [PATCH 188/399] Make erf_inv and erfc_inv GPU enabled

---
 .../math/special_functions/detail/erf_inv.hpp | 57 ++++++++++---------
 .../boost/math/special_functions/math_fwd.hpp | 12 ++--
 2 files changed, 35 insertions(+), 34 deletions(-)

diff --git a/include/boost/math/special_functions/detail/erf_inv.hpp b/include/boost/math/special_functions/detail/erf_inv.hpp
index 690ea4a44e..09772632d4 100644
--- a/include/boost/math/special_functions/detail/erf_inv.hpp
+++ b/include/boost/math/special_functions/detail/erf_inv.hpp
@@ -14,6 +14,7 @@
 #pragma warning(disable:4702) // Unreachable code: optimization warning
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <type_traits>
 
 namespace boost{ namespace math{
@@ -24,7 +25,7 @@ namespace detail{
 // this version is for 80-bit long double's and smaller:
 //
 template <class T, class Policy>
-T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING // for ADL of std names.
 
@@ -45,8 +46,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       // Maximum Deviation Found (actual error term at infinite precision) 8.030e-21
       //
       // LCOV_EXCL_START
-      static const float Y = 0.0891314744949340820313f;
-      static const T P[] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.0891314744949340820313f;
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, -0.000508781949658280665617),
          BOOST_MATH_BIG_CONSTANT(T, 64, -0.00836874819741736770379),
          BOOST_MATH_BIG_CONSTANT(T, 64, 0.0334806625409744615033),
@@ -56,7 +57,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
          BOOST_MATH_BIG_CONSTANT(T, 64, 0.00822687874676915743155),
          BOOST_MATH_BIG_CONSTANT(T, 64, -0.00538772965071242932965)
       };
-      static const T Q[] = {
+      BOOST_MATH_STATIC const T Q[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 64, -0.970005043303290640362),
          BOOST_MATH_BIG_CONSTANT(T, 64, -1.56574558234175846809),
@@ -88,8 +89,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       // Maximum Deviation Found (error term) 4.811e-20
       //
       // LCOV_EXCL_START
-      static const float Y = 2.249481201171875f;
-      static const T P[] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 2.249481201171875f;
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, -0.202433508355938759655),
          BOOST_MATH_BIG_CONSTANT(T, 64, 0.105264680699391713268),
          BOOST_MATH_BIG_CONSTANT(T, 64, 8.37050328343119927838),
@@ -100,7 +101,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
          BOOST_MATH_BIG_CONSTANT(T, 64, 21.1294655448340526258),
          BOOST_MATH_BIG_CONSTANT(T, 64, -3.67192254707729348546)
       };
-      static const T Q[] = {
+      BOOST_MATH_STATIC const T Q[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 64, 6.24264124854247537712),
          BOOST_MATH_BIG_CONSTANT(T, 64, 3.9713437953343869095),
@@ -143,8 +144,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       {
          // LCOV_EXCL_START
          // Max error found: 1.089051e-20
-         static const float Y = 0.807220458984375f;
-         static const T P[] = {
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.807220458984375f;
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.131102781679951906451),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.163794047193317060787),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.117030156341995252019),
@@ -157,7 +158,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.285225331782217055858e-7),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.681149956853776992068e-9)
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.46625407242567245975),
             BOOST_MATH_BIG_CONSTANT(T, 64, 5.38168345707006855425),
@@ -176,8 +177,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       {
          // LCOV_EXCL_START
          // Max error found: 8.389174e-21
-         static const float Y = 0.93995571136474609375f;
-         static const T P[] = {
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.93995571136474609375f;
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.0350353787183177984712),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.00222426529213447927281),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.0185573306514231072324),
@@ -188,7 +189,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.230404776911882601748e-9),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.266339227425782031962e-11)
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.3653349817554063097),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.762059164553623404043),
@@ -206,8 +207,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       {
          // LCOV_EXCL_START
          // Max error found: 1.481312e-19
-         static const float Y = 0.98362827301025390625f;
-         static const T P[] = {
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.98362827301025390625f;
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.0167431005076633737133),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.00112951438745580278863),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.00105628862152492910091),
@@ -218,7 +219,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.281128735628831791805e-13),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.99055709973310326855e-16)
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.591429344886417493481),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.138151865749083321638),
@@ -236,8 +237,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       {
          // LCOV_EXCL_START
          // Max error found: 5.697761e-20
-         static const float Y = 0.99714565277099609375f;
-         static const T P[] = {
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.99714565277099609375f;
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.0024978212791898131227),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.779190719229053954292e-5),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.254723037413027451751e-4),
@@ -247,7 +248,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.145596286718675035587e-11),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.116765012397184275695e-17)
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.207123112214422517181),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.0169410838120975906478),
@@ -265,8 +266,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
       {
          // LCOV_EXCL_START
          // Max error found: 1.279746e-20
-         static const float Y = 0.99941349029541015625f;
-         static const T P[] = {
+         BOOST_MATH_STATIC_LOCAL_VARIABLE const float Y = 0.99941349029541015625f;
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.000539042911019078575891),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.28398759004727721098e-6),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.899465114892291446442e-6),
@@ -276,7 +277,7 @@ T erf_inv_imp(const T& p, const T& q, const Policy&, const std::integral_constan
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.135880130108924861008e-14),
             BOOST_MATH_BIG_CONSTANT(T, 64, -0.348890393399948882918e-21)
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.0845746234001899436914),
             BOOST_MATH_BIG_CONSTANT(T, 64, 0.00282092984726264681981),
@@ -345,14 +346,14 @@ T erf_inv_imp(const T& p, const T& q, const Policy& pol, const std::integral_con
 } // namespace detail
 
 template <class T, class Policy>
-typename tools::promote_args<T>::type erfc_inv(T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type erfc_inv(T z, const Policy& pol)
 {
    typedef typename tools::promote_args<T>::type result_type;
 
    //
    // Begin by testing for domain errors, and other special cases:
    //
-   static const char* function = "boost::math::erfc_inv<%1%>(%1%, %1%)";
+   constexpr auto function = "boost::math::erfc_inv<%1%>(%1%, %1%)";
    if((z < 0) || (z > 2))
       return policies::raise_domain_error<result_type>(function, "Argument outside range [0,2] in inverse erfc function (got p=%1%).", z, pol);
    if(z == 0)
@@ -406,14 +407,14 @@ typename tools::promote_args<T>::type erfc_inv(T z, const Policy& pol)
 }
 
 template <class T, class Policy>
-typename tools::promote_args<T>::type erf_inv(T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type erf_inv(T z, const Policy& pol)
 {
    typedef typename tools::promote_args<T>::type result_type;
 
    //
    // Begin by testing for domain errors, and other special cases:
    //
-   static const char* function = "boost::math::erf_inv<%1%>(%1%, %1%)";
+   constexpr auto function = "boost::math::erf_inv<%1%>(%1%, %1%)";
    if((z < -1) || (z > 1))
       return policies::raise_domain_error<result_type>(function, "Argument outside range [-1, 1] in inverse erf function (got p=%1%).", z, pol);
    if(z == 1)
@@ -474,13 +475,13 @@ typename tools::promote_args<T>::type erf_inv(T z, const Policy& pol)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type erfc_inv(T z)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erfc_inv(T z)
 {
    return erfc_inv(z, policies::policy<>());
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type erf_inv(T z)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erf_inv(T z)
 {
    return erf_inv(z, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index c789d82df7..1d22f61b12 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -166,14 +166,14 @@ namespace boost
    BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erfc(RT z, const Policy&);
 
    template <class RT>// Error function inverse.
-   tools::promote_args_t<RT> erf_inv(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erf_inv(RT z);
    template <class RT, class Policy>// Error function inverse.
-   tools::promote_args_t<RT> erf_inv(RT z, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erf_inv(RT z, const Policy& pol);
 
    template <class RT>// Error function complement inverse.
-   tools::promote_args_t<RT> erfc_inv(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erfc_inv(RT z);
    template <class RT, class Policy>// Error function complement inverse.
-   tools::promote_args_t<RT> erfc_inv(RT z, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> erfc_inv(RT z, const Policy& pol);
 
    // Polynomials:
    template <class T1, class T2, class T3>
@@ -1278,10 +1278,10 @@ namespace boost
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erfc(RT z){ return ::boost::math::erfc(z, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> erf_inv(RT z) { return ::boost::math::erf_inv(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erf_inv(RT z) { return ::boost::math::erf_inv(z, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> erfc_inv(RT z){ return ::boost::math::erfc_inv(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erfc_inv(RT z){ return ::boost::math::erfc_inv(z, Policy()); }\
 \
    using boost::math::legendre_next;\
 \

From 9d2f7377712ba3e0821127df03f65f18853be417 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 08:31:49 -0400
Subject: [PATCH 189/399] Add erf_inv and erfc_inv CUDA testing

---
 test/cuda_jamfile            |   4 ++
 test/test_erf_inv_double.cu  | 100 +++++++++++++++++++++++++++++++++++
 test/test_erf_inv_float.cu   | 100 +++++++++++++++++++++++++++++++++++
 test/test_erfc_inv_double.cu | 100 +++++++++++++++++++++++++++++++++++
 test/test_erfc_inv_float.cu  | 100 +++++++++++++++++++++++++++++++++++
 5 files changed, 404 insertions(+)
 create mode 100644 test/test_erf_inv_double.cu
 create mode 100644 test/test_erf_inv_float.cu
 create mode 100644 test/test_erfc_inv_double.cu
 create mode 100644 test/test_erfc_inv_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 2823a966d5..b287cc5b10 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -101,8 +101,12 @@ run test_digamma_double.cu ;
 run test_digamma_float.cu ;
 run test_erf_double.cu ;
 run test_erf_float.cu ;
+run test_erf_inv_double.cu ;
+run test_erf_inv_float.cu ;
 run test_erfc_double.cu ;
 run test_erfc_float.cu ;
+run test_erfc_inv_double.cu ;
+run test_erfc_inv_float.cu ;
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
 run test_log1p_double.cu ;
diff --git a/test/test_erf_inv_double.cu b/test/test_erf_inv_double.cu
new file mode 100644
index 0000000000..f540babbb2
--- /dev/null
+++ b/test/test_erf_inv_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf_inv(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erf_inv(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erf_inv_float.cu b/test/test_erf_inv_float.cu
new file mode 100644
index 0000000000..d9f37687f1
--- /dev/null
+++ b/test/test_erf_inv_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf_inv(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erf_inv(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erfc_inv_double.cu b/test/test_erfc_inv_double.cu
new file mode 100644
index 0000000000..68642cd109
--- /dev/null
+++ b/test/test_erfc_inv_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc_inv(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erfc_inv(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_erfc_inv_float.cu b/test/test_erfc_inv_float.cu
new file mode 100644
index 0000000000..b5b72cd057
--- /dev/null
+++ b/test/test_erfc_inv_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc_inv(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::erfc_inv(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From e4692158fe701757df9a39ddcc022807cad311d4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 08:39:00 -0400
Subject: [PATCH 190/399] Replace igamma_temme_large integral constant pointer
 with reference

---
 .../math/special_functions/detail/igamma_large.hpp  | 13 ++++++++-----
 include/boost/math/special_functions/gamma.hpp      |  2 +-
 2 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/special_functions/detail/igamma_large.hpp b/include/boost/math/special_functions/detail/igamma_large.hpp
index 5483b53fb6..e8162095cc 100644
--- a/include/boost/math/special_functions/detail/igamma_large.hpp
+++ b/include/boost/math/special_functions/detail/igamma_large.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -59,13 +60,15 @@
 #pragma GCC system_header
 #endif
 
+#include <boost/math/tools/config.hpp>
+
 namespace boost{ namespace math{ namespace detail{
 
 // This version will never be called (at runtime), it's a stub used
 // when T is unsuitable to be passed to these routines:
 //
 template <class T, class Policy>
-inline T igamma_temme_large(T, T, const Policy& /* pol */, std::integral_constant<int, 0> const *)
+inline T igamma_temme_large(T, T, const Policy& /* pol */, const std::integral_constant<int, 0>&)
 {
    // stub function, should never actually be called
    BOOST_MATH_ASSERT(0);
@@ -76,7 +79,7 @@ inline T igamma_temme_large(T, T, const Policy& /* pol */, std::integral_constan
 // (80-bit long double, or 10^-20).
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 64> const *)
+T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -281,7 +284,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 64
 // (IEEE double precision or 10^-17).
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 53> const *)
+T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -423,7 +426,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 53
 // (IEEE float precision, or 10^-8)
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 24> const *)
+T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -479,7 +482,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 24
 // require many more terms in the polynomials.
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, std::integral_constant<int, 113> const *)
+T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index a58ea3e693..0c3b32b46c 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -1454,7 +1454,7 @@ T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
             precision_type::value <= 113 ? 113 : 0
          > tag_type;
 
-         result = igamma_temme_large(a, x, pol, static_cast<tag_type const*>(nullptr));
+         result = igamma_temme_large(a, x, pol, tag_type());
          if(x >= a)
             invert = !invert;
          if(p_derivative)

From 4aaa9b7d8f9257126d50b757f97e0427aa7a9598 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 08:40:50 -0400
Subject: [PATCH 191/399] Add GPU support to igamma_temme_large

---
 .../special_functions/detail/igamma_large.hpp | 28 +++++++++----------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/include/boost/math/special_functions/detail/igamma_large.hpp b/include/boost/math/special_functions/detail/igamma_large.hpp
index e8162095cc..1fa13c6921 100644
--- a/include/boost/math/special_functions/detail/igamma_large.hpp
+++ b/include/boost/math/special_functions/detail/igamma_large.hpp
@@ -284,7 +284,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 // (IEEE double precision or 10^-17).
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -296,7 +296,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 
    T workspace[10];
 
-   static const T C0[] = {
+   BOOST_MATH_STATIC const T C0[] = {
       static_cast<T>(-0.33333333333333333L),
       static_cast<T>(0.083333333333333333L),
       static_cast<T>(-0.014814814814814815L),
@@ -315,7 +315,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[0] = tools::evaluate_polynomial(C0, z);
 
-   static const T C1[] = {
+   BOOST_MATH_STATIC const T C1[] = {
       static_cast<T>(-0.0018518518518518519L),
       static_cast<T>(-0.0034722222222222222L),
       static_cast<T>(0.0026455026455026455L),
@@ -332,7 +332,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[1] = tools::evaluate_polynomial(C1, z);
 
-   static const T C2[] = {
+   BOOST_MATH_STATIC const T C2[] = {
       static_cast<T>(0.0041335978835978836L),
       static_cast<T>(-0.0026813271604938272L),
       static_cast<T>(0.00077160493827160494L),
@@ -347,7 +347,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[2] = tools::evaluate_polynomial(C2, z);
 
-   static const T C3[] = {
+   BOOST_MATH_STATIC const T C3[] = {
       static_cast<T>(0.00064943415637860082L),
       static_cast<T>(0.00022947209362139918L),
       static_cast<T>(-0.00046918949439525571L),
@@ -360,7 +360,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[3] = tools::evaluate_polynomial(C3, z);
 
-   static const T C4[] = {
+   BOOST_MATH_STATIC const T C4[] = {
       static_cast<T>(-0.0008618882909167117L),
       static_cast<T>(0.00078403922172006663L),
       static_cast<T>(-0.00029907248030319018L),
@@ -371,7 +371,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[4] = tools::evaluate_polynomial(C4, z);
 
-   static const T C5[] = {
+   BOOST_MATH_STATIC const T C5[] = {
       static_cast<T>(-0.00033679855336635815L),
       static_cast<T>(-0.69728137583658578e-4L),
       static_cast<T>(0.00027727532449593921L),
@@ -384,7 +384,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[5] = tools::evaluate_polynomial(C5, z);
 
-   static const T C6[] = {
+   BOOST_MATH_STATIC const T C6[] = {
       static_cast<T>(0.00053130793646399222L),
       static_cast<T>(-0.00059216643735369388L),
       static_cast<T>(0.00027087820967180448L),
@@ -395,7 +395,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[6] = tools::evaluate_polynomial(C6, z);
 
-   static const T C7[] = {
+   BOOST_MATH_STATIC const T C7[] = {
       static_cast<T>(0.00034436760689237767L),
       static_cast<T>(0.51717909082605922e-4L),
       static_cast<T>(-0.00033493161081142236L),
@@ -404,7 +404,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[7] = tools::evaluate_polynomial(C7, z);
 
-   static const T C8[] = {
+   BOOST_MATH_STATIC const T C8[] = {
       static_cast<T>(-0.00065262391859530942L),
       static_cast<T>(0.00083949872067208728L),
       static_cast<T>(-0.00043829709854172101L),
@@ -426,7 +426,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 // (IEEE float precision, or 10^-8)
 //
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -438,7 +438,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 
    T workspace[3];
 
-   static const T C0[] = {
+   BOOST_MATH_STATIC const T C0[] = {
       static_cast<T>(-0.333333333L),
       static_cast<T>(0.0833333333L),
       static_cast<T>(-0.0148148148L),
@@ -449,7 +449,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[0] = tools::evaluate_polynomial(C0, z);
 
-   static const T C1[] = {
+   BOOST_MATH_STATIC const T C1[] = {
       static_cast<T>(-0.00185185185L),
       static_cast<T>(-0.00347222222L),
       static_cast<T>(0.00264550265L),
@@ -458,7 +458,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[1] = tools::evaluate_polynomial(C1, z);
 
-   static const T C2[] = {
+   BOOST_MATH_STATIC const T C2[] = {
       static_cast<T>(0.00413359788L),
       static_cast<T>(-0.00268132716L),
       static_cast<T>(0.000771604938L),

From 4f2cbbd0d8aeef8c295402f0d6c2ea5ac04eaf68 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 11:52:57 -0400
Subject: [PATCH 192/399] Add GPU support to lgamma_small_imp

---
 .../special_functions/detail/lgamma_small.hpp | 22 ++++++++++---------
 1 file changed, 12 insertions(+), 10 deletions(-)

diff --git a/include/boost/math/special_functions/detail/lgamma_small.hpp b/include/boost/math/special_functions/detail/lgamma_small.hpp
index 6a4a9171fd..a4d3bac70e 100644
--- a/include/boost/math/special_functions/detail/lgamma_small.hpp
+++ b/include/boost/math/special_functions/detail/lgamma_small.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/big_constant.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
@@ -36,7 +38,7 @@ T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos& l);
 // lgamma for small arguments:
 //
 template <class T, class Policy, class Lanczos>
-T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
+BOOST_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
 {
    // This version uses rational approximations for small
    // values of z accurate enough for 64-bit mantissas
@@ -87,7 +89,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
       // At long double: Max error found:               1.987e-21
       // Maximum Deviation Found (approximation error): 5.900e-24
       //
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.180355685678449379109e-1)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.25126649619989678683e-1)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.494103151567532234274e-1)),
@@ -96,7 +98,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.541009869215204396339e-3)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.324588649825948492091e-4))
       };
-      static const T Q[] = {
+      BOOST_MATH_STATIC const T Q[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.1e1)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.196202987197795200688e1)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.148019669424231326694e1)),
@@ -107,7 +109,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.223352763208617092964e-6))
       };
 
-      static const float Y = 0.158963680267333984375e0f;
+      constexpr float Y = 0.158963680267333984375e0f;
 
       T r = zm2 * (z + 1);
       T R = tools::evaluate_polynomial(P, zm2);
@@ -152,9 +154,9 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
          // Expected Error Term:                                 3.139e-021
 
          //
-         static const float Y = 0.52815341949462890625f;
+         constexpr float Y = 0.52815341949462890625f;
 
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.490622454069039543534e-1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.969117530159521214579e-1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.414983358359495381969e0)),
@@ -163,7 +165,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.240149820648571559892e-1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.100346687696279557415e-2))
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.1e1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.302349829846463038743e1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.348739585360723852576e1)),
@@ -197,9 +199,9 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
          // Maximum Deviation Found:                           2.151e-021
          // Expected Error Term:                               2.150e-021
          //
-         static const float Y = 0.452017307281494140625f;
+         constexpr float Y = 0.452017307281494140625f;
 
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.292329721830270012337e-1)), 
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.144216267757192309184e0)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.142440390738631274135e0)),
@@ -207,7 +209,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, co
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.850535976868336437746e-2)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.431171342679297331241e-3))
          };
-         static const T Q[] = {
+         BOOST_MATH_STATIC const T Q[] = {
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.1e1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -0.150169356054485044494e1)),
             static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.846973248876495016101e0)),

From 0a15df8cc8c196d7ea70dafc975f28a235278163 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:10:28 -0400
Subject: [PATCH 193/399] Add additional factorial overloads for GPU times

---
 .../detail/unchecked_factorial.hpp            | 122 +++++++++++++++++-
 1 file changed, 119 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/detail/unchecked_factorial.hpp b/include/boost/math/special_functions/detail/unchecked_factorial.hpp
index b528a24fe9..f7720a2aba 100644
--- a/include/boost/math/special_functions/detail/unchecked_factorial.hpp
+++ b/include/boost/math/special_functions/detail/unchecked_factorial.hpp
@@ -46,6 +46,8 @@ struct max_factorial;
 template <class T, bool = true>
 struct unchecked_factorial_data;
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <bool b>
 struct unchecked_factorial_data<float, b>
 {
@@ -137,17 +139,67 @@ template<bool b>
 
 // Definitions:
 template <>
-inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION float unchecked_factorial<float>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(float))
+BOOST_MATH_GPU_ENABLED inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION float unchecked_factorial<float>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(float))
 {
    return unchecked_factorial_data<float>::factorials[i];
 }
 
+#else
+
+template <>
+BOOST_MATH_GPU_ENABLED inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION float unchecked_factorial<float>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(float))
+{
+   constexpr float factorials[] = {
+      1.0F,
+      1.0F,
+      2.0F,
+      6.0F,
+      24.0F,
+      120.0F,
+      720.0F,
+      5040.0F,
+      40320.0F,
+      362880.0F,
+      3628800.0F,
+      39916800.0F,
+      479001600.0F,
+      6227020800.0F,
+      87178291200.0F,
+      1307674368000.0F,
+      20922789888000.0F,
+      355687428096000.0F,
+      6402373705728000.0F,
+      121645100408832000.0F,
+      0.243290200817664e19F,
+      0.5109094217170944e20F,
+      0.112400072777760768e22F,
+      0.2585201673888497664e23F,
+      0.62044840173323943936e24F,
+      0.15511210043330985984e26F,
+      0.403291461126605635584e27F,
+      0.10888869450418352160768e29F,
+      0.304888344611713860501504e30F,
+      0.8841761993739701954543616e31F,
+      0.26525285981219105863630848e33F,
+      0.822283865417792281772556288e34F,
+      0.26313083693369353016721801216e36F,
+      0.868331761881188649551819440128e37F,
+      0.29523279903960414084761860964352e39F,
+   };
+
+   return factorials[i];
+}
+
+#endif
+
 template <>
 struct max_factorial<float>
 {
    static constexpr unsigned value = 34;
 };
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <bool b>
 struct unchecked_factorial_data<double, b>
 {
@@ -510,7 +562,7 @@ template <bool b>
 #endif
 
 template <>
-inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION double unchecked_factorial<double>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(double))
+BOOST_MATH_GPU_ENABLED inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION double unchecked_factorial<double>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(double))
 {
    return unchecked_factorial_data<double>::factorials[i];
 }
@@ -521,6 +573,62 @@ struct max_factorial<double>
    static constexpr unsigned value = 170;
 };
 
+#else
+
+template <>
+BOOST_MATH_GPU_ENABLED inline BOOST_MATH_CONSTEXPR_TABLE_FUNCTION double unchecked_factorial<double>(unsigned i BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(double))
+{
+   constexpr double factorials[] = {
+      1,
+      1,
+      2,
+      6,
+      24,
+      120,
+      720,
+      5040,
+      40320,
+      362880.0,
+      3628800.0,
+      39916800.0,
+      479001600.0,
+      6227020800.0,
+      87178291200.0,
+      1307674368000.0,
+      20922789888000.0,
+      355687428096000.0,
+      6402373705728000.0,
+      121645100408832000.0,
+      0.243290200817664e19,
+      0.5109094217170944e20,
+      0.112400072777760768e22,
+      0.2585201673888497664e23,
+      0.62044840173323943936e24,
+      0.15511210043330985984e26,
+      0.403291461126605635584e27,
+      0.10888869450418352160768e29,
+      0.304888344611713860501504e30,
+      0.8841761993739701954543616e31,
+      0.26525285981219105863630848e33,
+      0.822283865417792281772556288e34,
+      0.26313083693369353016721801216e36,
+      0.868331761881188649551819440128e37,
+      0.29523279903960414084761860964352e39,
+   };
+
+   return factorials[i];
+}
+
+template <>
+struct max_factorial<double>
+{
+   static constexpr unsigned value = 34;
+};
+
+#endif
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <bool b>
 struct unchecked_factorial_data<long double, b>
 {
@@ -1556,6 +1664,8 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 0
    return factorials[i];
 }
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T>
 inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, std::numeric_limits<float>::digits>&)
 {
@@ -1568,6 +1678,8 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, s
    return unchecked_factorial<double>(i);
 }
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 #if DBL_MANT_DIG != LDBL_MANT_DIG
 template <class T>
 inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, LDBL_MANT_DIG>&)
@@ -1583,6 +1695,8 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 1
 }
 #endif
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T>
 inline T unchecked_factorial(unsigned i)
 {
@@ -1601,9 +1715,11 @@ struct max_factorial
 {
    static constexpr unsigned value = 
       std::numeric_limits<T>::digits == std::numeric_limits<float>::digits ? max_factorial<float>::value 
-      : std::numeric_limits<T>::digits == std::numeric_limits<double>::digits ? max_factorial<double>::value 
+      : std::numeric_limits<T>::digits == std::numeric_limits<double>::digits ? max_factorial<double>::value
+      #ifndef BOOST_MATH_GPU_ENABLED 
       : std::numeric_limits<T>::digits == std::numeric_limits<long double>::digits ? max_factorial<long double>::value 
       BOOST_MATH_DETAIL_FLOAT128_MAX_FACTORIAL
+      #endif
       : 100;
 };
 

From 4d513296654eb25d458b2eed5ee1c9ba43492fba Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:10:41 -0400
Subject: [PATCH 194/399] Add GPU support to lgamma_small

---
 include/boost/math/special_functions/detail/lgamma_small.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/detail/lgamma_small.hpp b/include/boost/math/special_functions/detail/lgamma_small.hpp
index a4d3bac70e..82a1761f19 100644
--- a/include/boost/math/special_functions/detail/lgamma_small.hpp
+++ b/include/boost/math/special_functions/detail/lgamma_small.hpp
@@ -30,7 +30,7 @@ namespace boost{ namespace math{ namespace detail{
 // These need forward declaring to keep GCC happy:
 //
 template <class T, class Policy, class Lanczos>
-T gamma_imp(T z, const Policy& pol, const Lanczos& l);
+BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l);
 template <class T, class Policy>
 T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos& l);
 

From 540c715c6b5fc6c1eca7bf4e9fc47d3b0e21837b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:10:59 -0400
Subject: [PATCH 195/399] Fix signbit GPU support

---
 include/boost/math/special_functions/sign.hpp | 25 ++++++++++++++++---
 1 file changed, 21 insertions(+), 4 deletions(-)

diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index cd7fdfb2ab..2092a41bb2 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -26,9 +26,10 @@ namespace detail {
 
 #ifdef BOOST_MATH_USE_STD_FPCLASSIFY
     template<class T> 
-    inline int signbit_impl(T x, native_tag const&)
+    BOOST_MATH_GPU_ENABLED inline int signbit_impl(T x, native_tag const&)
     {
-        return (std::signbit)(x) ? 1 : 0;
+        using std::signbit;
+        return (signbit)(x) ? 1 : 0;
     }
 #endif
 
@@ -66,7 +67,7 @@ namespace detail {
 #endif
 
     template<class T>
-    inline int signbit_impl(T x, ieee_copy_all_bits_tag const&)
+    BOOST_MATH_GPU_ENABLED inline int signbit_impl(T x, ieee_copy_all_bits_tag const&)
     {
         typedef typename fp_traits<T>::type traits;
 
@@ -76,7 +77,7 @@ namespace detail {
     }
 
     template<class T> 
-    inline int signbit_impl(T x, ieee_copy_leading_bits_tag const&)
+    BOOST_MATH_GPU_ENABLED inline int signbit_impl(T x, ieee_copy_leading_bits_tag const&)
     {
         typedef typename fp_traits<T>::type traits;
 
@@ -161,6 +162,22 @@ BOOST_MATH_GPU_ENABLED int (signbit)(T x)
    return detail::signbit_impl(static_cast<result_type>(x), method());
 }
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+template<>
+BOOST_MATH_GPU_ENABLED int signbit<float>(float x)
+{
+    using std::signbit;
+    return (signbit)(x);
+}
+
+template<>
+BOOST_MATH_GPU_ENABLED int signbit<double>(double x)
+{
+    using std::signbit;
+    return (signbit)(x);
+}
+#endif
+
 template <class T>
 BOOST_MATH_GPU_ENABLED inline int sign BOOST_NO_MACRO_EXPAND(const T& z)
 {

From 2bfb2b516d49ddd8180bbc94545a5c192b0bc2b0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:11:16 -0400
Subject: [PATCH 196/399] Support GPU with root epsilon functions

---
 include/boost/math/tools/precision.hpp | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index b9577efeee..877d231f1d 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -316,13 +316,13 @@ BOOST_MATH_GPU_ENABLED constexpr long double epsilon(BOOST_MATH_EXPLICIT_TEMPLAT
 namespace detail{
 
 template <class T>
-inline constexpr T root_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(0.00034526698300124390839884978618400831996329879769945L);
 }
 
 template <class T>
-inline constexpr T root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(0.1490116119384765625e-7L);
 }
@@ -355,13 +355,13 @@ inline T root_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(0.0049215666011518482998719164346805794944150447839903L);
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(6.05545445239333906078989272793696693569753008995e-6L);
 }
@@ -394,13 +394,13 @@ inline T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(0.018581361171917516667460937040007436176452688944747L);
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
 {
    return static_cast<T>(0.0001220703125L);
 }
@@ -442,19 +442,19 @@ struct root_epsilon_traits
 }
 
 template <class T>
-inline constexpr T root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::root_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::cbrt_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::forth_root_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }

From 10e7e1b93c8d1f7bf6715d2932a42689eb3878d5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:11:35 -0400
Subject: [PATCH 197/399] Add GPU support to gamma functions

---
 .../boost/math/special_functions/gamma.hpp    | 148 +++++++++---------
 1 file changed, 76 insertions(+), 72 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 0c3b32b46c..b77f4f5eaa 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -2,7 +2,7 @@
 //  Copyright Paul A. Bristow 2007, 2013-14.
 //  Copyright Nikhar Agrawal 2013-14
 //  Copyright Christopher Kormanyos 2013-14, 2020, 2024
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -14,12 +14,12 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/fraction.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/promotion.hpp>
 #include <boost/math/tools/assert.hpp>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -56,13 +56,13 @@ namespace boost{ namespace math{
 namespace detail{
 
 template <class T>
-inline bool is_odd(T v, const std::true_type&)
+BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const std::true_type&)
 {
    int i = static_cast<int>(v);
    return i&1;
 }
 template <class T>
-inline bool is_odd(T v, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const std::false_type&)
 {
    // Oh dear can't cast T to int!
    BOOST_MATH_STD_USING
@@ -70,13 +70,13 @@ inline bool is_odd(T v, const std::false_type&)
    return static_cast<bool>(modulus != 0);
 }
 template <class T>
-inline bool is_odd(T v)
+BOOST_MATH_GPU_ENABLED inline bool is_odd(T v)
 {
    return is_odd(v, ::std::is_convertible<T, int>());
 }
 
 template <class T>
-T sinpx(T z)
+BOOST_MATH_GPU_ENABLED T sinpx(T z)
 {
    // Ad hoc function calculates x * sin(pi * x),
    // taking extra care near when x is near a whole number.
@@ -108,7 +108,7 @@ T sinpx(T z)
 // tgamma(z), with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
-T gamma_imp(T z, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
 
@@ -122,7 +122,7 @@ T gamma_imp(T z, const Policy& pol, const Lanczos& l)
       b = true;
    }
 #endif
-   static const char* function = "boost::math::tgamma<%1%>(%1%)";
+   constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
 
    if(z <= 0)
    {
@@ -199,7 +199,7 @@ T gamma_imp(T z, const Policy& pol, const Lanczos& l)
 // lgamma(z) with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
-T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
+BOOST_MATH_GPU_ENABLED T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
 {
 #ifdef BOOST_MATH_INSTRUMENT
    static bool b = false;
@@ -212,7 +212,7 @@ T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
 
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::lgamma<%1%>(%1%)";
+   constexpr auto function = "boost::math::lgamma<%1%>(%1%)";
 
    T result = 0;
    int sresult = 1;
@@ -291,12 +291,12 @@ struct upper_incomplete_gamma_fract
 public:
    typedef std::pair<T,T> result_type;
 
-   upper_incomplete_gamma_fract(T a1, T z1)
+   BOOST_MATH_GPU_ENABLED upper_incomplete_gamma_fract(T a1, T z1)
       : z(z1-a1+1), a(a1), k(0)
    {
    }
 
-   result_type operator()()
+   BOOST_MATH_GPU_ENABLED result_type operator()()
    {
       ++k;
       z += 2;
@@ -305,7 +305,7 @@ struct upper_incomplete_gamma_fract
 };
 
 template <class T>
-inline T upper_gamma_fraction(T a, T z, T eps)
+BOOST_MATH_GPU_ENABLED inline T upper_gamma_fraction(T a, T z, T eps)
 {
    // Multiply result by z^a * e^-z to get the full
    // upper incomplete integral.  Divide by tgamma(z)
@@ -321,9 +321,9 @@ struct lower_incomplete_gamma_series
    T a, z, result;
 public:
    typedef T result_type;
-   lower_incomplete_gamma_series(T a1, T z1) : a(a1), z(z1), result(1){}
+   BOOST_MATH_GPU_ENABLED lower_incomplete_gamma_series(T a1, T z1) : a(a1), z(z1), result(1){}
 
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = result;
       a += 1;
@@ -333,7 +333,7 @@ struct lower_incomplete_gamma_series
 };
 
 template <class T, class Policy>
-inline T lower_gamma_series(T a, T z, const Policy& pol, T init_value = 0)
+BOOST_MATH_GPU_ENABLED inline T lower_gamma_series(T a, T z, const Policy& pol, T init_value = 0)
 {
    // Multiply result by ((z^a) * (e^-z) / a) to get the full
    // lower incomplete integral. Then divide by tgamma(a)
@@ -460,7 +460,7 @@ T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&)
 {
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::tgamma<%1%>(%1%)";
+   constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
 
    // Check if the argument of tgamma is identically zero.
    const bool is_at_zero = (z == 0);
@@ -610,7 +610,7 @@ T lgamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&, int* sig
 {
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::lgamma<%1%>(%1%)";
+   constexpr auto function = "boost::math::lgamma<%1%>(%1%)";
 
    // Check if the argument of lgamma is identically zero.
    const bool is_at_zero = (z == 0);
@@ -720,7 +720,7 @@ T lgamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&, int* sig
 // used by the upper incomplete gamma with z < 1:
 //
 template <class T, class Policy, class Lanczos>
-T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
 
@@ -789,9 +789,9 @@ struct small_gamma2_series
 {
    typedef T result_type;
 
-   small_gamma2_series(T a_, T x_) : result(-x_), x(-x_), apn(a_+1), n(1){}
+   BOOST_MATH_GPU_ENABLED small_gamma2_series(T a_, T x_) : result(-x_), x(-x_), apn(a_+1), n(1){}
 
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = result / (apn);
       result *= x;
@@ -809,7 +809,7 @@ struct small_gamma2_series
 // incomplete gammas:
 //
 template <class T, class Policy>
-T full_igamma_prefix(T a, T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T full_igamma_prefix(T a, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -864,7 +864,7 @@ T full_igamma_prefix(T a, T z, const Policy& pol)
 // most if the error occurs in this function:
 //
 template <class T, class Policy, class Lanczos>
-T regularised_gamma_prefix(T a, T z, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T regularised_gamma_prefix(T a, T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
    if (z >= tools::max_value<T>())
@@ -1017,7 +1017,7 @@ T regularised_gamma_prefix(T a, T z, const Policy& pol, const lanczos::undefined
 // Upper gamma fraction for very small a:
 //
 template <class T, class Policy>
-inline T tgamma_small_upper_part(T a, T x, const Policy& pol, T* pgam = 0, bool invert = false, T* pderivative = 0)
+BOOST_MATH_GPU_ENABLED inline T tgamma_small_upper_part(T a, T x, const Policy& pol, T* pgam = 0, bool invert = false, T* pderivative = 0)
 {
    BOOST_MATH_STD_USING  // ADL of std functions.
    //
@@ -1047,7 +1047,7 @@ inline T tgamma_small_upper_part(T a, T x, const Policy& pol, T* pgam = 0, bool
 // Upper gamma fraction for integer a:
 //
 template <class T, class Policy>
-inline T finite_gamma_q(T a, T x, Policy const& pol, T* pderivative = 0)
+BOOST_MATH_GPU_ENABLED inline T finite_gamma_q(T a, T x, Policy const& pol, T* pderivative = 0)
 {
    //
    // Calculates normalised Q when a is an integer:
@@ -1075,7 +1075,7 @@ inline T finite_gamma_q(T a, T x, Policy const& pol, T* pderivative = 0)
 // Upper gamma fraction for half integer a:
 //
 template <class T, class Policy>
-T finite_half_gamma_q(T a, T x, T* p_derivative, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T finite_half_gamma_q(T a, T x, T* p_derivative, const Policy& pol)
 {
    //
    // Calculates normalised Q when a is a half-integer:
@@ -1115,9 +1115,9 @@ template <class T>
 struct incomplete_tgamma_large_x_series
 {
    typedef T result_type;
-   incomplete_tgamma_large_x_series(const T& a, const T& x)
+   BOOST_MATH_GPU_ENABLED incomplete_tgamma_large_x_series(const T& a, const T& x)
       : a_poch(a - 1), z(x), term(1) {}
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T result = term;
       term *= a_poch / z;
@@ -1128,7 +1128,7 @@ struct incomplete_tgamma_large_x_series
 };
 
 template <class T, class Policy>
-T incomplete_tgamma_large_x(const T& a, const T& x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T incomplete_tgamma_large_x(const T& a, const T& x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    incomplete_tgamma_large_x_series<T> s(a, x);
@@ -1143,10 +1143,10 @@ T incomplete_tgamma_large_x(const T& a, const T& x, const Policy& pol)
 // Main incomplete gamma entry point, handles all four incomplete gamma's:
 //
 template <class T, class Policy>
-T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
+BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
                        const Policy& pol, T* p_derivative)
 {
-   static const char* function = "boost::math::gamma_p<%1%>(%1%, %1%)";
+   constexpr auto function = "boost::math::gamma_p<%1%>(%1%, %1%)";
    if(a <= 0)
       return policies::raise_domain_error<T>(function, "Argument a to the incomplete gamma function must be greater than zero (got a=%1%).", a, pol);
    if(x < 0)
@@ -1529,7 +1529,7 @@ T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
 // Ratios of two gamma functions:
 //
 template <class T, class Policy, class Lanczos>
-T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
    if(z < tools::epsilon<T>())
@@ -1648,7 +1648,7 @@ T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const lanczos:
 }
 
 template <class T, class Policy>
-T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -1706,7 +1706,7 @@ T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
 }
 
 template <class T, class Policy>
-T tgamma_ratio_imp(T x, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T tgamma_ratio_imp(T x, T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -1775,7 +1775,7 @@ T tgamma_ratio_imp(T x, T y, const Policy& pol)
 }
 
 template <class T, class Policy>
-T gamma_p_derivative_imp(T a, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T gamma_p_derivative_imp(T a, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    //
@@ -1816,7 +1816,7 @@ T gamma_p_derivative_imp(T a, T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    tgamma(T z, const Policy& /* pol */, const std::true_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1837,7 +1837,7 @@ struct igamma_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
 
@@ -1851,24 +1851,26 @@ struct igamma_initializer
          do_init(tag_type());
       }
       template <int N>
-      static void do_init(const std::integral_constant<int, N>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, N>&)
       {
          // If std::numeric_limits<T>::digits is zero, we must not call
          // our initialization code here as the precision presumably
          // varies at runtime, and will not have been set yet.  Plus the
          // code requiring initialization isn't called when digits == 0.
-         if(std::numeric_limits<T>::digits)
+         BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<T>::digits)
          {
             boost::math::gamma_p(static_cast<T>(400), static_cast<T>(400), Policy());
          }
       }
-      static void do_init(const std::integral_constant<int, 53>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 53>&){}
       void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -1880,7 +1882,7 @@ struct lgamma_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
          typedef std::integral_constant<int,
@@ -1891,28 +1893,30 @@ struct lgamma_initializer
 
          do_init(tag_type());
       }
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 64>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
-      static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 113>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.5), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
-      static void do_init(const std::integral_constant<int, 0>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 0>&)
       {
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -1920,7 +1924,7 @@ template <class T, class Policy>
 const typename lgamma_initializer<T, Policy>::init lgamma_initializer<T, Policy>::initializer;
 
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const Policy&, const std::false_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1943,7 +1947,7 @@ inline tools::promote_args_t<T1, T2>
 }
 
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const std::false_type& tag)
 {
    return tgamma(a, z, policies::policy<>(), tag);
@@ -1953,14 +1957,14 @@ inline tools::promote_args_t<T1, T2>
 } // namespace detail
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    tgamma(T z)
 {
    return tgamma(z, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    lgamma(T z, int* sign, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -1980,28 +1984,28 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    lgamma(T z, int* sign)
 {
    return lgamma(z, sign, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    lgamma(T x, const Policy& pol)
 {
    return ::boost::math::lgamma(x, nullptr, pol);
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    lgamma(T x)
 {
    return ::boost::math::lgamma(x, nullptr, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    tgamma1pm1(T z, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2019,7 +2023,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    tgamma1pm1(T z)
 {
    return tgamma1pm1(z, policies::policy<>());
@@ -2029,7 +2033,7 @@ inline typename tools::promote_args<T>::type
 // Full upper incomplete gamma:
 //
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z)
 {
    //
@@ -2041,7 +2045,7 @@ inline tools::promote_args_t<T1, T2>
    return static_cast<result_type>(detail::tgamma(a, z, maybe_policy()));
 }
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const Policy& pol)
 {
    using result_type = tools::promote_args_t<T1, T2>;
@@ -2051,7 +2055,7 @@ inline tools::promote_args_t<T1, T2>
 // Full lower incomplete gamma:
 //
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_lower(T1 a, T2 z, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2073,7 +2077,7 @@ inline tools::promote_args_t<T1, T2>
       forwarding_policy(), static_cast<value_type*>(nullptr)), "tgamma_lower<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_lower(T1 a, T2 z)
 {
    return tgamma_lower(a, z, policies::policy<>());
@@ -2082,7 +2086,7 @@ inline tools::promote_args_t<T1, T2>
 // Regularised upper incomplete gamma:
 //
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_q(T1 a, T2 z, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2104,7 +2108,7 @@ inline tools::promote_args_t<T1, T2>
       forwarding_policy(), static_cast<value_type*>(nullptr)), "gamma_q<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_q(T1 a, T2 z)
 {
    return gamma_q(a, z, policies::policy<>());
@@ -2113,7 +2117,7 @@ inline tools::promote_args_t<T1, T2>
 // Regularised lower incomplete gamma:
 //
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_p(T1 a, T2 z, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2135,7 +2139,7 @@ inline tools::promote_args_t<T1, T2>
       forwarding_policy(), static_cast<value_type*>(nullptr)), "gamma_p<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_p(T1 a, T2 z)
 {
    return gamma_p(a, z, policies::policy<>());
@@ -2143,7 +2147,7 @@ inline tools::promote_args_t<T1, T2>
 
 // ratios of gamma functions:
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_delta_ratio(T1 z, T2 delta, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2159,13 +2163,13 @@ inline tools::promote_args_t<T1, T2>
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::tgamma_delta_ratio_imp(static_cast<value_type>(z), static_cast<value_type>(delta), forwarding_policy()), "boost::math::tgamma_delta_ratio<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_delta_ratio(T1 z, T2 delta)
 {
    return tgamma_delta_ratio(z, delta, policies::policy<>());
 }
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_ratio(T1 a, T2 b, const Policy&)
 {
    typedef tools::promote_args_t<T1, T2> result_type;
@@ -2180,14 +2184,14 @@ inline tools::promote_args_t<T1, T2>
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::tgamma_ratio_imp(static_cast<value_type>(a), static_cast<value_type>(b), forwarding_policy()), "boost::math::tgamma_delta_ratio<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma_ratio(T1 a, T2 b)
 {
    return tgamma_ratio(a, b, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_p_derivative(T1 a, T2 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
@@ -2203,7 +2207,7 @@ inline tools::promote_args_t<T1, T2>
    return policies::checked_narrowing_cast<result_type, forwarding_policy>(detail::gamma_p_derivative_imp(static_cast<value_type>(a), static_cast<value_type>(x), forwarding_policy()), "boost::math::gamma_p_derivative<%1%>(%1%, %1%)");
 }
 template <class T1, class T2>
-inline tools::promote_args_t<T1, T2>
+BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    gamma_p_derivative(T1 a, T2 x)
 {
    return gamma_p_derivative(a, x, policies::policy<>());

From 80f0ffffd9d20ebd4509698b6f7ad140c3ab1030 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:11:55 -0400
Subject: [PATCH 198/399] Add GPU markers to math_fwd for gamma functions

---
 .../boost/math/special_functions/math_fwd.hpp | 66 +++++++++----------
 1 file changed, 33 insertions(+), 33 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 1d22f61b12..fdccfad8b4 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -424,7 +424,7 @@ namespace boost
    template <class RT, class Policy>
    RT factorial(unsigned int, const Policy& pol);
    template <class RT>
-   RT unchecked_factorial(unsigned int BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(RT));
+   BOOST_MATH_GPU_ENABLED RT unchecked_factorial(unsigned int BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(RT));
    template <class RT>
    RT double_factorial(unsigned i);
    template <class RT, class Policy>
@@ -444,67 +444,67 @@ namespace boost
 
    // Gamma functions.
    template <class RT>
-   tools::promote_args_t<RT> tgamma(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> tgamma(RT z);
 
    template <class RT>
-   tools::promote_args_t<RT> tgamma1pm1(RT z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> tgamma1pm1(RT z);
 
    template <class RT, class Policy>
-   tools::promote_args_t<RT> tgamma1pm1(RT z, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> tgamma1pm1(RT z, const Policy& pol);
 
    template <class RT1, class RT2>
-   tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z);
 
    template <class RT1, class RT2, class Policy>
-   tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z, const Policy& pol);
 
    template <class RT>
-   tools::promote_args_t<RT> lgamma(RT z, int* sign);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> lgamma(RT z, int* sign);
 
    template <class RT, class Policy>
-   tools::promote_args_t<RT> lgamma(RT z, int* sign, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> lgamma(RT z, int* sign, const Policy& pol);
 
    template <class RT>
-   tools::promote_args_t<RT> lgamma(RT x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> lgamma(RT x);
 
    template <class RT, class Policy>
-   tools::promote_args_t<RT> lgamma(RT x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> lgamma(RT x, const Policy& pol);
 
    template <class RT1, class RT2>
-   tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z);
 
    template <class RT1, class RT2, class Policy>
-   tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z, const Policy&);
 
    template <class RT1, class RT2>
-   tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z);
 
    template <class RT1, class RT2, class Policy>
-   tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z, const Policy&);
 
    template <class RT1, class RT2>
-   tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z);
 
    template <class RT1, class RT2, class Policy>
-   tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x, const Policy&);
 
    // gamma inverse.
    template <class T1, class T2>
@@ -1410,37 +1410,37 @@ namespace boost
    inline boost::math::tools::promote_args_t<RT> rising_factorial(RT x, unsigned n){ return boost::math::rising_factorial(x, n, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> tgamma(RT z){ return boost::math::tgamma(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> tgamma(RT z){ return boost::math::tgamma(z, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> tgamma1pm1(RT z){ return boost::math::tgamma1pm1(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> tgamma1pm1(RT z){ return boost::math::tgamma1pm1(z, Policy()); }\
 \
    template <class RT1, class RT2>\
-   inline boost::math::tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z){ return boost::math::tgamma(a, z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z){ return boost::math::tgamma(a, z, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> lgamma(RT z, int* sign){ return boost::math::lgamma(z, sign, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> lgamma(RT z, int* sign){ return boost::math::lgamma(z, sign, Policy()); }\
 \
    template <class RT>\
-   inline boost::math::tools::promote_args_t<RT> lgamma(RT x){ return boost::math::lgamma(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> lgamma(RT x){ return boost::math::lgamma(x, Policy()); }\
 \
    template <class RT1, class RT2>\
-   inline boost::math::tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z){ return boost::math::tgamma_lower(a, z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2> tgamma_lower(RT1 a, RT2 z){ return boost::math::tgamma_lower(a, z, Policy()); }\
 \
    template <class RT1, class RT2>\
-   inline boost::math::tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z){ return boost::math::gamma_q(a, z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2> gamma_q(RT1 a, RT2 z){ return boost::math::gamma_q(a, z, Policy()); }\
 \
    template <class RT1, class RT2>\
-   inline boost::math::tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z){ return boost::math::gamma_p(a, z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2> gamma_p(RT1 a, RT2 z){ return boost::math::gamma_p(a, z, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta){ return boost::math::tgamma_delta_ratio(z, delta, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> tgamma_delta_ratio(T1 z, T2 delta){ return boost::math::tgamma_delta_ratio(z, delta, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b) { return boost::math::tgamma_ratio(a, b, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> tgamma_ratio(T1 a, T2 b) { return boost::math::tgamma_ratio(a, b, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x){ return boost::math::gamma_p_derivative(a, x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x){ return boost::math::gamma_p_derivative(a, x, Policy()); }\
 \
    template <class T1, class T2>\
    inline boost::math::tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p){ return boost::math::gamma_p_inv(a, p, Policy()); }\

From 9f7215d1e227f521efccbea701b4ff2cc7472006 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:12:05 -0400
Subject: [PATCH 199/399] Add CUDA testing for tgamma and lgamma

---
 test/cuda_jamfile          |   4 ++
 test/test_lgamma_double.cu | 102 +++++++++++++++++++++++++++++++++++++
 test/test_lgamma_float.cu  | 102 +++++++++++++++++++++++++++++++++++++
 test/test_tgamma_double.cu | 102 +++++++++++++++++++++++++++++++++++++
 test/test_tgamma_float.cu  | 102 +++++++++++++++++++++++++++++++++++++
 5 files changed, 412 insertions(+)
 create mode 100644 test/test_lgamma_double.cu
 create mode 100644 test/test_lgamma_float.cu
 create mode 100644 test/test_tgamma_double.cu
 create mode 100644 test/test_tgamma_float.cu

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index b287cc5b10..97ba14e81a 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -109,6 +109,8 @@ run test_erfc_inv_double.cu ;
 run test_erfc_inv_float.cu ;
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
+run test_lgamma_double.cu ;
+run test_lgamma_float.cu ;
 run test_log1p_double.cu ;
 run test_log1p_float.cu ;
 run test_modf_double.cu ;
@@ -117,6 +119,8 @@ run test_round_double.cu ;
 run test_round_float.cu ;
 run test_sin_pi_double.cu ; 
 run test_sin_pi_float.cu ;
+run test_tgamma_double.cu ;
+run test_tgamma_float.cu ;
 run test_trigamma_double.cu ;
 run test_trigamma_float.cu ;
 run test_trunc_double.cu ;
diff --git a/test/test_lgamma_double.cu b/test/test_lgamma_double.cu
new file mode 100644
index 0000000000..776ff5d271
--- /dev/null
+++ b/test/test_lgamma_double.cu
@@ -0,0 +1,102 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::lgamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::lgamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_lgamma_float.cu b/test/test_lgamma_float.cu
new file mode 100644
index 0000000000..101037ab30
--- /dev/null
+++ b/test/test_lgamma_float.cu
@@ -0,0 +1,102 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::lgamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::lgamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_tgamma_double.cu b/test/test_tgamma_double.cu
new file mode 100644
index 0000000000..6e4140ab6e
--- /dev/null
+++ b/test/test_tgamma_double.cu
@@ -0,0 +1,102 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::tgamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_tgamma_float.cu b/test/test_tgamma_float.cu
new file mode 100644
index 0000000000..cb2d01482d
--- /dev/null
+++ b/test/test_tgamma_float.cu
@@ -0,0 +1,102 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::tgamma(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}

From e9ccdcfccd27ea8591c0cb4eb5349392fbf57ed7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:32:08 -0400
Subject: [PATCH 200/399] Disable factorial check on GPU platform

---
 include/boost/math/special_functions/beta.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 25e524d0b3..07ac9d5a6b 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -930,7 +930,9 @@ template <>
 struct Pn_size<long double>
 {
    static constexpr unsigned value = 50; // ~35-50 digit accuracy
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
    static_assert(::boost::math::max_factorial<long double>::value >= 100, "Type does not provide for ~35-50 digits of accuracy");
+#endif
 };
 
 template <class T, class Policy>

From 5ad3866816a6794354231c2a0db1dab6c89bda9e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:37:44 -0400
Subject: [PATCH 201/399] Add SYCL gamma testing

---
 test/sycl_jamfile   | 1 +
 test/test_gamma.cpp | 4 ++++
 test/test_gamma.hpp | 5 ++++-
 3 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index e336523e6c..d0a458cce6 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -33,3 +33,4 @@ run test_log1p_simple.cpp ;
 run test_digamma_simple.cpp ;
 run test_trigamma.cpp ;
 run test_erf.cpp ;
+run test_gamma.cpp ;
diff --git a/test/test_gamma.cpp b/test/test_gamma.cpp
index 6b2d19cca6..565d5888a0 100644
--- a/test/test_gamma.cpp
+++ b/test/test_gamma.cpp
@@ -3,7 +3,11 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#include <boost/math/special_functions/gamma.hpp>
 #include "test_gamma.hpp"
 
 //
diff --git a/test/test_gamma.hpp b/test/test_gamma.hpp
index c21573dac6..729a8266d5 100644
--- a/test/test_gamma.hpp
+++ b/test/test_gamma.hpp
@@ -6,6 +6,7 @@
 
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #define BOOST_TEST_MAIN
@@ -13,7 +14,7 @@
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/next.hpp>  // for has_denorm_now
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
@@ -320,11 +321,13 @@ void test_spots(T, const char* name)
       BOOST_CHECK(sign == -1);
    }
 
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    if(boost::math::detail::has_denorm_now<T>() && std::numeric_limits<T>::has_infinity && (boost::math::isinf)(1 / std::numeric_limits<T>::denorm_min()))
    {
       BOOST_CHECK_EQUAL(boost::math::tgamma(-std::numeric_limits<T>::denorm_min()), -std::numeric_limits<T>::infinity());
       BOOST_CHECK_EQUAL(boost::math::tgamma(std::numeric_limits<T>::denorm_min()), std::numeric_limits<T>::infinity());
    }
+   #endif
    //
    // Extra large values for lgamma, see https://github.com/boostorg/math/issues/242
    //

From b67f1fd4cad97d4d07e37cdc486e07791bccd6f8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 14:48:18 -0400
Subject: [PATCH 202/399] Remove extra overloads

---
 include/boost/math/special_functions/sign.hpp | 16 ----------------
 1 file changed, 16 deletions(-)

diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index 2092a41bb2..d147b5b1be 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -162,22 +162,6 @@ BOOST_MATH_GPU_ENABLED int (signbit)(T x)
    return detail::signbit_impl(static_cast<result_type>(x), method());
 }
 
-#ifndef BOOST_MATH_HAS_GPU_SUPPORT
-template<>
-BOOST_MATH_GPU_ENABLED int signbit<float>(float x)
-{
-    using std::signbit;
-    return (signbit)(x);
-}
-
-template<>
-BOOST_MATH_GPU_ENABLED int signbit<double>(double x)
-{
-    using std::signbit;
-    return (signbit)(x);
-}
-#endif
-
 template <class T>
 BOOST_MATH_GPU_ENABLED inline int sign BOOST_NO_MACRO_EXPAND(const T& z)
 {

From 18ef483309516837cfc382e39385445fc65cd379 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 15:08:54 -0400
Subject: [PATCH 203/399] Remove recursion from tgamma

---
 .../boost/math/special_functions/gamma.hpp    | 42 ++++++++++++-------
 1 file changed, 28 insertions(+), 14 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index b77f4f5eaa..62448d69e3 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED T sinpx(T z)
 // tgamma(z), with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
-BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T gamma_imp_final(T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
 
@@ -127,20 +127,8 @@ BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l)
    if(z <= 0)
    {
       if(floor(z) == z)
-         return policies::raise_pole_error<T>(function, "Evaluation of tgamma at a negative integer %1%.", z, pol);
-      if(z <= -20)
       {
-         result = gamma_imp(T(-z), pol, l) * sinpx(z);
-         BOOST_MATH_INSTRUMENT_VARIABLE(result);
-         if((fabs(result) < 1) && (tools::max_value<T>() * fabs(result) < boost::math::constants::pi<T>()))
-            return -boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
-         result = -boost::math::constants::pi<T>() / result;
-         if(result == 0)
-            return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
-         if((boost::math::fpclassify)(result) == (int)FP_SUBNORMAL)
-            return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
-         BOOST_MATH_INSTRUMENT_VARIABLE(result);
-         return result;
+         return policies::raise_pole_error<T>(function, "Evaluation of tgamma at a negative integer %1%.", z, pol);
       }
 
       // shift z to > 1:
@@ -195,6 +183,32 @@ BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l)
    }
    return result;
 }
+// SYCL compilers can not support recursion so we extract it into a dispatch function
+template <class T, class Policy, class Lanczos>
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol, const Lanczos& l)
+{
+   BOOST_MATH_STD_USING
+   
+   if(z <= -20)
+   {
+      constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
+      T result = gamma_imp_final(T(-z), pol, l) * sinpx(z);
+      BOOST_MATH_INSTRUMENT_VARIABLE(result);
+      if((fabs(result) < 1) && (tools::max_value<T>() * fabs(result) < boost::math::constants::pi<T>()))
+         return -boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
+      result = -boost::math::constants::pi<T>() / result;
+      if(result == 0)
+         return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
+      if((boost::math::fpclassify)(result) == (int)FP_SUBNORMAL)
+         return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
+      BOOST_MATH_INSTRUMENT_VARIABLE(result);
+      return result;
+   }
+   else
+   {
+      return gamma_imp_final(T(z), pol, l);
+   }
+}
 //
 // lgamma(z) with Lanczos support:
 //

From dc792c9f9071ef21a203b18b28ec6d039bdfaf04 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 15:47:04 -0400
Subject: [PATCH 204/399] Remove recursion in lgamma

---
 .../boost/math/special_functions/gamma.hpp    | 66 +++++++++++++------
 1 file changed, 45 insertions(+), 21 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 62448d69e3..7601d5295a 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -188,7 +188,7 @@ template <class T, class Policy, class Lanczos>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
-   
+
    if(z <= -20)
    {
       constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
@@ -213,7 +213,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol
 // lgamma(z) with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
-BOOST_MATH_GPU_ENABLED T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
+BOOST_MATH_GPU_ENABLED T lgamma_imp_final(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
 {
 #ifdef BOOST_MATH_INSTRUMENT
    static bool b = false;
@@ -230,25 +230,8 @@ BOOST_MATH_GPU_ENABLED T lgamma_imp(T z, const Policy& pol, const Lanczos& l, in
 
    T result = 0;
    int sresult = 1;
-   if(z <= -tools::root_epsilon<T>())
-   {
-      // reflection formula:
-      if(floor(z) == z)
-         return policies::raise_pole_error<T>(function, "Evaluation of lgamma at a negative integer %1%.", z, pol);
-
-      T t = sinpx(z);
-      z = -z;
-      if(t < 0)
-      {
-         t = -t;
-      }
-      else
-      {
-         sresult = -sresult;
-      }
-      result = log(boost::math::constants::pi<T>()) - lgamma_imp(z, pol, l) - log(t);
-   }
-   else if (z < tools::root_epsilon<T>())
+   
+   if (z < tools::root_epsilon<T>())
    {
       if (0 == z)
          return policies::raise_pole_error<T>(function, "Evaluation of lgamma at %1%.", z, pol);
@@ -293,6 +276,47 @@ BOOST_MATH_GPU_ENABLED T lgamma_imp(T z, const Policy& pol, const Lanczos& l, in
    return result;
 }
 
+template <class T, class Policy, class Lanczos>
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
+{
+   BOOST_MATH_STD_USING
+
+   if(z <= -tools::root_epsilon<T>())
+   {
+      constexpr auto function = "boost::math::lgamma<%1%>(%1%)";
+
+      T result = 0;
+      int sresult = 1;
+
+      // reflection formula:
+      if(floor(z) == z)
+         return policies::raise_pole_error<T>(function, "Evaluation of lgamma at a negative integer %1%.", z, pol);
+
+      T t = sinpx(z);
+      z = -z;
+      if(t < 0)
+      {
+         t = -t;
+      }
+      else
+      {
+         sresult = -sresult;
+      }
+      result = log(boost::math::constants::pi<T>()) - lgamma_imp_final(T(z), pol, l) - log(t);
+
+      if(sign)
+      {
+         *sign = sresult;
+      }
+
+      return result;
+   }
+   else
+   {
+      return lgamma_imp_final(T(z), pol, l, sign);
+   }
+}
+
 //
 // Incomplete gamma functions follow:
 //

From 1fcc01ad4cf2fdf10d39222444a174f9bc4b7a7d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 15:51:14 -0400
Subject: [PATCH 205/399] Ignore CUDA warning about GNU force inline

---
 include/boost/math/special_functions/gamma.hpp | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 7601d5295a..af0599c886 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -183,6 +183,11 @@ BOOST_MATH_GPU_ENABLED T gamma_imp_final(T z, const Policy& pol, const Lanczos&
    }
    return result;
 }
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_suppress 2190
+#endif
+
 // SYCL compilers can not support recursion so we extract it into a dispatch function
 template <class T, class Policy, class Lanczos>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol, const Lanczos& l)
@@ -209,6 +214,11 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol
       return gamma_imp_final(T(z), pol, l);
    }
 }
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_default 2190
+#endif
+
 //
 // lgamma(z) with Lanczos support:
 //
@@ -276,6 +286,10 @@ BOOST_MATH_GPU_ENABLED T lgamma_imp_final(T z, const Policy& pol, const Lanczos&
    return result;
 }
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_suppress 2190
+#endif
+
 template <class T, class Policy, class Lanczos>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T lgamma_imp(T z, const Policy& pol, const Lanczos& l, int* sign = nullptr)
 {
@@ -317,6 +331,10 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T lgamma_imp(T z, const Policy& po
    }
 }
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_default 2190
+#endif
+
 //
 // Incomplete gamma functions follow:
 //

From 0fafaf2cd1ef77db7f88f7de243dc9be0e56b9e1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 15:57:04 -0400
Subject: [PATCH 206/399] Ignore literal range warnings

---
 test/test_erf.cpp | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/test/test_erf.cpp b/test/test_erf.cpp
index beb521ac4c..b4513d96db 100644
--- a/test/test_erf.cpp
+++ b/test/test_erf.cpp
@@ -8,6 +8,14 @@
 #include <pch_light.hpp>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma gcc diagnostic push 
+#  pragma gcc diagnostic ignored "-Wliteral-range"
+#endif
+
 #include <boost/math/special_functions/erf.hpp>
 #include "test_erf.hpp"
 

From 82d56ac1c5b956a3a142e520c568c40539e3bd6d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 16:15:14 -0400
Subject: [PATCH 207/399] Ignore mapairy literal range warnings

---
 test/test_mapairy.cpp | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index c1d1c739b0..096abde8b8 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -4,6 +4,14 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma gcc diagnostic push 
+#  pragma gcc diagnostic ignored "-Wliteral-range"
+#endif
+
 #define BOOST_TEST_MAIN
 #define BOOST_TEST_MODULE StatsMapAiryTest
 #include <boost/math/tools/config.hpp>

From 49cc43cd52a62d9c042b12266548e4fa496fc72f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 16:16:28 -0400
Subject: [PATCH 208/399] Make powm1 GPU compatible

---
 .../boost/math/special_functions/math_fwd.hpp |  6 +-
 .../boost/math/special_functions/powm1.hpp    | 66 +++++++++++--------
 2 files changed, 43 insertions(+), 29 deletions(-)

diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index fdccfad8b4..289b27592a 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -591,11 +591,11 @@ namespace boost
 
    // Power - 1
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          powm1(const T1 a, const T2 z);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          powm1(const T1 a, const T2 z, const Policy&);
 
    // sqrt(1+x) - 1
@@ -1481,7 +1481,7 @@ namespace boost
 \
    template <class T1, class T2>\
    inline boost::math::tools::promote_args_t<T1, T2> \
-   powm1(const T1 a, const T2 z){ return boost::math::powm1(a, z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED powm1(const T1 a, const T2 z){ return boost::math::powm1(a, z, Policy()); }\
 \
    template <class T>\
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sqrt1pm1(const T& val){ return boost::math::sqrt1pm1(val, Policy()); }\
diff --git a/include/boost/math/special_functions/powm1.hpp b/include/boost/math/special_functions/powm1.hpp
index e52277b16d..f00af22642 100644
--- a/include/boost/math/special_functions/powm1.hpp
+++ b/include/boost/math/special_functions/powm1.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,6 +13,7 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/expm1.hpp>
@@ -22,32 +24,23 @@
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-inline T powm1_imp(const T x, const T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T powm1_imp(const T x, const T y, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::powm1<%1%>(%1%, %1%)";
-   if (x > 0)
+   constexpr auto function = "boost::math::powm1<%1%>(%1%, %1%)";
+
+   if ((fabs(y * (x - 1)) < T(0.5)) || (fabs(y) < T(0.2)))
    {
-      if ((fabs(y * (x - 1)) < T(0.5)) || (fabs(y) < T(0.2)))
-      {
-         // We don't have any good/quick approximation for log(x) * y
-         // so just try it and see:
-         T l = y * log(x);
-         if (l < T(0.5))
-            return boost::math::expm1(l, pol);
-         if (l > boost::math::tools::log_max_value<T>())
-            return boost::math::policies::raise_overflow_error<T>(function, nullptr, pol);
-         // fall through....
-      }
-   }
-   else if ((boost::math::signbit)(x)) // Need to error check -0 here as well
-   {
-      // y had better be an integer:
-      if (boost::math::trunc(y) != y)
-         return boost::math::policies::raise_domain_error<T>(function, "For non-integral exponent, expected base > 0 but got %1%", x, pol);
-      if (boost::math::trunc(y / 2) == y / 2)
-         return powm1_imp(T(-x), y, pol);
+      // We don't have any good/quick approximation for log(x) * y
+      // so just try it and see:
+      T l = y * log(x);
+      if (l < T(0.5))
+         return boost::math::expm1(l, pol);
+      if (l > boost::math::tools::log_max_value<T>())
+         return boost::math::policies::raise_overflow_error<T>(function, nullptr, pol);
+      // fall through....
    }
+   
    T result = pow(x, y) - 1;
    if((boost::math::isinf)(result))
       return result < 0 ? -boost::math::policies::raise_overflow_error<T>(function, nullptr, pol) : boost::math::policies::raise_overflow_error<T>(function, nullptr, pol);
@@ -56,22 +49,43 @@ inline T powm1_imp(const T x, const T y, const Policy& pol)
    return result;
 }
 
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED inline T powm1_imp_dispatch(const T x, const T y, const Policy& pol)
+{
+   BOOST_MATH_STD_USING
+
+   if ((boost::math::signbit)(x)) // Need to error check -0 here as well
+   {
+      constexpr auto function = "boost::math::powm1<%1%>(%1%, %1%)";
+
+      // y had better be an integer:
+      if (boost::math::trunc(y) != y)
+         return boost::math::policies::raise_domain_error<T>(function, "For non-integral exponent, expected base > 0 but got %1%", x, pol);
+      if (boost::math::trunc(y / 2) == y / 2)
+         return powm1_imp(T(-x), T(y), pol);
+   }
+   else
+   {
+      return powm1_imp(T(x), T(y), pol);
+   }
+}
+
 } // detail
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    powm1(const T1 a, const T2 z)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
-   return detail::powm1_imp(static_cast<result_type>(a), static_cast<result_type>(z), policies::policy<>());
+   return detail::powm1_imp_dispatch(static_cast<result_type>(a), static_cast<result_type>(z), policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    powm1(const T1 a, const T2 z, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
-   return detail::powm1_imp(static_cast<result_type>(a), static_cast<result_type>(z), pol);
+   return detail::powm1_imp_dispatch(static_cast<result_type>(a), static_cast<result_type>(z), pol);
 }
 
 } // namespace math

From 635bd3215efd8b4dfd5838e897efc1c2fa4de121 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 16:23:52 -0400
Subject: [PATCH 209/399] Fix GCC warnings

---
 include/boost/math/special_functions/powm1.hpp | 6 ++----
 test/test_erf.cpp                              | 4 ++--
 test/test_mapairy.cpp                          | 4 ++--
 3 files changed, 6 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/special_functions/powm1.hpp b/include/boost/math/special_functions/powm1.hpp
index f00af22642..80d02dc299 100644
--- a/include/boost/math/special_functions/powm1.hpp
+++ b/include/boost/math/special_functions/powm1.hpp
@@ -64,10 +64,8 @@ BOOST_MATH_GPU_ENABLED inline T powm1_imp_dispatch(const T x, const T y, const P
       if (boost::math::trunc(y / 2) == y / 2)
          return powm1_imp(T(-x), T(y), pol);
    }
-   else
-   {
-      return powm1_imp(T(x), T(y), pol);
-   }
+
+   return powm1_imp(T(x), T(y), pol);
 }
 
 } // detail
diff --git a/test/test_erf.cpp b/test/test_erf.cpp
index b4513d96db..d01f8024d0 100644
--- a/test/test_erf.cpp
+++ b/test/test_erf.cpp
@@ -12,8 +12,8 @@
 #  pragma clang diagnostic push 
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
-#  pragma gcc diagnostic push 
-#  pragma gcc diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
 #endif
 
 #include <boost/math/special_functions/erf.hpp>
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index 096abde8b8..ee8e43bf00 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -8,8 +8,8 @@
 #  pragma clang diagnostic push 
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
-#  pragma gcc diagnostic push 
-#  pragma gcc diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
 #endif
 
 #define BOOST_TEST_MAIN

From c7e16f75cb91305ab0a7c6567cb6d5e1efa7b8a1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 30 Jul 2024 17:20:49 -0400
Subject: [PATCH 210/399] Revert if constexpr change

---
 include/boost/math/special_functions/gamma.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index af0599c886..b1beeb766b 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -1913,7 +1913,7 @@ struct igamma_initializer
          // our initialization code here as the precision presumably
          // varies at runtime, and will not have been set yet.  Plus the
          // code requiring initialization isn't called when digits == 0.
-         BOOST_MATH_IF_CONSTEXPR (std::numeric_limits<T>::digits)
+         if (std::numeric_limits<T>::digits)
          {
             boost::math::gamma_p(static_cast<T>(400), static_cast<T>(400), Policy());
          }

From 24a0922e8bb1070204b75951a3caa7bd3b953450 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 31 Jul 2024 12:05:00 -0400
Subject: [PATCH 211/399] Fix typo

---
 include/boost/math/special_functions/detail/lgamma_small.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/detail/lgamma_small.hpp b/include/boost/math/special_functions/detail/lgamma_small.hpp
index 82a1761f19..d9fa88b8ed 100644
--- a/include/boost/math/special_functions/detail/lgamma_small.hpp
+++ b/include/boost/math/special_functions/detail/lgamma_small.hpp
@@ -38,7 +38,7 @@ T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos& l);
 // lgamma for small arguments:
 //
 template <class T, class Policy, class Lanczos>
-BOOST_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
+BOOST_MATH_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
 {
    // This version uses rational approximations for small
    // values of z accurate enough for 64-bit mantissas

From faf541ee0b9401e491ab1d9dffe59b4211a414a6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 31 Jul 2024 14:29:09 -0400
Subject: [PATCH 212/399] Fix comparison

---
 include/boost/math/special_functions/erf.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/erf.hpp b/include/boost/math/special_functions/erf.hpp
index 323a91937a..0b311c4641 100644
--- a/include/boost/math/special_functions/erf.hpp
+++ b/include/boost/math/special_functions/erf.hpp
@@ -221,7 +221,7 @@ BOOST_MATH_GPU_ENABLED T erf_imp(T z, bool invert, const Policy& pol, const std:
          prefix_multiplier = -1;
          // return -erf_imp(T(-z), invert, pol, t);
       }
-      else if(z < -0.5)
+      else if(z < T(-0.5))
       {
          prefix_adder = 2;
          // return 2 - erf_imp(T(-z), invert, pol, t);

From 87048d927b7fb5be7adfcf8785209958a7e06795 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 31 Jul 2024 14:29:54 -0400
Subject: [PATCH 213/399] Use tag type idiom

---
 include/boost/math/special_functions/detail/erf_inv.hpp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/detail/erf_inv.hpp b/include/boost/math/special_functions/detail/erf_inv.hpp
index 09772632d4..69a08abe66 100644
--- a/include/boost/math/special_functions/detail/erf_inv.hpp
+++ b/include/boost/math/special_functions/detail/erf_inv.hpp
@@ -317,7 +317,8 @@ T erf_inv_imp(const T& p, const T& q, const Policy& pol, const std::integral_con
    //
    // Generic version, get a guess that's accurate to 64-bits (10^-19)
    //
-   T guess = erf_inv_imp(p, q, pol, std::integral_constant<int, 64>());
+   using tag_type = std::integral_constant<int, 64>;
+   T guess = erf_inv_imp(p, q, pol, tag_type());
    T result;
    //
    // If T has more bit's than 64 in it's mantissa then we need to iterate,

From 445e36adc0de9bea170669c9724d9b0ac9e3c5c3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 5 Aug 2024 15:28:58 -0400
Subject: [PATCH 214/399] Reorder overflow checks

---
 test/test_erf.cpp   | 1 +
 test/test_gamma.cpp | 1 +
 test/test_gamma.hpp | 2 --
 3 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/test_erf.cpp b/test/test_erf.cpp
index d01f8024d0..5044847114 100644
--- a/test/test_erf.cpp
+++ b/test/test_erf.cpp
@@ -16,6 +16,7 @@
 #  pragma GCC diagnostic ignored "-Wliteral-range"
 #endif
 
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #include <boost/math/special_functions/erf.hpp>
 #include "test_erf.hpp"
 
diff --git a/test/test_gamma.cpp b/test/test_gamma.cpp
index 565d5888a0..fb86080d72 100644
--- a/test/test_gamma.cpp
+++ b/test/test_gamma.cpp
@@ -7,6 +7,7 @@
 #include <pch_light.hpp>
 #endif
 
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #include <boost/math/special_functions/gamma.hpp>
 #include "test_gamma.hpp"
 
diff --git a/test/test_gamma.hpp b/test/test_gamma.hpp
index 729a8266d5..7376573ad2 100644
--- a/test/test_gamma.hpp
+++ b/test/test_gamma.hpp
@@ -4,8 +4,6 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
-#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
-
 #include <boost/math/tools/config.hpp>
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>

From 4b9c5b0e7823773111546baed3a8400a4639c36a Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Tue, 6 Aug 2024 13:06:09 +0100
Subject: [PATCH 215/399] Update history.

---
 doc/math.qbk             |  2 +-
 doc/overview/roadmap.qbk | 10 ++++++++++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/doc/math.qbk b/doc/math.qbk
index 30bc533398..4b8804dbbb 100644
--- a/doc/math.qbk
+++ b/doc/math.qbk
@@ -9,7 +9,7 @@
     ]
     [authors [Agrawal, Nikhar], [Bikineev, Anton], [Borland, Matthew], [Bristow, Paul A.], [Holin, Hubert], [Guazzone, Marco], [Kormanyos, Christopher], [Lalande, Bruno], [Maddock, John], [Miller, Evan], [Murphy, Jeremy W.], [Pulver, Matthew], [Råde, Johan], [Sobotta, Benjamin], [Sewani, Gautam], [Thompson, Nicholas], [van den Berg, Thijs], [Walker, Daryle], [Zhang, Xiaogang]]
     [/last-revision $Date$]
-    [version 4.2.0]
+    [version 4.2.1]
 ]
 
 [template mathpart[id title]
diff --git a/doc/overview/roadmap.qbk b/doc/overview/roadmap.qbk
index f217c815bc..4f356ea5e4 100644
--- a/doc/overview/roadmap.qbk
+++ b/doc/overview/roadmap.qbk
@@ -8,6 +8,16 @@ All old bug reports including closed ones can be viewed on Trac
 
 Recent issues on GitHub [@https://github.com/boostorg/math/issues?utf8=%E2%9C%93&q=is%3Aissue here].
 
+[h4 Math-4.2.1 (Boost-1.86)]
+
+* Correct Bessel function results at infinity, see [@https://github.com/boostorg/math/issues/1143 1143].
+* Improve Non Central T numerical stability, see [@https://github.com/scipy/scipy/issues/20693 scipy20693].
+* Correct `float_next`/`float_prior` behaviour at infinity.
+* Prevent spurious underflow in non-central beta, see [@https://github.com/scipy/scipy/issues/20693 scipy20693].
+* Add improvement to Heuman Lambda precision.
+* Improve Skew Normal root finding, see [@https://github.com/boostorg/math/issues/1120 1120].
+* Lots of minor fixes and improved code coverage.
+
 [h4 Math-4.2.0 (Boost-1.85)]
 
 * Add support for [link math_toolkit.jso  Single objective real-parameter optimization: Algorithm jSO].

From d30faa38ffec0b2131d772437892a0262b430c5b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 13:58:13 -0400
Subject: [PATCH 216/399] Add tgamma nvrtc test

---
 test/test_gamma_nvrtc.cpp | 183 ++++++++++++++++++++++++++++++++++++++
 1 file changed, 183 insertions(+)
 create mode 100644 test/test_gamma_nvrtc.cpp

diff --git a/test/test_gamma_nvrtc.cpp b/test/test_gamma_nvrtc.cpp
new file mode 100644
index 0000000000..2d33430240
--- /dev/null
+++ b/test/test_gamma_nvrtc.cpp
@@ -0,0 +1,183 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+const char* cuda_kernel = R"(
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float *in1, const float*, float *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/math/boost-root/libs/math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float *h_in1, *h_in2, *h_out;
+        float *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float[numElements];
+        h_in2 = new float[numElements];
+        h_out = new float[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float>(dist(rng));
+            h_in2[i] = static_cast<float>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::tgamma(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From dae419023b6c03108eb16ee14335be928b9270ab Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 13:58:21 -0400
Subject: [PATCH 217/399] Add CI run

---
 .github/workflows/ci.yml | 58 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 58 insertions(+)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 0bf82c16e0..ccc4d37466 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -669,3 +669,61 @@ jobs:
       #  run: |
       #    cd ../boost-root/__build__
       #    ctest --output-on-failure --no-tests=error
+  nvrtc-cmake-test:
+    strategy:
+      fail-fast: false
+
+    runs-on: gpu-runner-1
+
+    steps:
+      - uses: Jimver/cuda-toolkit@v0.2.16
+        id: cuda-toolkit
+        with:
+          cuda: '12.5.0'
+          method: 'network'
+
+      - name: Output CUDA information
+        run: |
+          echo "Installed cuda version is: ${{steps.cuda-toolkit.outputs.cuda}}"+
+          echo "Cuda install location: ${{steps.cuda-toolkit.outputs.CUDA_PATH}}"
+          nvcc -V
+      - uses: actions/checkout@v4
+
+      - name: Install Packages
+        run: |
+          sudo apt-get install -y cmake make
+      - name: Setup Boost
+        run: |
+          echo GITHUB_REPOSITORY: $GITHUB_REPOSITORY
+          LIBRARY=${GITHUB_REPOSITORY#*/}
+          echo LIBRARY: $LIBRARY
+          echo "LIBRARY=$LIBRARY" >> $GITHUB_ENV
+          echo GITHUB_BASE_REF: $GITHUB_BASE_REF
+          echo GITHUB_REF: $GITHUB_REF
+          REF=${GITHUB_BASE_REF:-$GITHUB_REF}
+          REF=${REF#refs/heads/}
+          echo REF: $REF
+          BOOST_BRANCH=develop && [ "$REF" == "master" ] && BOOST_BRANCH=master || true
+          echo BOOST_BRANCH: $BOOST_BRANCH
+          cd ..
+          git clone -b $BOOST_BRANCH --depth 1 https://github.com/boostorg/boost.git boost-root
+          cd boost-root
+          mkdir -p libs/$LIBRARY
+          cp -r $GITHUB_WORKSPACE/* libs/$LIBRARY
+          git submodule update --init tools/boostdep
+          python3 tools/boostdep/depinst/depinst.py --git_args "--jobs 3" $LIBRARY
+      - name: Configure
+        run: |
+          cd ../boost-root
+          mkdir __build__ && cd __build__
+          cmake -DBOOST_INCLUDE_LIBRARIES=$LIBRARY -DBUILD_TESTING=ON -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc -DBOOST_MATH_ENABLE_NVRTC=1 -DCMAKE_CUDA_ARCHITECTURES=70 -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-12.5 -DBOOST_MATH_NVRTC_CI_RUN=1 ..
+          pwd
+      - name: Build tests
+        run: |
+          cd ../boost-root/__build__
+          cmake --build . --target tests -j $(nproc)
+      # We don't have the ability for runtime right now
+      #- name: Run tests
+      #  run: |
+      #    cd ../boost-root/__build__
+      #    ctest --output-on-failure --no-tests=error

From 88c36d3fefcd9aed278541fe8b2b77acb261a881 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 13:58:26 -0400
Subject: [PATCH 218/399] Add Jamfile

---
 test/nvrtc_jamfile | 13 +++++++++++++
 1 file changed, 13 insertions(+)
 create mode 100644 test/nvrtc_jamfile

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
new file mode 100644
index 0000000000..707780b7a7
--- /dev/null
+++ b/test/nvrtc_jamfile
@@ -0,0 +1,13 @@
+# Copyright 2024 Matt Borland
+# Distributed under the Boost Software License, Version 1.0.
+# https://www.boost.org/LICENSE_1_0.txt
+
+import testing ;
+import ../../config/checks/config : requires ;
+
+project : requirements
+    [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
+    ;
+
+# Special Functions
+run test_gamma_nvrtc.cpp ;

From 470e5934da54c7505faf30da03cc5c63023f44fb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 13:59:47 -0400
Subject: [PATCH 219/399] Update CML

---
 test/CMakeLists.txt | 23 ++++++++++++++++++++---
 1 file changed, 20 insertions(+), 3 deletions(-)

diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 78d8fd4c34..22799e92ea 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -8,7 +8,7 @@ if(HAVE_BOOST_TEST)
 
     if (BOOST_MATH_ENABLE_CUDA)
 
-        message(STATUS "Building boost.cuda_math with CUDA")
+        message(STATUS "Building boost.math with CUDA")
 
         enable_language(CUDA)
         set(CMAKE_CUDA_EXTENSIONS OFF)
@@ -16,9 +16,26 @@ if(HAVE_BOOST_TEST)
         enable_testing()
 
         boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework )
+
+    elseif (BOOST_MATH_ENABLE_NVRTC)
+
+        message(STATUS "Building boost.math with NVRTC")
+
+        find_package(CUDA REQUIRED)
+
+        enable_testing()
+
+        set(CUDA_nvrtc_LIBRARY /usr/local/cuda/lib64/libnvrtc.so)
+        
+        if (BOOST_MATH_NVRTC_CI_RUN)
+            boost_test_jamfile(FILE nvrtc_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception ${CUDA_nvrtc_LIBRARY} ${CUDA_LIBRARIES} ${CUDA_CUDA_LIBRARY} COMPILE_DEFINITIONS BOOST_MATH_NVRTC_CI_RUN=1 INCLUDE_DIRECTORIES ${CUDA_INCLUDE_DIRS} )
+        else ()
+            boost_test_jamfile(FILE nvrtc_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception ${CUDA_nvrtc_LIBRARY} ${CUDA_LIBRARIES} ${CUDA_CUDA_LIBRARY} INCLUDE_DIRECTORIES ${CUDA_INCLUDE_DIRS} )
+        endif()
+
     elseif (BOOST_MATH_ENABLE_SYCL)
 
-        message(STATUS "Building boost.cuda_math with SYCL")
+        message(STATUS "Building boost.math with SYCL")
 
         set(CMAKE_CXX_COMPILER "icpx")
         set(CMAKE_C_COMPILER "icx")
@@ -32,4 +49,4 @@ if(HAVE_BOOST_TEST)
 
     endif()
 
-endif()
\ No newline at end of file
+endif()

From e7f09ca02749ee31147d3335a94188a491752c74 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 14:00:39 -0400
Subject: [PATCH 220/399] Add tgamma support to NVRTC

---
 include/boost/math/special_functions/gamma.hpp | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index b1beeb766b..46e8236aa1 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -14,6 +14,22 @@
 #pragma once
 #endif
 
+#ifdef __CUDACC_RTC__
+
+namespace boost {
+namespace math {
+
+template <typename T>
+__host__ __device__ T tgamma(T x)
+{
+   return ::tgamma(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#else
+
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/fraction.hpp>
@@ -2280,4 +2296,6 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 #include <boost/math/special_functions/detail/gamma_inva.hpp>
 #include <boost/math/special_functions/erf.hpp>
 
+#endif // __CUDACC_RTC__
+
 #endif // BOOST_MATH_SF_GAMMA_HPP

From 477d1c1777253e669bdf677f308a9e6df11f52fd Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 14:45:07 -0400
Subject: [PATCH 221/399] Fix runs on value

---
 .github/workflows/ci.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index ccc4d37466..ee72988440 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -673,7 +673,7 @@ jobs:
     strategy:
       fail-fast: false
 
-    runs-on: gpu-runner-1
+    runs-on: ubuntu-22.04
 
     steps:
       - uses: Jimver/cuda-toolkit@v0.2.16

From 37db0179032d0820159a6f802f79c1c65f2e39fe Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 07:28:13 -0400
Subject: [PATCH 222/399] Rearrange and add policy overload

---
 .../boost/math/special_functions/gamma.hpp    | 33 ++++++++++---------
 1 file changed, 18 insertions(+), 15 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 46e8236aa1..70b4ff155c 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -14,21 +14,7 @@
 #pragma once
 #endif
 
-#ifdef __CUDACC_RTC__
-
-namespace boost {
-namespace math {
-
-template <typename T>
-__host__ __device__ T tgamma(T x)
-{
-   return ::tgamma(x);
-}
-
-} // namespace math
-} // namespace boost
-
-#else
+#ifndef __CUDACC_RTC__
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/series.hpp>
@@ -2296,6 +2282,23 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 #include <boost/math/special_functions/detail/gamma_inva.hpp>
 #include <boost/math/special_functions/erf.hpp>
 
+#else
+
+namespace boost {
+namespace math {
+
+inline __host__ __device__ float tgamma(float x) { return ::tgammaf(x); }
+inline __host__ __device__ double tgamma(double x) { return ::tgamma(x); }
+
+template <typename T, typename Policy>
+inline __host__ __device__ T tgamma(T x, const Policy&)
+{
+   return boost::math::tgamma(x);
+}
+
+} // namespace math
+} // namespace boost
+
 #endif // __CUDACC_RTC__
 
 #endif // BOOST_MATH_SF_GAMMA_HPP

From 135208b3a642594b7caa3460e8b01441d21456fa Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 07:29:38 -0400
Subject: [PATCH 223/399] Expand testing

---
 test/nvrtc_jamfile                            |   3 +-
 test/test_gamma_nvrtc_double.cpp              | 186 ++++++++++++++++++
 ...a_nvrtc.cpp => test_gamma_nvrtc_float.cpp} |  33 ++--
 3 files changed, 206 insertions(+), 16 deletions(-)
 create mode 100644 test/test_gamma_nvrtc_double.cpp
 rename test/{test_gamma_nvrtc.cpp => test_gamma_nvrtc_float.cpp} (84%)

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 707780b7a7..63d0f2af09 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -10,4 +10,5 @@ project : requirements
     ;
 
 # Special Functions
-run test_gamma_nvrtc.cpp ;
+run test_gamma_nvrtc_double.cpp ;
+run test_gamma_nvrtc_float.cpp ;
diff --git a/test/test_gamma_nvrtc_double.cpp b/test/test_gamma_nvrtc_double.cpp
new file mode 100644
index 0000000000..6b21bd04b7
--- /dev/null
+++ b/test/test_gamma_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::tgamma(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_nvrtc.cpp b/test/test_gamma_nvrtc_float.cpp
similarity index 84%
rename from test/test_gamma_nvrtc.cpp
rename to test/test_gamma_nvrtc_float.cpp
index 2d33430240..ce312f6916 100644
--- a/test/test_gamma_nvrtc.cpp
+++ b/test/test_gamma_nvrtc_float.cpp
@@ -18,10 +18,13 @@
 #include <cuda_runtime.h>
 #include <nvrtc.h>
 
+typedef float float_type;
+
 const char* cuda_kernel = R"(
+typedef float float_type;
 #include <boost/math/special_functions/gamma.hpp>
 extern "C" __global__ 
-void test_gamma_kernel(const float *in1, const float*, float *out, int numElements)
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -113,36 +116,36 @@ int main()
         checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
-        float *h_in1, *h_in2, *h_out;
-        float *d_in1, *d_in2, *d_out;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
 
         // Allocate memory on the host
-        h_in1 = new float[numElements];
-        h_in2 = new float[numElements];
-        h_out = new float[numElements];
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
 
         // Initialize input arrays
         std::mt19937_64 rng(42);
-        std::uniform_real_distribution<float> dist(0.0f, 1.0f);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
         for (int i = 0; i < numElements; ++i) 
         {
-            h_in1[i] = static_cast<float>(dist(rng));
-            h_in2[i] = static_cast<float>(dist(rng));
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
         }
 
-        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float)), "Failed to allocate device memory for d_in1");
-        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float)), "Failed to allocate device memory for d_in2");
-        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float)), "Failed to allocate device memory for d_out");
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
 
-        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
-        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
 
         int blockSize = 256;
         int numBlocks = (numElements + blockSize - 1) / blockSize;
         void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
         checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
 
-        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
 
         // Verify Result
         for (int i = 0; i < numElements; ++i) 

From 77bf1c1447cd54b609c501c90098a84c5cb50a2f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 15:30:44 -0400
Subject: [PATCH 224/399] Add NVRTC support to sign

---
 include/boost/math/special_functions/sign.hpp | 35 +++++++++++++++++++
 1 file changed, 35 insertions(+)

diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index d147b5b1be..58358328e2 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -14,6 +14,8 @@
 #pragma once
 #endif
 
+#ifndef __CUDACC_RTC__
+
 #include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/detail/fp_traits.hpp>
@@ -192,6 +194,39 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args_permissive<T, U>::typ
 } // namespace math
 } // namespace boost
 
+#else // NVRTC alias versions
+
+namespace boost {
+namespace math {
+
+template <typename T>
+__host__ __device__ int signbit(T x)
+{
+    return ::signbit(x);
+}
+
+template <typename T>
+__host__ __device__ T changesign(T x)
+{
+    return -x;
+}
+
+template <typename T>
+__host__ __device__ T copysign(T x, T y)
+{
+    return ::copysign(x, y);
+}
+
+template <typename T>
+__host__ __device__ T sign(T z)
+{
+    return (z == 0) ? 0 : ::signbit(z) ? -1 : 1;
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // __CUDACC_RTC__
 
 #endif // BOOST_MATH_TOOLS_SIGN_HPP
 

From e85ad1311b732a331f049aa932cc9950fcab67c8 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 15:31:03 -0400
Subject: [PATCH 225/399] Add sign functions NVRTC test set

---
 test/test_sign_nvrtc.cpp | 190 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 190 insertions(+)
 create mode 100644 test/test_sign_nvrtc.cpp

diff --git a/test/test_sign_nvrtc.cpp b/test/test_sign_nvrtc.cpp
new file mode 100644
index 0000000000..37f7b13cf0
--- /dev/null
+++ b/test/test_sign_nvrtc.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/sign.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+const char* cuda_kernel = R"(
+#include <boost/math/special_functions/sign.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float *in1, const float *in2, float *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::signbit(in1[i]) + 
+                 boost::math::changesign(in1[i]) + 
+                 boost::math::copysign(in1[i], in2[i]) +
+                 boost::math::sign(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float *h_in1, *h_in2, *h_out;
+        float *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float[numElements];
+        h_in2 = new float[numElements];
+        h_out = new float[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float>(dist(rng));
+            h_in2[i] = static_cast<float>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::signbit(h_in1[i]) + 
+                       boost::math::changesign(h_in1[i]) + 
+                       boost::math::copysign(h_in1[i], h_in2[i]) +
+                       boost::math::sign(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 17dbb1eff6fa5e919751333a61654cb2dc76da69 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 16:11:19 -0400
Subject: [PATCH 226/399] Add specific float overload

---
 include/boost/math/special_functions/sign.hpp | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index 58358328e2..9fd8bba945 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -217,6 +217,12 @@ __host__ __device__ T copysign(T x, T y)
     return ::copysign(x, y);
 }
 
+template <typename T>
+__host__ __device__ float copysign(float x, float y)
+{
+    return ::copysignf(x, y);
+}
+
 template <typename T>
 __host__ __device__ T sign(T z)
 {

From ea23ddc58845ee0417b11b2643e090f772163198 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 16:29:47 -0400
Subject: [PATCH 227/399] Expand testing

---
 test/nvrtc_jamfile                            |   2 +
 test/test_sign_nvrtc_double.cpp               | 193 ++++++++++++++++++
 ...gn_nvrtc.cpp => test_sign_nvrtc_float.cpp} |  33 +--
 3 files changed, 213 insertions(+), 15 deletions(-)
 create mode 100644 test/test_sign_nvrtc_double.cpp
 rename test/{test_sign_nvrtc.cpp => test_sign_nvrtc_float.cpp} (85%)

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 63d0f2af09..bdf2309ee2 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -12,3 +12,5 @@ project : requirements
 # Special Functions
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
+run test_sign_nvrtc_double.cpp ;
+run test_sign_nvrtc_float.cpp ;
diff --git a/test/test_sign_nvrtc_double.cpp b/test/test_sign_nvrtc_double.cpp
new file mode 100644
index 0000000000..0951f9ef68
--- /dev/null
+++ b/test/test_sign_nvrtc_double.cpp
@@ -0,0 +1,193 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/sign.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/sign.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::signbit(in1[i]) + 
+                 boost::math::changesign(in1[i]) + 
+                 boost::math::copysign(in1[i], in2[i]) +
+                 boost::math::sign(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::signbit(h_in1[i]) + 
+                       boost::math::changesign(h_in1[i]) + 
+                       boost::math::copysign(h_in1[i], h_in2[i]) +
+                       boost::math::sign(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sign_nvrtc.cpp b/test/test_sign_nvrtc_float.cpp
similarity index 85%
rename from test/test_sign_nvrtc.cpp
rename to test/test_sign_nvrtc_float.cpp
index 37f7b13cf0..6e07f1996a 100644
--- a/test/test_sign_nvrtc.cpp
+++ b/test/test_sign_nvrtc_float.cpp
@@ -18,10 +18,13 @@
 #include <cuda_runtime.h>
 #include <nvrtc.h>
 
+typedef float float_type;
+
 const char* cuda_kernel = R"(
+typedef float float_type;
 #include <boost/math/special_functions/sign.hpp>
 extern "C" __global__ 
-void test_gamma_kernel(const float *in1, const float *in2, float *out, int numElements)
+void test_gamma_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -116,36 +119,36 @@ int main()
         checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
-        float *h_in1, *h_in2, *h_out;
-        float *d_in1, *d_in2, *d_out;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
 
         // Allocate memory on the host
-        h_in1 = new float[numElements];
-        h_in2 = new float[numElements];
-        h_out = new float[numElements];
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
 
         // Initialize input arrays
         std::mt19937_64 rng(42);
-        std::uniform_real_distribution<float> dist(0.0f, 1.0f);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
         for (int i = 0; i < numElements; ++i) 
         {
-            h_in1[i] = static_cast<float>(dist(rng));
-            h_in2[i] = static_cast<float>(dist(rng));
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
         }
 
-        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float)), "Failed to allocate device memory for d_in1");
-        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float)), "Failed to allocate device memory for d_in2");
-        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float)), "Failed to allocate device memory for d_out");
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
 
-        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
-        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
 
         int blockSize = 256;
         int numBlocks = (numElements + blockSize - 1) / blockSize;
         void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
         checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
 
-        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
 
         // Verify Result
         for (int i = 0; i < numElements; ++i) 

From b101e79b7e49d5ea360c79b1766af3ea624a0fe2 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 16:54:52 -0400
Subject: [PATCH 228/399] Add NVRTC support to cbrt

---
 include/boost/math/special_functions/cbrt.hpp | 25 +++++++++++++++++++
 1 file changed, 25 insertions(+)

diff --git a/include/boost/math/special_functions/cbrt.hpp b/include/boost/math/special_functions/cbrt.hpp
index 2488bb5d46..fb05996cf1 100644
--- a/include/boost/math/special_functions/cbrt.hpp
+++ b/include/boost/math/special_functions/cbrt.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,8 @@
 #pragma once
 #endif
 
+#ifndef __CUDACC_RTC__
+
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/policies/error_handling.hpp>
@@ -171,6 +174,28 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cbrt(T z)
 } // namespace math
 } // namespace boost
 
+#else
+
+namespace boost {
+namespace math {
+
+template <typename T>
+__host__ __device__ T cbrt(T x)
+{
+   return ::cbrt(x);
+}
+
+template <>
+__host__ __device__ float cbrt(float x)
+{
+   return ::cbrtf(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // NVRTC
+
 #endif // BOOST_MATH_SF_CBRT_HPP
 
 

From b7f1eab738860a8e85caec49ac2cc90e837c10a0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 6 Aug 2024 16:55:01 -0400
Subject: [PATCH 229/399] Add NVRTC cbrt tests

---
 test/nvrtc_jamfile              |   2 +
 test/test_cbrt_nvrtc_double.cpp | 186 ++++++++++++++++++++++++++++++++
 test/test_cbrt_nvrtc_float.cpp  | 186 ++++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_cbrt_nvrtc_double.cpp
 create mode 100644 test/test_cbrt_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index bdf2309ee2..55b9b85049 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -10,6 +10,8 @@ project : requirements
     ;
 
 # Special Functions
+run test_cbrt_nvrtc_double.cpp ;
+run test_cbrt_nvrtc_float.cpp ;
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
diff --git a/test/test_cbrt_nvrtc_double.cpp b/test/test_cbrt_nvrtc_double.cpp
new file mode 100644
index 0000000000..717d116d68
--- /dev/null
+++ b/test/test_cbrt_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/cbrt.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/cbrt.hpp>
+extern "C" __global__ 
+void test_cbrt_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cbrt(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cbrt_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cbrt_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cbrt_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::cbrt(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cbrt_nvrtc_float.cpp b/test/test_cbrt_nvrtc_float.cpp
new file mode 100644
index 0000000000..a595cb8705
--- /dev/null
+++ b/test/test_cbrt_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/cbrt.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/cbrt.hpp>
+extern "C" __global__ 
+void test_cbrt_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cbrt(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cbrt_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cbrt_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cbrt_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::cbrt(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From d4a15eb6b901a3a9a255934d604fe4277b509e7b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 09:36:55 -0400
Subject: [PATCH 230/399] Add lgamma

---
 include/boost/math/special_functions/gamma.hpp | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 70b4ff155c..451b2d69ad 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -2296,6 +2296,15 @@ inline __host__ __device__ T tgamma(T x, const Policy&)
    return boost::math::tgamma(x);
 }
 
+inline __host__ __device__ float lgamma(float x) { return ::lgammaf(x); }
+inline __host__ __device__ double lgamma(double x) { return ::lgamma(x); }
+
+template <typename T, typename Policy>
+inline __host__ __device__ T lgamma(T x, const Policy&)
+{
+   return boost::math::lgamma(x);
+}
+
 } // namespace math
 } // namespace boost
 

From 0dcf8b5982f344382529689407f100a1c4340e8d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 09:37:03 -0400
Subject: [PATCH 231/399] Add lgamma testing

---
 test/test_gamma_nvrtc_double.cpp | 6 +++---
 test/test_gamma_nvrtc_float.cpp  | 6 +++---
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/test/test_gamma_nvrtc_double.cpp b/test/test_gamma_nvrtc_double.cpp
index 6b21bd04b7..9302d1190e 100644
--- a/test/test_gamma_nvrtc_double.cpp
+++ b/test/test_gamma_nvrtc_double.cpp
@@ -24,12 +24,12 @@ const char* cuda_kernel = R"(
 typedef double float_type;
 #include <boost/math/special_functions/gamma.hpp>
 extern "C" __global__ 
-void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_gamma_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
     {
-        out[i] = boost::math::tgamma(in1[i]);
+        out[i] = boost::math::tgamma(in1[i]) + boost::math::lgamma(in2[i]);
     }
 }
 )";
@@ -150,7 +150,7 @@ int main()
         // Verify Result
         for (int i = 0; i < numElements; ++i) 
         {
-            auto res = boost::math::tgamma(h_in1[i]);
+            auto res = boost::math::tgamma(h_in1[i]) + boost::math::lgamma(h_in2[i]);
             if (std::isfinite(res))
             {
                 if (boost::math::epsilon_difference(res, h_out[i]) > 300)
diff --git a/test/test_gamma_nvrtc_float.cpp b/test/test_gamma_nvrtc_float.cpp
index ce312f6916..6e9ba72586 100644
--- a/test/test_gamma_nvrtc_float.cpp
+++ b/test/test_gamma_nvrtc_float.cpp
@@ -24,12 +24,12 @@ const char* cuda_kernel = R"(
 typedef float float_type;
 #include <boost/math/special_functions/gamma.hpp>
 extern "C" __global__ 
-void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_gamma_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
     {
-        out[i] = boost::math::tgamma(in1[i]);
+        out[i] = boost::math::tgamma(in1[i]) + boost::math::lgamma(in2[i]);
     }
 }
 )";
@@ -150,7 +150,7 @@ int main()
         // Verify Result
         for (int i = 0; i < numElements; ++i) 
         {
-            auto res = boost::math::tgamma(h_in1[i]);
+            auto res = boost::math::tgamma(h_in1[i]) + boost::math::lgamma(h_in2[i]);
             if (std::isfinite(res))
             {
                 if (boost::math::epsilon_difference(res, h_out[i]) > 300)

From c1f1a4690b02a198b0b9abbd6cda7baf8cc4c7f1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 09:38:24 -0400
Subject: [PATCH 232/399] Fix template specialization

---
 include/boost/math/special_functions/sign.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index 9fd8bba945..3220130d34 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -217,7 +217,7 @@ __host__ __device__ T copysign(T x, T y)
     return ::copysign(x, y);
 }
 
-template <typename T>
+template <>
 __host__ __device__ float copysign(float x, float y)
 {
     return ::copysignf(x, y);

From ff2632c684f0b3700632beeaf50c2a349ced4721 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 09:54:30 -0400
Subject: [PATCH 233/399] Begin adding a special configuration section for
 NVRTC

---
 include/boost/math/tools/config.hpp | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 152edfa0ee..32b5817d94 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -11,6 +11,8 @@
 #pragma once
 #endif
 
+#ifndef __CUDACC_RTC__
+
 #include <boost/math/tools/is_standalone.hpp>
 
 // Minimum language standard transition
@@ -760,6 +762,25 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #  endif
 #endif
 
+#else // Special section for CUDA NVRTC to ensure we consume no headers
+
+#ifndef BOOST_MATH_STANDALONE
+#  define BOOST_MATH_STANDALONE
+#endif
+
+#define BOOST_MATH_NVRTC_ENABLED
+
+#define BOOST_MATH_GPU_ENABLED __host__ __device__
+
+template <class T>
+BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
+
+#define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b)
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) ::min(a, b)
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) ::max(a, b)
+
+#endif // NVRTC
+
 #endif // BOOST_MATH_TOOLS_CONFIG_HPP
 
 

From ad9d7b7058e524494132941b26b3a9197ec13d7b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 09:54:41 -0400
Subject: [PATCH 234/399] Add config

---
 include/boost/math/special_functions/gamma.hpp | 14 ++++++++------
 include/boost/math/special_functions/sign.hpp  | 12 +++++++-----
 2 files changed, 15 insertions(+), 11 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 451b2d69ad..34e20fd9b8 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -2284,23 +2284,25 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 
 #else
 
+#include <boost/math/tools/config.hpp>
+
 namespace boost {
 namespace math {
 
-inline __host__ __device__ float tgamma(float x) { return ::tgammaf(x); }
-inline __host__ __device__ double tgamma(double x) { return ::tgamma(x); }
+inline BOOST_MATH_GPU_ENABLED float tgamma(float x) { return ::tgammaf(x); }
+inline BOOST_MATH_GPU_ENABLED double tgamma(double x) { return ::tgamma(x); }
 
 template <typename T, typename Policy>
-inline __host__ __device__ T tgamma(T x, const Policy&)
+inline BOOST_MATH_GPU_ENABLED T tgamma(T x, const Policy&)
 {
    return boost::math::tgamma(x);
 }
 
-inline __host__ __device__ float lgamma(float x) { return ::lgammaf(x); }
-inline __host__ __device__ double lgamma(double x) { return ::lgamma(x); }
+inline BOOST_MATH_GPU_ENABLED float lgamma(float x) { return ::lgammaf(x); }
+inline BOOST_MATH_GPU_ENABLED double lgamma(double x) { return ::lgamma(x); }
 
 template <typename T, typename Policy>
-inline __host__ __device__ T lgamma(T x, const Policy&)
+inline BOOST_MATH_GPU_ENABLED T lgamma(T x, const Policy&)
 {
    return boost::math::lgamma(x);
 }
diff --git a/include/boost/math/special_functions/sign.hpp b/include/boost/math/special_functions/sign.hpp
index 3220130d34..4f76522654 100644
--- a/include/boost/math/special_functions/sign.hpp
+++ b/include/boost/math/special_functions/sign.hpp
@@ -196,35 +196,37 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args_permissive<T, U>::typ
 
 #else // NVRTC alias versions
 
+#include <boost/math/tools/config.hpp>
+
 namespace boost {
 namespace math {
 
 template <typename T>
-__host__ __device__ int signbit(T x)
+BOOST_MATH_GPU_ENABLED int signbit(T x)
 {
     return ::signbit(x);
 }
 
 template <typename T>
-__host__ __device__ T changesign(T x)
+BOOST_MATH_GPU_ENABLED T changesign(T x)
 {
     return -x;
 }
 
 template <typename T>
-__host__ __device__ T copysign(T x, T y)
+BOOST_MATH_GPU_ENABLED T copysign(T x, T y)
 {
     return ::copysign(x, y);
 }
 
 template <>
-__host__ __device__ float copysign(float x, float y)
+BOOST_MATH_GPU_ENABLED float copysign(float x, float y)
 {
     return ::copysignf(x, y);
 }
 
 template <typename T>
-__host__ __device__ T sign(T z)
+BOOST_MATH_GPU_ENABLED T sign(T z)
 {
     return (z == 0) ? 0 : ::signbit(z) ? -1 : 1;
 }

From e8b9ed76ac381a9fa16cee0048772b96aefb0724 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 10:14:00 -0400
Subject: [PATCH 235/399] Add additional macros

---
 include/boost/math/tools/config.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 32b5817d94..948e4105b4 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -769,6 +769,8 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #endif
 
 #define BOOST_MATH_NVRTC_ENABLED
+#define BOOST_MATH_CUDA_ENABLED
+#define BOOST_MATH_HAS_GPU_SUPPORT
 
 #define BOOST_MATH_GPU_ENABLED __host__ __device__
 

From b2bfd171a3a0ee1a841c8e27ad0abf1569134f5c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 10:14:51 -0400
Subject: [PATCH 236/399] Remove std headers from CUDA path

---
 include/boost/math/tools/tuple.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index 60867e06d0..da98e67805 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -8,10 +8,8 @@
 #define BOOST_MATH_TUPLE_HPP_INCLUDED
 
 #include <boost/math/tools/config.hpp>
-#include <boost/math/tools/cxx03_warn.hpp>
-#include <tuple>
 
-#ifdef BOOST_MATH_ENABLE_CUDA
+#ifdef BOOST_MATH_CUDA_ENABLED
 
 #include <thrust/pair.h>
 #include <thrust/tuple.h>
@@ -36,6 +34,8 @@ using thrust::tuple_element;
 
 #else
 
+#include <tuple>
+
 namespace boost { 
 namespace math {
 

From 280432cfe5128ab4fb70f58b2dff1780aef14c0b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 10:21:08 -0400
Subject: [PATCH 237/399] Remove non-CUDA tests

---
 test/cuda_jamfile | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 97ba14e81a..44e818c58a 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -9,12 +9,6 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
-# Autodiff Tests
-run test_autodiff_1.cpp ;
-
-# Tools Tests
-run test_polynomial.cpp ;
-
 # Distributions
 run test_arcsine_cdf_double.cu ;
 run test_arcsine_cdf_float.cu ;
@@ -29,7 +23,6 @@ run test_bernoulli_pdf_double.cu ;
 run test_bernoulli_pdf_float.cu ;
 run test_bernoulli_range_support_double.cu ;
 run test_bernoulli_range_support_float.cu ;
-run test_binomial.cpp ;
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;

From 86157576c03f4f575619ac9dd05153f4c6a2b318 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 08:45:16 -0400
Subject: [PATCH 238/399] Fix linking to thrust

---
 test/CMakeLists.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 22799e92ea..4d15c2e4ae 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -10,6 +10,7 @@ if(HAVE_BOOST_TEST)
 
         message(STATUS "Building boost.math with CUDA")
 
+        find_package(CUDA REQUIRED)
         enable_language(CUDA)
         set(CMAKE_CUDA_EXTENSIONS OFF)
 

From d05e3c39bb5f5690f68fe7298068dca1b2caafc6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 11:43:18 -0400
Subject: [PATCH 239/399] Begin to add <type_traits>

---
 include/boost/math/tools/type_traits.hpp | 43 ++++++++++++++++++++++++
 1 file changed, 43 insertions(+)
 create mode 100644 include/boost/math/tools/type_traits.hpp

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
new file mode 100644
index 0000000000..2d6dd1f3a1
--- /dev/null
+++ b/include/boost/math/tools/type_traits.hpp
@@ -0,0 +1,43 @@
+//  Copyright (c) 2024 Matt Borland
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+//  Regular use of <type_traits> is not compatible with CUDA
+//  Adds aliases to unify the support
+//  Also adds convience overloads like is_same_v so we don't have to wait for C++17
+
+#ifndef BOOST_MATH_TOOLS_TYPE_TRAITS
+#define BOOST_MATH_TOOLS_TYPE_TRAITS
+
+#include <boost/math/tools/config.hpp>
+
+namespace boost {
+namespace math {
+
+#ifdef BOOST_MATH_CUDA_ENABLED
+
+using cuda::std::is_void;
+using cuda::std::is_integral;
+using cuda::std::enable_if_t;
+
+#else // STD versions
+
+#include <type_traits>
+
+using std::is_void;
+using std::is_integral;
+using std::enable_if_t;
+
+#endif 
+
+template <typename T>
+BOOST_MATH_STATIC_CONSTEXPR bool is_void_v = boost::math::is_void<T>::value;
+
+template <typename T>
+BOOST_MATH_STATIC_CONSTEXPR bool is_integral_v = boost::math::is_integral<T>::value;
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_TOOLS_TYPE_TRAITS

From 3ec25ab28773eeaafa1a38e571c349467a1c8e1e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 11:43:32 -0400
Subject: [PATCH 240/399] Add definitions of FP classify macros

---
 include/boost/math/tools/config.hpp | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 948e4105b4..594b0f43e6 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -762,6 +762,12 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #  endif
 #endif
 
+#define BOOST_MATH_FP_NAN FP_NAN
+#define BOOST_MATH_FP_INFINITE FP_INFINITE
+#define BOOST_MATH_FP_ZERO FP_ZERO
+#define BOOST_MATH_FP_SUBNORMAL FP_SUBNORMAL
+#define BOOST_MATH_FP_NORMAL FP_NORMAL
+
 #else // Special section for CUDA NVRTC to ensure we consume no headers
 
 #ifndef BOOST_MATH_STANDALONE
@@ -781,6 +787,12 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_GPU_SAFE_MIN(a, b) ::min(a, b)
 #define BOOST_MATH_GPU_SAFE_MAX(a, b) ::max(a, b)
 
+#define BOOST_MATH_FP_NAN 0
+#define BOOST_MATH_FP_INFINITE 1
+#define BOOST_MATH_FP_ZERO 2
+#define BOOST_MATH_FP_SUBNORMAL 3
+#define BOOST_MATH_FP_NORMAL 4
+
 #endif // NVRTC
 
 #endif // BOOST_MATH_TOOLS_CONFIG_HPP

From f7068994634b4de3033b56fe3cfe77eb76554528 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 11:44:03 -0400
Subject: [PATCH 241/399] Add NVRTC support for classification functions

---
 .../math/special_functions/fpclassify.hpp     | 82 ++++++++++++++++++-
 1 file changed, 79 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/fpclassify.hpp b/include/boost/math/special_functions/fpclassify.hpp
index ed75fa35df..a523db317c 100644
--- a/include/boost/math/special_functions/fpclassify.hpp
+++ b/include/boost/math/special_functions/fpclassify.hpp
@@ -1,5 +1,6 @@
 //  Copyright John Maddock 2005-2008.
 //  Copyright (c) 2006-2008 Johan Rade
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,13 +12,17 @@
 #pragma once
 #endif
 
-#include <limits>
-#include <type_traits>
-#include <cmath>
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NVRTC_ENABLED
+
 #include <boost/math/tools/real_cast.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/detail/fp_traits.hpp>
+#include <limits>
+#include <type_traits>
+#include <cmath>
+
 /*!
   \file fpclassify.hpp
   \brief Classify floating-point value as normal, subnormal, zero, infinite, or NaN.
@@ -711,5 +716,76 @@ inline bool (isnan)(__float128 x)
 
 } // namespace math
 } // namespace boost
+
+#else // Special handling generally using the CUDA library
+
+#include <boost/math/tools/type_traits.hpp>
+
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isnan(T x)
+{
+   return false;
+}
+
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isnan(T x)
+{
+   return ::isnan(x);
+}
+
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isinf(T x)
+{
+   return false;
+}
+
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isinf(T x)
+{
+   return ::isinf(x);
+}
+
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isfinite(T x)
+{
+   return true;
+}
+
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+inline BOOST_MATH_GPU_ENABLED bool isfinite(T x)
+{
+   return ::isfinite(x);
+}
+
+template <typename T>
+inline BOOST_MATH_GPU_ENABLED bool isnormal(T x)
+{
+   return x != static_cast<T>(0) && x != static_cast<T>(-0) && 
+            !boost::math::isnan(x) && 
+            !boost::math::isinf(x);
+}
+
+// We skip the check for FP_SUBNORMAL since they are not supported on these platforms
+template <typename T>
+inline BOOST_MATH_GPU_ENABLED int fpclassify(T x)
+{
+   if (boost::math::isnan(x))
+   {
+      return BOOST_MATH_FP_NAN;
+   }
+   else if (boost::math::isinf(x))
+   {
+      return BOOST_MATH_FP_INFINITE;
+   }
+   else if (x == static_cast<T>(0) || x == static_cast<T>(-0))
+   {
+      return BOOST_MATH_FP_ZERO;
+   }
+
+   return BOOST_MATH_FP_NORMAL;
+}
+
+#endif // BOOST_MATH_NVRTC_ENABLED
+
 #endif // BOOST_MATH_FPCLASSIFY_HPP
 

From 39f5c757948110246a31d44e84b885ec0550d9a9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 13:43:08 -0400
Subject: [PATCH 242/399] Add definitions for inline constexpr variables

---
 include/boost/math/tools/config.hpp | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 594b0f43e6..4d79c027e4 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -743,7 +743,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 // See if we can inline them instead
 
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
-#  define BOOST_MATH_STATIC_CONSTEXPR inline constexpr
+#  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr
 #  define BOOST_MATH_STATIC static
 #  ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #    define BOOST_MATH_STATIC_LOCAL_VARIABLE static
@@ -752,11 +752,11 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #  endif
 #else
 #  ifndef BOOST_MATH_HAS_GPU_SUPPORT
-#    define BOOST_MATH_STATIC_CONSTEXPR static constexpr
+#    define BOOST_MATH_INLINE_CONSTEXPR static constexpr
 #    define BOOST_MATH_STATIC static
 #    define BOOST_MATH_STATIC_LOCAL_VARIABLE
 #  else
-#    define BOOST_MATH_STATIC_CONSTEXPR constexpr
+#    define BOOST_MATH_INLINE_CONSTEXPR constexpr
 #    define BOOST_MATH_STATIC constexpr
 #    define BOOST_MATH_STATIC_LOCAL_VARIABLE static
 #  endif
@@ -793,6 +793,12 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_FP_SUBNORMAL 3
 #define BOOST_MATH_FP_NORMAL 4
 
+#if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
+#  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr
+#else
+#  define BOOST_MATH_INLINE_CONSTEXPR constexpr
+#endif
+
 #endif // NVRTC
 
 #endif // BOOST_MATH_TOOLS_CONFIG_HPP

From eb9b5336b3261b27766e36eee4391a5231e342d5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 13:43:19 -0400
Subject: [PATCH 243/399] Fix namespace and SFINAE

---
 .../math/special_functions/fpclassify.hpp      | 18 ++++++++++++------
 1 file changed, 12 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/special_functions/fpclassify.hpp b/include/boost/math/special_functions/fpclassify.hpp
index a523db317c..b0f706b3b3 100644
--- a/include/boost/math/special_functions/fpclassify.hpp
+++ b/include/boost/math/special_functions/fpclassify.hpp
@@ -721,37 +721,40 @@ inline bool (isnan)(__float128 x)
 
 #include <boost/math/tools/type_traits.hpp>
 
-template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+namespace boost {
+namespace math {
+
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isnan(T x)
 {
    return false;
 }
 
-template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isnan(T x)
 {
    return ::isnan(x);
 }
 
-template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isinf(T x)
 {
    return false;
 }
 
-template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isinf(T x)
 {
    return ::isinf(x);
 }
 
-template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>> = true>
+template <typename T, boost::math::enable_if_t<boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isfinite(T x)
 {
    return true;
 }
 
-template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>> = true>
+template <typename T, boost::math::enable_if_t<!boost::math::is_integral_v<T>, bool> = true>
 inline BOOST_MATH_GPU_ENABLED bool isfinite(T x)
 {
    return ::isfinite(x);
@@ -785,6 +788,9 @@ inline BOOST_MATH_GPU_ENABLED int fpclassify(T x)
    return BOOST_MATH_FP_NORMAL;
 }
 
+} // Namespace math
+} // Namespace boost
+
 #endif // BOOST_MATH_NVRTC_ENABLED
 
 #endif // BOOST_MATH_FPCLASSIFY_HPP

From fbf986532fd4898ddc800543bfc848a58ac49b6f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 13:43:49 -0400
Subject: [PATCH 244/399] Add CUDA header and inline constexpr variables

---
 include/boost/math/tools/type_traits.hpp | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index 2d6dd1f3a1..927890a766 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -17,6 +17,8 @@ namespace math {
 
 #ifdef BOOST_MATH_CUDA_ENABLED
 
+#include <cuda/std/type_traits>
+
 using cuda::std::is_void;
 using cuda::std::is_integral;
 using cuda::std::enable_if_t;
@@ -32,10 +34,10 @@ using std::enable_if_t;
 #endif 
 
 template <typename T>
-BOOST_MATH_STATIC_CONSTEXPR bool is_void_v = boost::math::is_void<T>::value;
+BOOST_MATH_INLINE_CONSTEXPR bool is_void_v = boost::math::is_void<T>::value;
 
 template <typename T>
-BOOST_MATH_STATIC_CONSTEXPR bool is_integral_v = boost::math::is_integral<T>::value;
+BOOST_MATH_INLINE_CONSTEXPR bool is_integral_v = boost::math::is_integral<T>::value;
 
 } // namespace math
 } // namespace boost

From 5a0da08bc860ce46978712a6e4ac7ba32741f441 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 14:00:16 -0400
Subject: [PATCH 245/399] Add fpclassify testing

---
 test/nvrtc_jamfile                    |   2 +
 test/test_fpclassify_nvrtc_double.cpp | 198 ++++++++++++++++++++++++++
 test/test_fpclassify_nvrtc_float.cpp  | 198 ++++++++++++++++++++++++++
 3 files changed, 398 insertions(+)
 create mode 100644 test/test_fpclassify_nvrtc_double.cpp
 create mode 100644 test/test_fpclassify_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 55b9b85049..22e6f81ea6 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -12,6 +12,8 @@ project : requirements
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
+run test_fpclassify_nvrtc_double.cpp ;
+run test_fpclassify_nvrtc_float.cpp ;
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
diff --git a/test/test_fpclassify_nvrtc_double.cpp b/test/test_fpclassify_nvrtc_double.cpp
new file mode 100644
index 0000000000..04416e77d2
--- /dev/null
+++ b/test/test_fpclassify_nvrtc_double.cpp
@@ -0,0 +1,198 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/fpclassify.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::isnan(in1[i]) + 
+                 boost::math::isinf(in1[i]) + 
+                 boost::math::isfinite(in1[i]) +
+                 boost::math::isnormal(in1[i]) +
+                 boost::math::fpclassify(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::isnan(h_in1[i]) + 
+                       boost::math::isinf(h_in1[i]) + 
+                       boost::math::isfinite(h_in1[i]) +
+                       boost::math::isnormal(h_in1[i]) +
+                       boost::math::fpclassify(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fpclassify_nvrtc_float.cpp b/test/test_fpclassify_nvrtc_float.cpp
new file mode 100644
index 0000000000..04416e77d2
--- /dev/null
+++ b/test/test_fpclassify_nvrtc_float.cpp
@@ -0,0 +1,198 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/fpclassify.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::isnan(in1[i]) + 
+                 boost::math::isinf(in1[i]) + 
+                 boost::math::isfinite(in1[i]) +
+                 boost::math::isnormal(in1[i]) +
+                 boost::math::fpclassify(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::isnan(h_in1[i]) + 
+                       boost::math::isinf(h_in1[i]) + 
+                       boost::math::isfinite(h_in1[i]) +
+                       boost::math::isnormal(h_in1[i]) +
+                       boost::math::fpclassify(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 1af296498933890feed5527c9252b4d8c59ccc40 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 14:47:07 -0400
Subject: [PATCH 246/399] Fix configuration macros

---
 include/boost/math/tools/config.hpp      | 2 +-
 include/boost/math/tools/tuple.hpp       | 2 +-
 include/boost/math/tools/type_traits.hpp | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 4d79c027e4..e6bc9928ff 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -775,7 +775,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #endif
 
 #define BOOST_MATH_NVRTC_ENABLED
-#define BOOST_MATH_CUDA_ENABLED
+#define BOOST_MATH_ENABLE_CUDA
 #define BOOST_MATH_HAS_GPU_SUPPORT
 
 #define BOOST_MATH_GPU_ENABLED __host__ __device__
diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index da98e67805..f132b97f51 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -9,7 +9,7 @@
 
 #include <boost/math/tools/config.hpp>
 
-#ifdef BOOST_MATH_CUDA_ENABLED
+#ifdef BOOST_MATH_ENABLE_CUDA
 
 #include <thrust/pair.h>
 #include <thrust/tuple.h>
diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index 927890a766..689815a5ad 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -15,7 +15,7 @@
 namespace boost {
 namespace math {
 
-#ifdef BOOST_MATH_CUDA_ENABLED
+#ifdef BOOST_MATH_ENABLE_CUDA
 
 #include <cuda/std/type_traits>
 

From 58f8af649d62a5a8c0bb3b36eb40760acdb5cc06 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 16:41:56 -0400
Subject: [PATCH 247/399] Complete the development of type traits for future
 usage

---
 include/boost/math/tools/type_traits.hpp | 449 +++++++++++++++++++++++
 1 file changed, 449 insertions(+)

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index 689815a5ad..b10f386e91 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -19,26 +19,475 @@ namespace math {
 
 #include <cuda/std/type_traits>
 
+// Helper classes
+using cuda::std::integral_constant;
+using cuda::std::true_type;
+using cuda::std::false_type;
+
+// Primary type categories
 using cuda::std::is_void;
+using cuda::std::is_null_pointer;
 using cuda::std::is_integral;
+using cuda::std::is_floating_point;
+using cuda::std::is_array;
+using cuda::std::is_enum;
+using cuda::std::is_union;
+using cuda::std::is_class;
+using cuda::std::is_function;
+using cuda::std::is_pointer;
+using cuda::std::is_lvalue_reference;
+using cuda::std::is_rvalue_reference;
+using cuda::std::is_member_object_pointer;
+using cuda::std::is_member_function_pointer;
+
+// Composite Type Categories
+using cuda::std::is_fundamental;
+using cuda::std::is_arithmetic;
+using cuda::std::is_scalar;
+using cuda::std::is_object;
+using cuda::std::is_compound;
+using cuda::std::is_reference;
+using cuda::std::is_member_pointer;
+
+// Type properties
+using cuda::std::is_const;
+using cuda::std::is_volatile;
+using cuda::std::is_trivial;
+using cuda::std::is_trivially_copyable;
+using cuda::std::is_standard_layout;
+using cuda::std::is_empty;
+using cuda::std::is_polymorphic;
+using cuda::std::is_abstract;
+using cuda::std::is_final;
+using cuda::std::is_signed;
+using cuda::std::is_unsigned; 
+
+// Supported Operations
+using cuda::std::is_constructible;
+using cuda::std::is_trivially_constructible;
+using cuda::std::is_nothrow_constructible;
+
+using cuda::std::is_default_constructible;
+using cuda::std::is_trivially_default_constructible;
+using cuda::std::is_nothrow_default_constructible;
+
+using cuda::std::is_copy_constructible;
+using cuda::std::is_trivially_copy_constructible;
+using cuda::std::is_nothrow_copy_constructible;
+
+using cuda::std::is_move_constructible;
+using cuda::std::is_trivially_move_constructible;
+using cuda::std::is_nothrow_move_constructible;
+
+using cuda::std::is_assignable;
+using cuda::std::is_trivially_assignable;
+using cuda::std::is_nothrow_assignable;
+
+using cuda::std::is_copy_assignable;
+using cuda::std::is_trivially_copy_assignable;
+using cuda::std::is_nothrow_copy_assignable;
+
+using cuda::std::is_move_assignable;
+using cuda::std::is_trivially_move_assignable;
+using cuda::std::is_nothrow_move_assignable;
+
+using cuda::std::is_destructible;
+using cuda::std::is_trivially_destructible;
+using cuda::std::is_nothrow_destructible;
+
+using cuda::std::has_virtual_destructor;
+
+// Property Queries
+using cuda::std::alignment_of;
+using cuda::std::rank;
+using cuda::std::extent;
+
+// Type Relationships
+using cuda::std::is_same;
+using cuda::std::is_base_of;
+using cuda::std::is_convertible;
+
+// Const-volatility specifiers
+using cuda::std::remove_cv;
+using cuda::std::remove_cv_t;
+using cuda::std::remove_const;
+using cuda::std::remove_const_t;
+using cuda::std::remove_volatile;
+using cuda::std::remove_volatile_t;
+using cuda::std::add_cv;
+using cuda::std::add_cv_t;
+using cuda::std::add_const;
+using cuda::std::add_const_t;
+using cuda::std::add_volatile;
+using cuda::std::add_volatile_t;
+
+// References
+using cuda::std::remove_reference;
+using cuda::std::remove_reference_t;
+using cuda::std::add_lvalue_reference;
+using cuda::std::add_lvalue_reference_t;
+using cuda::std::add_rvalue_reference;
+using cuda::std::add_rvalue_reference_t;
+
+// Pointers
+using cuda::std::remove_pointer;
+using cuda::std::remove_pointer_t;
+using cuda::std::add_pointer;
+using cuda::std::add_pointer_t;
+
+// Sign Modifiers
+using cuda::std::make_signed;
+using cuda::std::make_signed_t;
+using cuda::std::make_unsigned;
+using cuda::std::make_unsigned_t;
+
+// Arrays
+using cuda::std::remove_extent;
+using cuda::std::remove_extent_t;
+using cuda::std::remove_all_extents;
+using cuda::std::remove_all_extents_t;
+
+// Misc transformations
+using cuda::std::decay;
+using cuda::std::decay_t;
+using cuda::std::enable_if;
 using cuda::std::enable_if_t;
+using cuda::std::conditional;
+using cuda::std::conditional_t;
+using cuda::std::common_type;
+using cuda::std::common_type_t;
+using cuda::std::underlying_type;
+using cuda::std::underlying_type_t;
 
 #else // STD versions
 
 #include <type_traits>
 
+// Helper classes
+using std::integral_constant;
+using std::true_type;
+using std::false_type;
+
+// Primary type categories
 using std::is_void;
+using std::is_null_pointer;
 using std::is_integral;
+using std::is_floating_point;
+using std::is_array;
+using std::is_enum;
+using std::is_union;
+using std::is_class;
+using std::is_function;
+using std::is_pointer;
+using std::is_lvalue_reference;
+using std::is_rvalue_reference;
+using std::is_member_object_pointer;
+using std::is_member_function_pointer;
+
+// Composite Type Categories
+using std::is_fundamental;
+using std::is_arithmetic;
+using std::is_scalar;
+using std::is_object;
+using std::is_compound;
+using std::is_reference;
+using std::is_member_pointer;
+
+// Type properties
+using std::is_const;
+using std::is_volatile;
+using std::is_trivial;
+using std::is_trivially_copyable;
+using std::is_standard_layout;
+using std::is_empty;
+using std::is_polymorphic;
+using std::is_abstract;
+using std::is_final;
+using std::is_signed;
+using std::is_unsigned; 
+
+// Supported Operations
+using std::is_constructible;
+using std::is_trivially_constructible;
+using std::is_nothrow_constructible;
+
+using std::is_default_constructible;
+using std::is_trivially_default_constructible;
+using std::is_nothrow_default_constructible;
+
+using std::is_copy_constructible;
+using std::is_trivially_copy_constructible;
+using std::is_nothrow_copy_constructible;
+
+using std::is_move_constructible;
+using std::is_trivially_move_constructible;
+using std::is_nothrow_move_constructible;
+
+using std::is_assignable;
+using std::is_trivially_assignable;
+using std::is_nothrow_assignable;
+
+using std::is_copy_assignable;
+using std::is_trivially_copy_assignable;
+using std::is_nothrow_copy_assignable;
+
+using std::is_move_assignable;
+using std::is_trivially_move_assignable;
+using std::is_nothrow_move_assignable;
+
+using std::is_destructible;
+using std::is_trivially_destructible;
+using std::is_nothrow_destructible;
+
+using std::has_virtual_destructor;
+
+// Property Queries
+using std::alignment_of;
+using std::rank;
+using std::extent;
+
+// Type Relationships
+using std::is_same;
+using std::is_base_of;
+using std::is_convertible;
+
+// Const-volatility specifiers
+using std::remove_cv;
+using std::remove_cv_t;
+using std::remove_const;
+using std::remove_const_t;
+using std::remove_volatile;
+using std::remove_volatile_t;
+using std::add_cv;
+using std::add_cv_t;
+using std::add_const;
+using std::add_const_t;
+using std::add_volatile;
+using std::add_volatile_t;
+
+// References
+using std::remove_reference;
+using std::remove_reference_t;
+using std::add_lvalue_reference;
+using std::add_lvalue_reference_t;
+using std::add_rvalue_reference;
+using std::add_rvalue_reference_t;
+
+// Pointers
+using std::remove_pointer;
+using std::remove_pointer_t;
+using std::add_pointer;
+using std::add_pointer_t;
+
+// Sign Modifiers
+using std::make_signed;
+using std::make_signed_t;
+using std::make_unsigned;
+using std::make_unsigned_t;
+
+// Arrays
+using std::remove_extent;
+using std::remove_extent_t;
+using std::remove_all_extents;
+using std::remove_all_extents_t;
+
+// Misc transformations
+using std::decay;
+using std::decay_t;
+using std::enable_if;
 using std::enable_if_t;
+using std::conditional;
+using std::conditional_t;
+using std::common_type;
+using std::common_type_t;
+using std::underlying_type;
+using std::underlying_type_t;
 
 #endif 
 
+template <bool B>
+using bool_constant = boost::math::integral_constant<bool, B>;
+
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_void_v = boost::math::is_void<T>::value;
 
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_null_pointer_v = boost::math::is_null_pointer<T>::value;
+
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_integral_v = boost::math::is_integral<T>::value;
 
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_floating_point_v = boost::math::is_floating_point<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_array_v = boost::math::is_array<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_enum_v = boost::math::is_enum<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_union_v = boost::math::is_union<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_class_v = boost::math::is_class<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_function_v = boost::math::is_function<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_pointer_v = boost::math::is_pointer<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_lvalue_reference_v = boost::math::is_lvalue_reference<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_rvalue_reference_v = boost::math::is_rvalue_reference<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_member_object_pointer_v = boost::math::is_member_object_pointer<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_member_function_pointer_v = boost::math::is_member_function_pointer<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_fundamental_v = boost::math::is_fundamental<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_arithmetic_v = boost::math::is_arithmetic<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_scalar_v = boost::math::is_scalar<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_object_v = boost::math::is_object<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_compound_v = boost::math::is_compound<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_reference_v = boost::math::is_reference<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_member_pointer_v = boost::math::is_member_pointer<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_const_v = boost::math::is_const<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_volatile_v = boost::math::is_volatile<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivial_v = boost::math::is_trivial<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_copyable_v = boost::math::is_trivially_copyable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_standard_layout_v = boost::math::is_standard_layout<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_empty_v = boost::math::is_empty<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_polymorphic_v = boost::math::is_polymorphic<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_abstract_v = boost::math::is_abstract<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_final_v = boost::math::is_final<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_aggregate_v = boost::math::is_aggregate<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_signed_v = boost::math::is_signed<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_unsigned_v = boost::math::is_unsigned<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_constructible_v = boost::math::is_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_constructible_v = boost::math::is_trivially_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_constructible_v = boost::math::is_nothrow_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_default_constructible_v = boost::math::is_default_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_default_constructible_v = boost::math::is_trivially_default_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_default_constructible_v = boost::math::is_nothrow_default_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_copy_constructible_v = boost::math::is_copy_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_copy_constructible_v = boost::math::is_trivially_copy_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_copy_constructible_v = boost::math::is_nothrow_copy_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_move_constructible_v = boost::math::is_move_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_move_constructible_v = boost::math::is_trivially_move_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_move_constructible_v = boost::math::is_nothrow_move_constructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_assignable_v = boost::math::is_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_assignable_v = boost::math::is_trivially_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_assignable_v = boost::math::is_nothrow_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_copy_assignable_v = boost::math::is_copy_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_copy_assignable_v = boost::math::is_trivially_copy_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_copy_assignable_v = boost::math::is_nothrow_copy_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_move_assignable_v = boost::math::is_move_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_move_assignable_v = boost::math::is_trivially_move_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_move_assignable_v = boost::math::is_nothrow_move_assignable<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_destructible_v = boost::math::is_destructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_destructible_v = boost::math::is_trivially_destructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_destructible_v = boost::math::is_nothrow_destructible<T>::value;
+
+template <typename T>
+BOOST_MATH_INLINE_CONSTEXPR bool has_virtual_destructor_v = boost::math::has_virtual_destructor<T>::value;
+
+template <typename T, typename U>
+BOOST_MATH_INLINE_CONSTEXPR bool is_same_v = boost::math::is_same<T, U>::value;
+
+template <typename T, typename U>
+BOOST_MATH_INLINE_CONSTEXPR bool is_base_of_v = boost::math::is_base_of<T, U>::value;
+
 } // namespace math
 } // namespace boost
 

From 467a84c08820babca40de4ad5c61aaff23d376e4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 7 Aug 2024 17:05:35 -0400
Subject: [PATCH 248/399] Fix aliases

---
 include/boost/math/tools/type_traits.hpp | 15 ++++++---------
 1 file changed, 6 insertions(+), 9 deletions(-)

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index b10f386e91..3b67efc034 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -398,9 +398,6 @@ BOOST_MATH_INLINE_CONSTEXPR bool is_abstract_v = boost::math::is_abstract<T>::va
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_final_v = boost::math::is_final<T>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_aggregate_v = boost::math::is_aggregate<T>::value;
-
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_signed_v = boost::math::is_signed<T>::value;
 
@@ -443,14 +440,14 @@ BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_move_constructible_v = boost::math
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_move_constructible_v = boost::math::is_nothrow_move_constructible<T>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_assignable_v = boost::math::is_assignable<T>::value;
+template <typename T, typename U>
+BOOST_MATH_INLINE_CONSTEXPR bool is_assignable_v = boost::math::is_assignable<T, U>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_assignable_v = boost::math::is_trivially_assignable<T>::value;
+template <typename T, typename U>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_assignable_v = boost::math::is_trivially_assignable<T, U>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_assignable_v = boost::math::is_nothrow_assignable<T>::value;
+template <typename T, typename U>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_assignable_v = boost::math::is_nothrow_assignable<T, U>::value;
 
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_copy_assignable_v = boost::math::is_copy_assignable<T>::value;

From 044118770b4d2d137732ee172fddd341666d0544 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 08:47:42 -0400
Subject: [PATCH 249/399] Fix linking with thrust

---
 test/CMakeLists.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 4d15c2e4ae..fef1189f1d 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -16,7 +16,7 @@ if(HAVE_BOOST_TEST)
 
         enable_testing()
 
-        boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework )
+        boost_test_jamfile(FILE cuda_jamfile LINK_LIBRARIES Boost::math Boost::assert Boost::concept_check Boost::config Boost::core Boost::integer Boost::lexical_cast Boost::multiprecision Boost::predef Boost::random Boost::static_assert Boost::throw_exception Boost::unit_test_framework ${CUDA_LIBRARIES} INCLUDE_DIRECTORIES ${CUDA_INCLUDE_DIRS}  )
 
     elseif (BOOST_MATH_ENABLE_NVRTC)
 

From 37875f2a8ba08251a37d7900bf6d366ebcefc65c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 09:41:01 -0400
Subject: [PATCH 250/399] Fix min/max usage

---
 include/boost/math/tools/config.hpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index e6bc9928ff..712105a499 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -784,8 +784,8 @@ template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
 
 #define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b)
-#define BOOST_MATH_GPU_SAFE_MIN(a, b) ::min(a, b)
-#define BOOST_MATH_GPU_SAFE_MAX(a, b) ::max(a, b)
+#define BOOST_MATH_GPU_SAFE_MIN(a, b) (::min)(a, b)
+#define BOOST_MATH_GPU_SAFE_MAX(a, b) (::max)(a, b)
 
 #define BOOST_MATH_FP_NAN 0
 #define BOOST_MATH_FP_INFINITE 1

From 687125c7a1439d7f0b34031549f93acf501ce1ac Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 9 Aug 2024 08:01:11 -0400
Subject: [PATCH 251/399] Fix gamma unused parameter warning

---
 include/boost/math/special_functions/gamma.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 34e20fd9b8..dc017462e1 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -110,7 +110,7 @@ BOOST_MATH_GPU_ENABLED T sinpx(T z)
 // tgamma(z), with Lanczos support:
 //
 template <class T, class Policy, class Lanczos>
-BOOST_MATH_GPU_ENABLED T gamma_imp_final(T z, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T gamma_imp_final(T z, const Policy& pol, const Lanczos&)
 {
    BOOST_MATH_STD_USING
 

From 53d5dab3191bb67ebb1e4d2e9f1a7ab097977fa1 Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Sat, 10 Aug 2024 15:28:00 +0100
Subject: [PATCH 252/399] Simplify and remove redundant code from Cauchy. Fixes
 https://github.com/boostorg/math/issues/1171

---
 include/boost/math/distributions/cauchy.hpp | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index 91c848c911..716940119c 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -105,14 +105,13 @@ BOOST_MATH_GPU_ENABLED RealType cdf_imp(const cauchy_distribution<RealType, Poli
 template <class RealType, class Policy>
 BOOST_MATH_GPU_ENABLED RealType quantile_imp(
       const cauchy_distribution<RealType, Policy>& dist,
-      const RealType& p,
+      RealType p,
       bool complement)
 {
    // This routine implements the quantile for the Cauchy distribution,
    // the value p may be the probability, or its complement if complement=true.
    //
-   // The procedure first performs argument reduction on p to avoid error
-   // when calculating the tangent, then calculates the distance from the
+   // The procedure calculates the distance from the
    // mid-point of the distribution.  This is either added or subtracted
    // from the location parameter depending on whether `complement` is true.
    //
@@ -144,16 +143,15 @@ BOOST_MATH_GPU_ENABLED RealType quantile_imp(
       return (complement ? 1 : -1) * policies::raise_overflow_error<RealType>(function, 0, Policy());
    }
 
-   RealType P = p - floor(p);   // argument reduction of p:
-   if(P > 0.5)
+   if(p > 0.5)
    {
-      P = P - 1;
+      p = p - 1;
    }
-   if(P == 0.5)   // special case:
+   if(p == 0.5)   // special case:
    {
       return location;
    }
-   result = -scale / tan(constants::pi<RealType>() * P);
+   result = -scale / tan(constants::pi<RealType>() * p);
    return complement ? RealType(location - result) : RealType(location + result);
 } // quantile
 

From 3714b9e5a0ff88c7956faaf66fd8c39a6bd1ea09 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 12 Aug 2024 09:59:38 -0400
Subject: [PATCH 253/399] Document logpdf, logcdf, and specializations

---
 doc/distributions/dist_tutorial.qbk | 37 +++++++++++++++++++++++++++++
 1 file changed, 37 insertions(+)

diff --git a/doc/distributions/dist_tutorial.qbk b/doc/distributions/dist_tutorial.qbk
index ee28dbdca5..80e8e2e458 100644
--- a/doc/distributions/dist_tutorial.qbk
+++ b/doc/distributions/dist_tutorial.qbk
@@ -128,12 +128,49 @@ And quantiles are just the same:
    quantile(my_dist, p);  // Returns the value of the random variable x
                           // such that cdf(my_dist, x) == p.
 
+As are the logcdf (Natural log of the Cumulative Distribution Function):
+
+   logcdf(my_dist, x); // Returns logcdf at at point x of distribution my_dist.
+
+And the logpdf (Natural log of the Probability Density Function):
+
+   logpdf(my_dist, x); // Returns logpdf at point x of distribution my_dist.
+
 If you're wondering why these aren't member functions, it's to
 make the library more easily extensible: if you want to add additional
 generic operations - let's say the /n'th moment/ - then all you have to
 do is add the appropriate non-member functions, overloaded for each
 implemented distribution type.
 
+The logcdf and logpdf functions are minimally calculated with log(cdf(my_dist, x)),
+and log(pdf(my_dist, x)) respectively. The following distributions have specialized
+implementations of the logcdf:
+
+* Exponential
+* Extreme Value
+* Geometric
+* Laplace
+* Logistic
+* Pareto
+* Rayleigh
+* Weibull
+
+And the following distributions have specialized implementations of logpdf:
+
+* Exponential
+* Extreme Value
+* Gamma
+* Inverse Gamma
+* Inverse Gaussian
+* Laplace
+* Normal
+* Poisson
+* Rayleigh
+* Weibull
+
+These above listed specialized implementations allow a higher degree of precision
+than can be obtained through the naive generic method.
+
 [tip
 
 [*Random numbers that approximate Quantiles of Distributions]

From 0d7c9447522626edba05170f15a4cdadc23b0d8d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 12 Aug 2024 14:02:22 -0400
Subject: [PATCH 254/399] Update non-members docs and __usual_accessors macro

---
 doc/distributions/non_members.qbk | 16 ++++++++++++++++
 doc/math.qbk                      |  2 +-
 2 files changed, 17 insertions(+), 1 deletion(-)

diff --git a/doc/distributions/non_members.qbk b/doc/distributions/non_members.qbk
index 9c900bf127..99728b8700 100644
--- a/doc/distributions/non_members.qbk
+++ b/doc/distributions/non_members.qbk
@@ -17,6 +17,8 @@ to go straight to the function you want if you already know its name.
 * __hazard.
 * __kurtosis.
 * __kurtosis_excess
+* __logcdf.
+* __logpdf.
 * __mean.
 * __median.
 * __mode.
@@ -349,6 +351,20 @@ Kurtosis excess can have a value from -2 to + infinity.
 
 The kurtosis excess of a normal distribution is zero.
 
+[h4:logcdf Natural Log of the Cumulative Distribution Function]
+
+   template <class RealType, ``__Policy``>
+   RealType logcdf(const ``['Distribution-Type]``<RealType, ``__Policy``>& dist);
+
+Returns the natural log of the CDF of distribution /dist/.
+
+[h4:logpdf Natural Log of the Probability Density Function]
+
+   template <class RealType, ``__Policy``>
+   RealType logcdf(const ``['Distribution-Type]``<RealType, ``__Policy``>& dist);
+
+Returns the natural log of the CDF of distribution /dist/.
+
 [h4:cdfPQ P and Q]
 
 The terms P and Q are sometimes used to refer to the __cdf
diff --git a/doc/math.qbk b/doc/math.qbk
index 4b8804dbbb..d6b90efb0b 100644
--- a/doc/math.qbk
+++ b/doc/math.qbk
@@ -424,7 +424,7 @@ and use the function's name as the link text.]
 
 
 [def __usual_accessors __cdf, __pdf, __quantile, __hazard,
-   __chf, __mean, __median, __mode, __variance, __sd, __skewness,
+   __chf, __logcdf, __logpdf, __mean, __median, __mode, __variance, __sd, __skewness,
    __kurtosis, __kurtosis_excess, __range and __support]
 
 [def __real_concept [link math_toolkit.real_concepts  real concept]]

From d892e030700d80b999a5301a720d1d104c46d480 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 12 Aug 2024 14:11:43 -0400
Subject: [PATCH 255/399] Add notes to individual dist docs for specializations

---
 doc/distributions/exponential.qbk      | 3 +++
 doc/distributions/extreme_value.qbk    | 3 +++
 doc/distributions/gamma.qbk            | 3 +++
 doc/distributions/geometric.qbk        | 3 +++
 doc/distributions/inverse_gamma.qbk    | 3 +++
 doc/distributions/inverse_gaussian.qbk | 3 +++
 doc/distributions/laplace.qbk          | 3 +++
 doc/distributions/logistic.qbk         | 3 +++
 doc/distributions/pareto.qbk           | 3 +++
 doc/distributions/poisson.qbk          | 3 +++
 doc/distributions/rayleigh.qbk         | 3 +++
 doc/distributions/weibull.qbk          | 3 +++
 12 files changed, 36 insertions(+)

diff --git a/doc/distributions/exponential.qbk b/doc/distributions/exponential.qbk
index 043818b4a4..0b7ea5cbb1 100644
--- a/doc/distributions/exponential.qbk
+++ b/doc/distributions/exponential.qbk
@@ -57,6 +57,9 @@ that are generic to all distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[0, +[infin]\].
 
+In this distribution the implementation of both `logcdf`, and `logpdf` are specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The exponential distribution is implemented in terms of the 
diff --git a/doc/distributions/extreme_value.qbk b/doc/distributions/extreme_value.qbk
index 314917ebc1..56c4fb5dfd 100644
--- a/doc/distributions/extreme_value.qbk
+++ b/doc/distributions/extreme_value.qbk
@@ -81,6 +81,9 @@ that are generic to all distributions are supported: __usual_accessors.
 
 The domain of the random parameter is \[-[infin], +[infin]\].
 
+In this distribution the implementation of both `logcdf`, and `logpdf` are specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The extreme value distribution is implemented in terms of the 
diff --git a/doc/distributions/gamma.qbk b/doc/distributions/gamma.qbk
index eefcc84a0c..8e53ec6ee4 100644
--- a/doc/distributions/gamma.qbk
+++ b/doc/distributions/gamma.qbk
@@ -99,6 +99,9 @@ distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[0,+[infin]\].
 
+In this distribution the implementation of `logpdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The gamma distribution is implemented in terms of the 
diff --git a/doc/distributions/geometric.qbk b/doc/distributions/geometric.qbk
index 7aa1a33439..9992b016de 100644
--- a/doc/distributions/geometric.qbk
+++ b/doc/distributions/geometric.qbk
@@ -303,6 +303,9 @@ the context of this distribution:
    ``quantile(complement(geometric(p), P))``]]
 ]
 
+In this distribution the implementation of `logcdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 This distribution is implemented using the pow and exp functions, so most results
diff --git a/doc/distributions/inverse_gamma.qbk b/doc/distributions/inverse_gamma.qbk
index 8fccbc19c4..8fb64dde84 100644
--- a/doc/distributions/inverse_gamma.qbk
+++ b/doc/distributions/inverse_gamma.qbk
@@ -87,6 +87,9 @@ The domain of the random variate is \[0,+[infin]\].
 [note Unlike some definitions, this implementation supports a random variate 
 equal to zero as a special case, returning zero for pdf and cdf.]
 
+In this distribution the implementation of `logpdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The inverse gamma distribution is implemented in terms of the 
diff --git a/doc/distributions/inverse_gaussian.qbk b/doc/distributions/inverse_gaussian.qbk
index c5b824385f..776a377726 100644
--- a/doc/distributions/inverse_gaussian.qbk
+++ b/doc/distributions/inverse_gaussian.qbk
@@ -115,6 +115,9 @@ The domain of the random variate is \[0,+[infin]).
 [note Unlike some definitions, this implementation supports a random variate 
 equal to zero as a special case, returning zero for both pdf and cdf.]
 
+In this distribution the implementation of `logpdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The inverse_gaussian distribution is implemented in terms of the 
diff --git a/doc/distributions/laplace.qbk b/doc/distributions/laplace.qbk
index 93327e0228..998072811f 100644
--- a/doc/distributions/laplace.qbk
+++ b/doc/distributions/laplace.qbk
@@ -76,6 +76,9 @@ distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[-[infin],+[infin]\].
 
+In this distribution the implementation of both `logcdf`, and `logpdf` are specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The laplace distribution is implemented in terms of the
diff --git a/doc/distributions/logistic.qbk b/doc/distributions/logistic.qbk
index 0a22b48d42..ba1b29a17e 100644
--- a/doc/distributions/logistic.qbk
+++ b/doc/distributions/logistic.qbk
@@ -67,6 +67,9 @@ At `p=1` and `p=0`, the quantile function returns the result of
 quantile function returns the result of -__overflow_error and 
 +__overflow_error respectively. 
 
+In this distribution the implementation of `logcdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The logistic distribution is implemented in terms of the `std::exp` 
diff --git a/doc/distributions/pareto.qbk b/doc/distributions/pareto.qbk
index fcc7eee425..7938ed86d8 100644
--- a/doc/distributions/pareto.qbk
+++ b/doc/distributions/pareto.qbk
@@ -73,6 +73,9 @@ distributions are supported: __usual_accessors.
 
 The supported domain of the random variable is \[scale, [infin]\].
 
+In this distribution the implementation of `logcdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The Pareto distribution is implemented in terms of the
diff --git a/doc/distributions/poisson.qbk b/doc/distributions/poisson.qbk
index 50a3b12cea..a1ccc1b8b7 100644
--- a/doc/distributions/poisson.qbk
+++ b/doc/distributions/poisson.qbk
@@ -62,6 +62,9 @@ distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[0, [infin]\].
 
+In this distribution the implementation of `logpdf` is specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The Poisson distribution is implemented in terms of the 
diff --git a/doc/distributions/rayleigh.qbk b/doc/distributions/rayleigh.qbk
index 5fd6fe44c2..89054ac0e3 100644
--- a/doc/distributions/rayleigh.qbk
+++ b/doc/distributions/rayleigh.qbk
@@ -77,6 +77,9 @@ distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[0, max_value\].
 
+In this distribution the implementation of both `logcdf`, and `logpdf` are specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The Rayleigh distribution is implemented in terms of the
diff --git a/doc/distributions/weibull.qbk b/doc/distributions/weibull.qbk
index 95c9e461e2..d01ceded9e 100644
--- a/doc/distributions/weibull.qbk
+++ b/doc/distributions/weibull.qbk
@@ -88,6 +88,9 @@ distributions are supported: __usual_accessors.
 
 The domain of the random variable is \[0, [infin]\].
 
+In this distribution the implementation of both `logcdf`, and `logpdf` are specialized
+to improve numerical accuracy.
+
 [h4 Accuracy]
 
 The Weibull distribution is implemented in terms of the 

From d5bab81593c09e6ff2ff2839b452ae99f474122e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 12 Aug 2024 14:44:33 -0400
Subject: [PATCH 256/399] Remove now unused parameter

---
 include/boost/math/special_functions/erf.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/erf.hpp b/include/boost/math/special_functions/erf.hpp
index 0b311c4641..789d116b90 100644
--- a/include/boost/math/special_functions/erf.hpp
+++ b/include/boost/math/special_functions/erf.hpp
@@ -199,7 +199,7 @@ T erf_imp(T z, bool invert, const Policy& pol, const Tag& t)
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int, 53>& t)
+BOOST_MATH_GPU_ENABLED T erf_imp(T z, bool invert, const Policy& pol, const std::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING
 

From a30b10b803abfb18d60322ad9c1b660bdbca9804 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 09:59:55 -0400
Subject: [PATCH 257/399] Rename macro for clarity

---
 include/boost/math/special_functions/fpclassify.hpp | 4 ++--
 include/boost/math/tools/config.hpp                 | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/special_functions/fpclassify.hpp b/include/boost/math/special_functions/fpclassify.hpp
index b0f706b3b3..0ac9470f28 100644
--- a/include/boost/math/special_functions/fpclassify.hpp
+++ b/include/boost/math/special_functions/fpclassify.hpp
@@ -14,7 +14,7 @@
 
 #include <boost/math/tools/config.hpp>
 
-#ifndef BOOST_MATH_NVRTC_ENABLED
+#ifndef BOOST_MATH_HAS_NVRTC
 
 #include <boost/math/tools/real_cast.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -791,7 +791,7 @@ inline BOOST_MATH_GPU_ENABLED int fpclassify(T x)
 } // Namespace math
 } // Namespace boost
 
-#endif // BOOST_MATH_NVRTC_ENABLED
+#endif // BOOST_MATH_HAS_NVRTC
 
 #endif // BOOST_MATH_FPCLASSIFY_HPP
 
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 712105a499..f8796c8334 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -774,7 +774,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #  define BOOST_MATH_STANDALONE
 #endif
 
-#define BOOST_MATH_NVRTC_ENABLED
+#define BOOST_MATH_HAS_NVRTC
 #define BOOST_MATH_ENABLE_CUDA
 #define BOOST_MATH_HAS_GPU_SUPPORT
 

From 9cd9be397ae56fcc51d558fa04bba7eef7268537 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 10:22:26 -0400
Subject: [PATCH 258/399] Fix test set

---
 test/test_fpclassify_nvrtc_double.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/test_fpclassify_nvrtc_double.cpp b/test/test_fpclassify_nvrtc_double.cpp
index 04416e77d2..0a99ddaa8e 100644
--- a/test/test_fpclassify_nvrtc_double.cpp
+++ b/test/test_fpclassify_nvrtc_double.cpp
@@ -20,10 +20,10 @@
 #include <boost/math/special_functions/fpclassify.hpp>
 #include <boost/math/special_functions/relative_difference.hpp>
 
-typedef float float_type;
+typedef double float_type;
 
 const char* cuda_kernel = R"(
-typedef float float_type;
+typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/special_functions/fpclassify.hpp>
 extern "C" __global__ 

From 16b715f7893922de1c841d4eb1c4a37b2d245f9a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 10:35:41 -0400
Subject: [PATCH 259/399] Add round support to NVRTC

---
 .../boost/math/special_functions/round.hpp    | 85 +++++++++++++++++++
 1 file changed, 85 insertions(+)

diff --git a/include/boost/math/special_functions/round.hpp b/include/boost/math/special_functions/round.hpp
index 3df0145b62..7a76cd32ff 100644
--- a/include/boost/math/special_functions/round.hpp
+++ b/include/boost/math/special_functions/round.hpp
@@ -12,6 +12,9 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/ccmath/detail/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -241,4 +244,86 @@ BOOST_MATH_GPU_ENABLED inline long long llround(const T& v)
 
 }} // namespaces
 
+#else // Specialized NVRTC overloads
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED T round(T x)
+{
+   return ::round(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED float round(float x)
+{
+   return ::roundf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED T round(T x, const Policy&)
+{
+   return ::round(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED float round(float x, const Policy&)
+{
+   return ::roundf(x);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED long lround(T x)
+{
+   return ::lround(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED long lround(float x)
+{
+   return ::lroundf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED long lround(T x, const Policy&)
+{
+   return ::lround(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED long lround(float x, const Policy&)
+{
+   return ::lroundf(x);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED long long llround(T x)
+{
+   return ::llround(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED long long llround(float x)
+{
+   return ::llroundf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED long long llround(T x, const Policy&)
+{
+   return ::llround(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED long long llround(float x, const Policy&)
+{
+   return ::llroundf(x);
+}
+
+} // Namespace math
+} // Namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif // BOOST_MATH_ROUND_HPP

From ae3ea6f201542a1fff6361e683b94c5728eee8d4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 10:35:52 -0400
Subject: [PATCH 260/399] Add testing of round on NVRTC

---
 test/nvrtc_jamfile               |   2 +
 test/test_round_nvrtc_double.cpp | 194 +++++++++++++++++++++++++++++++
 test/test_round_nvrtc_float.cpp  | 194 +++++++++++++++++++++++++++++++
 3 files changed, 390 insertions(+)
 create mode 100644 test/test_round_nvrtc_double.cpp
 create mode 100644 test/test_round_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 22e6f81ea6..6d6327ddb2 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -16,5 +16,7 @@ run test_fpclassify_nvrtc_double.cpp ;
 run test_fpclassify_nvrtc_float.cpp ;
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
+run test_round_nvrtc_double.cpp ;
+run test_round_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
diff --git a/test/test_round_nvrtc_double.cpp b/test/test_round_nvrtc_double.cpp
new file mode 100644
index 0000000000..228e3dd674
--- /dev/null
+++ b/test/test_round_nvrtc_double.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/round.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/round.hpp>
+extern "C" __global__ 
+void test_round_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::round(in1[i]) + 
+                 boost::math::lround(in1[i]) + 
+                 boost::math::llround(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_round_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_round_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_round_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::round(h_in1[i]) + 
+                       boost::math::lround(h_in1[i]) + 
+                       boost::math::llround(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_round_nvrtc_float.cpp b/test/test_round_nvrtc_float.cpp
new file mode 100644
index 0000000000..8554add7cd
--- /dev/null
+++ b/test/test_round_nvrtc_float.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/round.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/round.hpp>
+extern "C" __global__ 
+void test_round_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::round(in1[i]) + 
+                 boost::math::lround(in1[i]) + 
+                 boost::math::llround(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_round_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_round_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_round_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::round(h_in1[i]) + 
+                       boost::math::lround(h_in1[i]) + 
+                       boost::math::llround(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 6699e05570133f7be573252b43dbd6c44dc0ab5f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 12:08:58 -0400
Subject: [PATCH 261/399] Add NVRTC compatible numeric limits definitions

---
 include/boost/math/tools/numeric_limits.hpp | 426 +++++++++++++++++++-
 1 file changed, 424 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
index 7d3d5db268..8db05b065a 100644
--- a/include/boost/math/tools/numeric_limits.hpp
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -7,22 +7,35 @@
 //  GPU platforms like CUDA since they are missing the __device__ marker
 //  and libcu++ does not provide something analogous.
 //  Rather than using giant if else blocks make our own version of numeric limits
+//
+//  On the CUDA NVRTC platform we use a best attempt at emulating the functions
+//  and values since we do not have any macros to go off of.
+//  Use the values as found on GCC 11.4 RHEL 9.4 x64
 
 #ifndef BOOST_MATH_TOOLS_NUMERIC_LIMITS_HPP
 #define BOOST_MATH_TOOLS_NUMERIC_LIMITS_HPP
 
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <type_traits>
 #include <limits>
 #include <climits>
+#include <cfloat>
+
+#endif
 
 namespace boost {
 namespace math {
 
 template <typename T>
-struct numeric_limits : public std::numeric_limits<T> {};
+struct numeric_limits 
+#ifndef BOOST_MATH_HAS_NVRTC
+: public std::numeric_limits<T> {};
+#endif
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+#if defined(BOOST_MATH_HAS_GPU_SUPPORT) && !defined(BOOST_MATH_HAS_NVRTC)
 
 template <>
 struct numeric_limits<float>
@@ -456,6 +469,415 @@ struct numeric_limits<bool>
     BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool denorm_min    () { return false; }
 };
 
+#elif defined(BOOST_MATH_HAS_NVRTC) // Pure NVRTC support - Removes rounding style and approximates the traits
+
+template <>
+struct numeric_limits<float>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = false;
+    BOOST_MATH_STATIC constexpr bool is_exact = false;
+    BOOST_MATH_STATIC constexpr bool has_infinity = true;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = true;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = true;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = true;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 24;
+    BOOST_MATH_STATIC constexpr int digits10 = 6;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 9;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = -125;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = -37;
+    BOOST_MATH_STATIC constexpr int max_exponent = 128;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 38;
+    BOOST_MATH_STATIC constexpr bool traps = false;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float (min)         () { return 1.17549435e-38F; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float (max)         () { return 3.40282347e+38F; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float lowest        () { return -3.40282347e+38F; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float epsilon       () { return 1.1920929e-07; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float round_error   () { return 0.5F; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float infinity      () { return __int_as_float(0x7f800000); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float quiet_NaN     () { return __int_as_float(0x7fc00000); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float signaling_NaN () { return __int_as_float(0x7fa00000); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr float denorm_min    () { return 1.4013e-45F; }
+};
+
+template <>
+struct numeric_limits<double>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = false;
+    BOOST_MATH_STATIC constexpr bool is_exact = false;
+    BOOST_MATH_STATIC constexpr bool has_infinity = true;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = true;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = true;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = true;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 53;
+    BOOST_MATH_STATIC constexpr int digits10 = 15;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 21;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = -1021;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = -307;
+    BOOST_MATH_STATIC constexpr int max_exponent = 1024;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 308;
+    BOOST_MATH_STATIC constexpr bool traps = false;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double (min)         () { return 2.2250738585072014e-308; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double (max)         () { return 1.7976931348623157e+308; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double lowest        () { return -1.7976931348623157e+308; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double epsilon       () { return 2.2204460492503131e-16; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double round_error   () { return 0.5; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double infinity      () { return __longlong_as_double(0x7ff0000000000000ULL); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double quiet_NaN     () { return __longlong_as_double(0x7ff8000000000000ULL); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double signaling_NaN () { return __longlong_as_double(0x7ff4000000000000ULL); }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr double denorm_min    () { return 4.9406564584124654e-324; }
+};
+
+template <>
+struct numeric_limits<short>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 15;
+    BOOST_MATH_STATIC constexpr int digits10 = 4;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -32768; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 32767; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -32768; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned short>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = false;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = true;
+    BOOST_MATH_STATIC constexpr int digits = 16;
+    BOOST_MATH_STATIC constexpr int digits10 = 4;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 65535; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<int>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 31;
+    BOOST_MATH_STATIC constexpr int digits10 = 9;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -2147483648; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 2147483647; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -2147483648; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned int>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = false;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = true;
+    BOOST_MATH_STATIC constexpr int digits = 32;
+    BOOST_MATH_STATIC constexpr int digits10 = 9;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 4294967295U; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 63;
+    BOOST_MATH_STATIC constexpr int digits10 = 18;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -9223372036854775808L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 9223372036854775807L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -9223372036854775808L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = false;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = true;
+    BOOST_MATH_STATIC constexpr int digits = 64;
+    BOOST_MATH_STATIC constexpr int digits10 = 19;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 18446744073709551615UL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<long long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = true;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 63;
+    BOOST_MATH_STATIC constexpr int digits10 = 18;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -9223372036854775808LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 9223372036854775807LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -9223372036854775808LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<unsigned long long>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = false;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = true;
+    BOOST_MATH_STATIC constexpr int digits = 64;
+    BOOST_MATH_STATIC constexpr int digits10 = 19;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = true;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 18446744073709551615UL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+};
+
+template <>
+struct numeric_limits<bool>
+{
+    BOOST_MATH_STATIC constexpr bool is_specialized = true;
+    BOOST_MATH_STATIC constexpr bool is_signed = false;
+    BOOST_MATH_STATIC constexpr bool is_integer = true;
+    BOOST_MATH_STATIC constexpr bool is_exact = true;
+    BOOST_MATH_STATIC constexpr bool has_infinity = false;
+    BOOST_MATH_STATIC constexpr bool has_quiet_NaN = false;
+    BOOST_MATH_STATIC constexpr bool has_signaling_NaN = false;
+
+    BOOST_MATH_STATIC constexpr bool is_iec559 = false;
+    BOOST_MATH_STATIC constexpr bool is_bounded = true;
+    BOOST_MATH_STATIC constexpr bool is_modulo = false;
+    BOOST_MATH_STATIC constexpr int digits = 1;
+    BOOST_MATH_STATIC constexpr int digits10 = 0;
+    BOOST_MATH_STATIC constexpr int max_digits10 = 0;
+    BOOST_MATH_STATIC constexpr int radix = 2;
+    BOOST_MATH_STATIC constexpr int min_exponent = 0;
+    BOOST_MATH_STATIC constexpr int min_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent = 0;
+    BOOST_MATH_STATIC constexpr int max_exponent10 = 0;
+    BOOST_MATH_STATIC constexpr bool traps = false;
+    BOOST_MATH_STATIC constexpr bool tinyness_before = false;
+
+    // Member Functions
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool (min)         () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool (max)         () { return true; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool lowest        () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool epsilon       () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool round_error   () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool infinity      () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool quiet_NaN     () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool signaling_NaN () { return false; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr bool denorm_min    () { return false; }
+};
+
 #endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 } // namespace math

From b9c645ef57ea210fd707e0f3083dd1eb7b0159a0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 14:44:32 -0400
Subject: [PATCH 262/399] Fix helper functions

---
 include/boost/math/tools/type_traits.hpp | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index 3b67efc034..a37e8e7ebb 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -404,14 +404,14 @@ BOOST_MATH_INLINE_CONSTEXPR bool is_signed_v = boost::math::is_signed<T>::value;
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_unsigned_v = boost::math::is_unsigned<T>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_constructible_v = boost::math::is_constructible<T>::value;
+template <typename T, typename... Args>
+BOOST_MATH_INLINE_CONSTEXPR bool is_constructible_v = boost::math::is_constructible<T, Args...>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_constructible_v = boost::math::is_trivially_constructible<T>::value;
+template <typename T, typename... Args>
+BOOST_MATH_INLINE_CONSTEXPR bool is_trivially_constructible_v = boost::math::is_trivially_constructible<T, Args...>::value;
 
-template <typename T>
-BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_constructible_v = boost::math::is_nothrow_constructible<T>::value;
+template <typename T, typename... Args>
+BOOST_MATH_INLINE_CONSTEXPR bool is_nothrow_constructible_v = boost::math::is_nothrow_constructible<T, Args...>::value;
 
 template <typename T>
 BOOST_MATH_INLINE_CONSTEXPR bool is_default_constructible_v = boost::math::is_default_constructible<T>::value;

From ae98552df8ccc6175d7aa21eb2f53079fdc3b7c1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 14:44:41 -0400
Subject: [PATCH 263/399] Ensure proper include order

---
 include/boost/math/tools/config.hpp | 14 +++++++++++++-
 1 file changed, 13 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index f8796c8334..565e801e63 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -669,6 +669,12 @@ namespace boost{ namespace math{
 //
 
 #ifdef __CUDACC__
+
+// We have to get our include order correct otherwise you get compilation failures
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <cuda/std/type_traits>
+
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
 
@@ -768,7 +774,13 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_FP_SUBNORMAL FP_SUBNORMAL
 #define BOOST_MATH_FP_NORMAL FP_NORMAL
 
-#else // Special section for CUDA NVRTC to ensure we consume no headers
+#else // Special section for CUDA NVRTC to ensure we consume no STL headers
+
+// Dependency on the order of includes
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <cuda/std/type_traits>
 
 #ifndef BOOST_MATH_STANDALONE
 #  define BOOST_MATH_STANDALONE

From 20050431690892c13dc284af71d5e5ae3b51f8eb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 14:45:06 -0400
Subject: [PATCH 264/399] Add NVRTC support to trunc

---
 .../boost/math/special_functions/trunc.hpp    | 120 +++++++++++++++++-
 1 file changed, 113 insertions(+), 7 deletions(-)

diff --git a/include/boost/math/special_functions/trunc.hpp b/include/boost/math/special_functions/trunc.hpp
index 4288225f16..564ff4891a 100644
--- a/include/boost/math/special_functions/trunc.hpp
+++ b/include/boost/math/special_functions/trunc.hpp
@@ -11,9 +11,14 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <type_traits>
 #include <boost/math/special_functions/math_fwd.hpp>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/ccmath/detail/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
@@ -57,6 +62,48 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T> trunc(const T& v)
 {
    return trunc(v, policies::policy<>());
 }
+
+#else // Special handling for nvrtc
+
+namespace boost {
+namespace math {
+
+namespace detail {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED double trunc_impl(T x)
+{
+   return static_cast<double>(x);
+}
+
+BOOST_MATH_GPU_ENABLED inline float trunc_impl(float x)
+{
+   return ::truncf(x);
+}
+
+BOOST_MATH_GPU_ENABLED inline double trunc_impl(double x)
+{
+   return ::trunc(x);
+}
+
+} // Namespace detail
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto trunc(T x, const Policy&)
+{
+   return detail::trunc_impl(x);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto trunc(T x)
+{
+   return detail::trunc_impl(x);
+}
+
+#endif
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 //
 // The following functions will not compile unless T has an
 // implicit conversion to the integer types.  For user-defined
@@ -214,15 +261,74 @@ BOOST_MATH_GPU_ENABLED inline long long lltrunc(const T& v)
    return lltrunc(v, policies::policy<>());
 }
 
+#else // Reduced impl specifically for NVRTC platform
+
+namespace detail {
+
+template <typename TargetType, typename T>
+BOOST_MATH_GPU_ENABLED TargetType integer_trunc_impl(T v)
+{
+   double r = boost::math::trunc(v, pol);
+
+   const double max_val = ldexp(1.0, boost::math::numeric_limits<TargetType>::digits);
+
+   if (r >= max_val || r < -max_val)
+   {
+      r = 0;
+   }
+
+   return static_cast<TargetType>(r);
+}
+
+} // Namespace detail
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED int itrunc(T v)
+{
+   return detail::integer_trunc_impl<int>(v);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED int itrunc(T v, const Policy&)
+{
+   return detail::integer_trunc_impl<int>(v);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED long ltrunc(T v)
+{
+   return detail::integer_trunc_impl<long>(v);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED long ltrunc(T v, const Policy&)
+{
+   return detail::integer_trunc_impl<long>(v);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED long long lltrunc(T v)
+{
+   return detail::integer_trunc_impl<long long>(v);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED long long lltrunc(T v, const Policy&)
+{
+   return detail::integer_trunc_impl<long long>(v);
+}
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<int, T>::value, int>::type
+BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<boost::math::is_constructible_v<int, T>, int>
    iconvert(const T& v, const Policy&)
 {
    return static_cast<int>(v);
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<int, T>::value, int>::type
+BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<!boost::math::is_constructible_v<int, T>, int>
    iconvert(const T& v, const Policy& pol)
 {
    using boost::math::itrunc;
@@ -230,14 +336,14 @@ BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<int
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<long, T>::value, long>::type
+BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<boost::math::is_constructible_v<long, T>, long>
    lconvert(const T& v, const Policy&)
 {
    return static_cast<long>(v);
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<long, T>::value, long>::type
+BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<!boost::math::is_constructible_v<long, T>, long>
    lconvert(const T& v, const Policy& pol)
 {
    using boost::math::ltrunc;
@@ -245,14 +351,14 @@ BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<lon
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<std::is_constructible<long long, T>::value, long long>::type
+BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<boost::math::is_constructible_v<long long, T>, long long>
    llconvertert(const T& v, const Policy&)
 {
    return static_cast<long long>(v);
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline typename std::enable_if<!std::is_constructible<long long, T>::value, long long>::type
+BOOST_MATH_GPU_ENABLED inline typename boost::math::enable_if_t<!boost::math::is_constructible_v<long long, T>, long long>
    llconvertert(const T& v, const Policy& pol)
 {
    using boost::math::lltrunc;

From cb23c0756f194187a8398b346506599d2bc79f27 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 15:35:19 -0400
Subject: [PATCH 265/399] Deprecate misspelled overloads

---
 include/boost/math/special_functions/trunc.hpp | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/trunc.hpp b/include/boost/math/special_functions/trunc.hpp
index 564ff4891a..6394909e1e 100644
--- a/include/boost/math/special_functions/trunc.hpp
+++ b/include/boost/math/special_functions/trunc.hpp
@@ -352,13 +352,28 @@ BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<!boost::math::is_construc
 
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline boost::math::enable_if_t<boost::math::is_constructible_v<long long, T>, long long>
-   llconvertert(const T& v, const Policy&)
+   llconvert(const T& v, const Policy&)
 {
    return static_cast<long long>(v);
 }
 
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline typename boost::math::enable_if_t<!boost::math::is_constructible_v<long long, T>, long long>
+   llconvert(const T& v, const Policy& pol)
+{
+   using boost::math::lltrunc;
+   return lltrunc(v, pol);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED [[deprecated("Use llconvert")]] inline boost::math::enable_if_t<boost::math::is_constructible_v<long long, T>, long long>
+   llconvertert(const T& v, const Policy&)
+{
+   return static_cast<long long>(v);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED [[deprecated("Use llconvert")]] inline typename boost::math::enable_if_t<!boost::math::is_constructible_v<long long, T>, long long>
    llconvertert(const T& v, const Policy& pol)
 {
    using boost::math::lltrunc;

From 975273af2859cc2da1a8d7b4b7d0a71e113cc510 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 15:35:31 -0400
Subject: [PATCH 266/399] Fix NVRTC paths

---
 include/boost/math/tools/numeric_limits.hpp | 128 ++++++++++----------
 1 file changed, 65 insertions(+), 63 deletions(-)

diff --git a/include/boost/math/tools/numeric_limits.hpp b/include/boost/math/tools/numeric_limits.hpp
index 8db05b065a..87a7802363 100644
--- a/include/boost/math/tools/numeric_limits.hpp
+++ b/include/boost/math/tools/numeric_limits.hpp
@@ -33,6 +33,8 @@ template <typename T>
 struct numeric_limits 
 #ifndef BOOST_MATH_HAS_NVRTC
 : public std::numeric_limits<T> {};
+#else
+{};
 #endif
 
 #if defined(BOOST_MATH_HAS_GPU_SUPPORT) && !defined(BOOST_MATH_HAS_NVRTC)
@@ -608,15 +610,15 @@ struct numeric_limits<unsigned short>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 65535; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short (max)         () { return 65535U; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned short denorm_min    () { return 0; }
 };
 
 template <>
@@ -645,15 +647,15 @@ struct numeric_limits<int>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -2147483648; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 2147483647; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -2147483648; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int (min)         () { return -2147483648; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int (max)         () { return 2147483647; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int lowest        () { return -2147483648; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr int denorm_min    () { return 0; }
 };
 
 template <>
@@ -682,15 +684,15 @@ struct numeric_limits<unsigned int>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 4294967295U; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int (max)         () { return 4294967295U; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned int denorm_min    () { return 0; }
 };
 
 template <>
@@ -719,15 +721,15 @@ struct numeric_limits<long>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -9223372036854775808L; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 9223372036854775807L; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -9223372036854775808L; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long (min)         () { return -9223372036854775808L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long (max)         () { return 9223372036854775807L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long lowest        () { return -9223372036854775808L; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long denorm_min    () { return 0; }
 };
 
 template <>
@@ -756,15 +758,15 @@ struct numeric_limits<unsigned long>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 18446744073709551615UL; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long (max)         () { return 18446744073709551615UL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long denorm_min    () { return 0; }
 };
 
 template <>
@@ -793,15 +795,15 @@ struct numeric_limits<long long>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return -9223372036854775808LL; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 9223372036854775807LL; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return -9223372036854775808LL; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long (min)         () { return -9223372036854775808LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long (max)         () { return 9223372036854775807LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long lowest        () { return -9223372036854775808LL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr long long denorm_min    () { return 0; }
 };
 
 template <>
@@ -830,15 +832,15 @@ struct numeric_limits<unsigned long long>
     BOOST_MATH_STATIC constexpr bool tinyness_before = false;
 
     // Member Functions
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (min)         () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short (max)         () { return 18446744073709551615UL; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short lowest        () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short epsilon       () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short round_error   () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short infinity      () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short quiet_NaN     () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short signaling_NaN () { return 0; }
-    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr short denorm_min    () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long (min)         () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long (max)         () { return 18446744073709551615UL; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long lowest        () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long epsilon       () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long round_error   () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long infinity      () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long quiet_NaN     () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long signaling_NaN () { return 0; }
+    BOOST_MATH_GPU_ENABLED BOOST_MATH_STATIC constexpr unsigned long long denorm_min    () { return 0; }
 };
 
 template <>

From 08f9685d450981fca5121823133cc3447ee4aae3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 15:35:48 -0400
Subject: [PATCH 267/399] Add definition of BOOST_MATH_STATIC

---
 include/boost/math/tools/config.hpp | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 565e801e63..fb785c376c 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -776,12 +776,6 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 
 #else // Special section for CUDA NVRTC to ensure we consume no STL headers
 
-// Dependency on the order of includes
-#include <nvrtc.h>
-#include <cuda.h>
-#include <cuda_runtime.h>
-#include <cuda/std/type_traits>
-
 #ifndef BOOST_MATH_STANDALONE
 #  define BOOST_MATH_STANDALONE
 #endif
@@ -792,6 +786,8 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 
 #define BOOST_MATH_GPU_ENABLED __host__ __device__
 
+#define BOOST_MATH_STATIC static
+
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
 

From a8ae64db8a8b807c26a4aa2452a2a1d914a9dd75 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 15:37:20 -0400
Subject: [PATCH 268/399] Fix copy paste error

---
 include/boost/math/special_functions/trunc.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/trunc.hpp b/include/boost/math/special_functions/trunc.hpp
index 6394909e1e..b52f4f321c 100644
--- a/include/boost/math/special_functions/trunc.hpp
+++ b/include/boost/math/special_functions/trunc.hpp
@@ -268,7 +268,7 @@ namespace detail {
 template <typename TargetType, typename T>
 BOOST_MATH_GPU_ENABLED TargetType integer_trunc_impl(T v)
 {
-   double r = boost::math::trunc(v, pol);
+   double r = boost::math::trunc(v);
 
    const double max_val = ldexp(1.0, boost::math::numeric_limits<TargetType>::digits);
 

From 2877f2bc8b4fadbdafa2daa3fbf136c0d8f995b7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 15:38:16 -0400
Subject: [PATCH 269/399] Add trunc NVRTC testing

---
 test/nvrtc_jamfile               |   1 +
 test/test_trunc_nvrtc_double.cpp | 196 +++++++++++++++++++++++++++++++
 test/test_trunc_nvrtc_float.cpp  | 196 +++++++++++++++++++++++++++++++
 3 files changed, 393 insertions(+)
 create mode 100644 test/test_trunc_nvrtc_double.cpp
 create mode 100644 test/test_trunc_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 6d6327ddb2..d62419e0a7 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -20,3 +20,4 @@ run test_round_nvrtc_double.cpp ;
 run test_round_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
+run test_trunc_nvrtc_double.cpp ;
diff --git a/test/test_trunc_nvrtc_double.cpp b/test/test_trunc_nvrtc_double.cpp
new file mode 100644
index 0000000000..1aab64887b
--- /dev/null
+++ b/test/test_trunc_nvrtc_double.cpp
@@ -0,0 +1,196 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/trunc.hpp>
+extern "C" __global__ 
+void test_trunc_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::trunc(in1[i]) + 
+                 boost::math::itrunc(in1[i]) +
+                 boost::math::ltrunc(in1[i]) + 
+                 boost::math::lltrunc(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_trunc_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_trunc_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_trunc_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::trunc(h_in1[i]) + 
+                             boost::math::itrunc(h_in1[i]) +
+                             boost::math::ltrunc(h_in1[i]) + 
+                             boost::math::lltrunc(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_trunc_nvrtc_float.cpp b/test/test_trunc_nvrtc_float.cpp
new file mode 100644
index 0000000000..13ad4bc51b
--- /dev/null
+++ b/test/test_trunc_nvrtc_float.cpp
@@ -0,0 +1,196 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/trunc.hpp>
+extern "C" __global__ 
+void test_trunc_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::trunc(in1[i]) + 
+                 boost::math::itrunc(in1[i]) +
+                 boost::math::ltrunc(in1[i]) + 
+                 boost::math::lltrunc(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_trunc_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_trunc_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_trunc_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::trunc(h_in1[i]) + 
+                             boost::math::itrunc(h_in1[i]) +
+                             boost::math::ltrunc(h_in1[i]) + 
+                             boost::math::lltrunc(h_in1[i]);
+                       
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 39d9fa30e8f798e6d5c8f3fde15e6b0f52bb9764 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 16:45:40 -0400
Subject: [PATCH 270/399] Add NVRTC support to expm1

---
 .../boost/math/special_functions/expm1.hpp    | 27 ++++++++++++++++++-
 1 file changed, 26 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/expm1.hpp b/include/boost/math/special_functions/expm1.hpp
index a5af573cd2..b1acf7aa0c 100644
--- a/include/boost/math/special_functions/expm1.hpp
+++ b/include/boost/math/special_functions/expm1.hpp
@@ -11,10 +11,13 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <cstdint>
 #include <limits>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -314,6 +317,28 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type expm1(T x)
 } // namespace math
 } // namespace boost
 
+#else // Special handling for NVRTC 
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto expm1(T x)
+{
+   return ::expm1(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto expm1(float x)
+{
+   return ::expm1f(x);
+}
+
+} // Namespace math
+} // Namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif // BOOST_MATH_HYPOT_INCLUDED
 
 

From 6c91a22d7bbefe23c560e46ff6df6b53c7ec9309 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 16:45:52 -0400
Subject: [PATCH 271/399] Add NVRTC expm1 testing

---
 test/nvrtc_jamfile               |   2 +
 test/test_expm1_nvrtc_double.cpp | 186 +++++++++++++++++++++++++++++++
 test/test_expm1_nvrtc_float.cpp  | 186 +++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_expm1_nvrtc_double.cpp
 create mode 100644 test/test_expm1_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index d62419e0a7..5f6cf69d43 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -12,6 +12,8 @@ project : requirements
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
+run test_expm1_nvrtc_double.cpp ;
+run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
 run test_fpclassify_nvrtc_float.cpp ;
 run test_gamma_nvrtc_double.cpp ;
diff --git a/test/test_expm1_nvrtc_double.cpp b/test/test_expm1_nvrtc_double.cpp
new file mode 100644
index 0000000000..ea496b73a7
--- /dev/null
+++ b/test/test_expm1_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/expm1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/expm1.hpp>
+extern "C" __global__ 
+void test_expm1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::expm1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expm1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expm1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expm1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::expm1(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_expm1_nvrtc_float.cpp b/test/test_expm1_nvrtc_float.cpp
new file mode 100644
index 0000000000..16d8636db5
--- /dev/null
+++ b/test/test_expm1_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/expm1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/expm1.hpp>
+extern "C" __global__ 
+void test_expm1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::expm1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expm1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expm1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expm1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::expm1(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From b441ff372951420f678eee55a1ee2a0533f975fb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 16:48:46 -0400
Subject: [PATCH 272/399] Add policy enabled overloads

---
 include/boost/math/special_functions/expm1.hpp | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/include/boost/math/special_functions/expm1.hpp b/include/boost/math/special_functions/expm1.hpp
index b1acf7aa0c..b59721e932 100644
--- a/include/boost/math/special_functions/expm1.hpp
+++ b/include/boost/math/special_functions/expm1.hpp
@@ -334,6 +334,18 @@ BOOST_MATH_GPU_ENABLED auto expm1(float x)
    return ::expm1f(x);
 }
 
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto expm1(T x, const Policy&)
+{
+   return ::expm1(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto expm1(float x, const Policy&)
+{
+   return ::expm1f(x);
+}
+
 } // Namespace math
 } // Namespace boost
 

From 86757846af02a56e8c26167083c1e5f997ab1619 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 16:54:14 -0400
Subject: [PATCH 273/399] Add NVRTC support to log1p

---
 .../boost/math/special_functions/log1p.hpp    | 39 ++++++++++++++++++-
 1 file changed, 38 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/log1p.hpp b/include/boost/math/special_functions/log1p.hpp
index 1df3dd8fea..cdec8ee86c 100644
--- a/include/boost/math/special_functions/log1p.hpp
+++ b/include/boost/math/special_functions/log1p.hpp
@@ -12,10 +12,13 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <cstdint>
 #include <limits>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -473,6 +476,40 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1pmx(T x)
 } // namespace math
 } // namespace boost
 
+#else // Special handling for NVRTC platform
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto log1p(T x)
+{
+   return ::log1p(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto log1p(float x)
+{
+   return ::log1pf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto log1p(T x, const Policy&)
+{
+   return ::log1p(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto log1p(float x, const Policy&)
+{
+   return ::log1pf(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #ifdef _MSC_VER
 #pragma warning(pop)
 #endif

From d7197803c8a18b437424b624fc4eb10af735d92c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 16:54:24 -0400
Subject: [PATCH 274/399] Add NVRTC log1p testing

---
 test/nvrtc_jamfile               |   2 +
 test/test_log1p_nvrtc_double.cpp | 186 +++++++++++++++++++++++++++++++
 test/test_log1p_nvrtc_float.cpp  | 186 +++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_log1p_nvrtc_double.cpp
 create mode 100644 test/test_log1p_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 5f6cf69d43..703bf8099a 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -18,6 +18,8 @@ run test_fpclassify_nvrtc_double.cpp ;
 run test_fpclassify_nvrtc_float.cpp ;
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
+run test_log1p_nvrtc_double.cpp ;
+run test_log1p_nvrtc_float.cpp ;
 run test_round_nvrtc_double.cpp ;
 run test_round_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
diff --git a/test/test_log1p_nvrtc_double.cpp b/test/test_log1p_nvrtc_double.cpp
new file mode 100644
index 0000000000..722194be6a
--- /dev/null
+++ b/test/test_log1p_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/log1p.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/log1p.hpp>
+extern "C" __global__ 
+void test_log1p_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::log1p(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_log1p_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_log1p_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_log1p_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::log1p(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_log1p_nvrtc_float.cpp b/test/test_log1p_nvrtc_float.cpp
new file mode 100644
index 0000000000..772c50cd10
--- /dev/null
+++ b/test/test_log1p_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/log1p.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/log1p.hpp>
+extern "C" __global__ 
+void test_log1p_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::log1p(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_log1p_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_log1p_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_log1p_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::log1p(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 2cbb993992810f70a59eb42d73b0afbeaa8fbee4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 17:02:51 -0400
Subject: [PATCH 275/399] Add macro for missing std::size_t

---
 include/boost/math/tools/config.hpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index fb785c376c..8cc471e9bb 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -774,6 +774,9 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_FP_SUBNORMAL FP_SUBNORMAL
 #define BOOST_MATH_FP_NORMAL FP_NORMAL
 
+// Missing type from NVRTC
+#define BOOST_MATH_SIZE_T std::size_t
+
 #else // Special section for CUDA NVRTC to ensure we consume no STL headers
 
 #ifndef BOOST_MATH_STANDALONE
@@ -800,6 +803,7 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_FP_ZERO 2
 #define BOOST_MATH_FP_SUBNORMAL 3
 #define BOOST_MATH_FP_NORMAL 4
+#define BOOST_MATH_SIZE_T unsigned long
 
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr

From 80edbb1913abfd7de63546eaa55c3f4179778bf0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 17:03:21 -0400
Subject: [PATCH 276/399] Enable use of meta programming facilities with NVRTC

---
 include/boost/math/tools/mp.hpp | 43 ++++++++++-----------------------
 1 file changed, 13 insertions(+), 30 deletions(-)

diff --git a/include/boost/math/tools/mp.hpp b/include/boost/math/tools/mp.hpp
index 55aac1b092..66fcbdbaf1 100644
--- a/include/boost/math/tools/mp.hpp
+++ b/include/boost/math/tools/mp.hpp
@@ -11,9 +11,8 @@
 #ifndef BOOST_MATH_TOOLS_MP
 #define BOOST_MATH_TOOLS_MP
 
-#include <type_traits>
-#include <cstddef>
-#include <utility>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost { namespace math { namespace tools { namespace meta_programming {
 
@@ -23,12 +22,12 @@ template<typename... T>
 struct mp_list {};
 
 // Size_t
-template<std::size_t N> 
-using mp_size_t = std::integral_constant<std::size_t, N>;
+template<BOOST_MATH_SIZE_T N> 
+using mp_size_t = boost::math::integral_constant<BOOST_MATH_SIZE_T, N>;
 
 // Boolean
 template<bool B>
-using mp_bool = std::integral_constant<bool, B>;
+using mp_bool = boost::math::integral_constant<bool, B>;
 
 // Identity
 template<typename T>
@@ -53,7 +52,7 @@ struct mp_size_impl {};
 template<template<typename...> class L, typename... T> // Template template parameter must use class
 struct mp_size_impl<L<T...>>
 {
-    using type = std::integral_constant<std::size_t, sizeof...(T)>;
+    using type = boost::math::integral_constant<BOOST_MATH_SIZE_T, sizeof...(T)>;
 };
 }
 
@@ -79,7 +78,7 @@ namespace detail {
 // At
 // TODO - Use tree based lookup for larger typelists
 // http://odinthenerd.blogspot.com/2017/04/tree-based-lookup-why-kvasirmpl-is.html
-template<typename L, std::size_t>
+template<typename L, BOOST_MATH_SIZE_T>
 struct mp_at_c {};
 
 template<template<typename...> class L, typename T0, typename... T>
@@ -168,7 +167,7 @@ struct mp_at_c<L<T0, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T...>, 1
 };
 }
 
-template<typename L, std::size_t Index>
+template<typename L, BOOST_MATH_SIZE_T Index>
 using mp_at_c = typename detail::mp_at_c<L, Index>::type;
 
 template<typename L, typename Index>
@@ -336,25 +335,11 @@ using mp_remove_if = typename detail::mp_remove_if_impl<L, P>::type;
 template<typename L, typename Q> 
 using mp_remove_if_q = mp_remove_if<L, Q::template fn>;
 
-// Index sequence
-// Use C++14 index sequence if available
-#if defined(__cpp_lib_integer_sequence) && (__cpp_lib_integer_sequence >= 201304)
-template<std::size_t... Index>
-using index_sequence = std::index_sequence<Index...>;
-
-template<std::size_t N>
-using make_index_sequence = std::make_index_sequence<N>;
-
-template<typename... T>
-using index_sequence_for = std::index_sequence_for<T...>;
-
-#else
-
 template<typename T, T... Index>
 struct integer_sequence {};
 
-template<std::size_t... Index>
-using index_sequence = integer_sequence<std::size_t, Index...>;
+template<BOOST_MATH_SIZE_T... Index>
+using index_sequence = integer_sequence<BOOST_MATH_SIZE_T, Index...>;
 
 namespace detail {
 
@@ -426,13 +411,11 @@ struct make_integer_sequence_impl
 template<typename T, T N>
 using make_integer_sequence = typename detail::make_integer_sequence_impl<T, N>::type;
 
-template<std::size_t N>
-using make_index_sequence = make_integer_sequence<std::size_t, N>;
+template<BOOST_MATH_SIZE_T N>
+using make_index_sequence = make_integer_sequence<BOOST_MATH_SIZE_T, N>;
 
 template<typename... T>
-using index_sequence_for = make_integer_sequence<std::size_t, sizeof...(T)>;
-
-#endif 
+using index_sequence_for = make_integer_sequence<BOOST_MATH_SIZE_T, sizeof...(T)>;
 
 }}}} // namespaces
 

From d5b8603c8d5e4e1e93057f5d162f324fbd888ba1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 17:06:43 -0400
Subject: [PATCH 277/399] Fix ambiguous use of is_same

---
 test/pow_test.cpp | 17 ++++++++---------
 1 file changed, 8 insertions(+), 9 deletions(-)

diff --git a/test/pow_test.cpp b/test/pow_test.cpp
index 9180ccab52..24a1cd7f79 100644
--- a/test/pow_test.cpp
+++ b/test/pow_test.cpp
@@ -18,7 +18,6 @@
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/typeof/typeof.hpp>
-#include <boost/type_traits/is_same.hpp>
 #include <boost/math/tools/assert.hpp>
 
 #include <boost/math/special_functions/pow.hpp>
@@ -103,15 +102,15 @@ void test_with_big_exponents()
 
 void test_return_types()
 {
-    static_assert((is_same<BOOST_TYPEOF(pow<2>('\1')), double>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(L'\2')), double>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(3)), double>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(4u)), double>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(5ul)), double>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(6.0f)), float>::value), "Return type mismatch");
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(7.0)), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>('\1')), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(L'\2')), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(3)), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(4u)), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(5ul)), double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(6.0f)), float>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(7.0)), double>::value), "Return type mismatch");
 #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
-    static_assert((is_same<BOOST_TYPEOF(pow<2>(7.0l)), long double>::value), "Return type mismatch");
+    static_assert((boost::math::is_same<BOOST_TYPEOF(pow<2>(7.0l)), long double>::value), "Return type mismatch");
 #endif
 }
 

From b19fd5ac920a0064c2c1db1e8100ecdbb9c42c37 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 17:38:52 -0400
Subject: [PATCH 278/399] Add macro definition of std::uintmax_t

---
 include/boost/math/tools/config.hpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 8cc471e9bb..eeee116711 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -775,7 +775,9 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_FP_NORMAL FP_NORMAL
 
 // Missing type from NVRTC
+#include <cstdint>
 #define BOOST_MATH_SIZE_T std::size_t
+#define BOOST_MATH_UINTMAX_T std::uintmax_t
 
 #else // Special section for CUDA NVRTC to ensure we consume no STL headers
 
@@ -803,7 +805,9 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_FP_ZERO 2
 #define BOOST_MATH_FP_SUBNORMAL 3
 #define BOOST_MATH_FP_NORMAL 4
+
 #define BOOST_MATH_SIZE_T unsigned long
+#define BOOST_MATH_UINTMAX_T unsigned long
 
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr

From b67454533368d9de01a2c202db06c193a7dc321f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 17:39:23 -0400
Subject: [PATCH 279/399] Make policies universally safe on GPU platforms

---
 include/boost/math/policies/policy.hpp | 119 ++++++++++++-------------
 1 file changed, 58 insertions(+), 61 deletions(-)

diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index f12837a2a6..a17dfe6dbf 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -9,11 +9,8 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/mp.hpp>
-#include <limits>
-#include <type_traits>
-#include <cmath>
-#include <cstdint>
-#include <cstddef>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost{ namespace math{
 
@@ -24,7 +21,7 @@ namespace tools{
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept;
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value);
+BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value);
 
 }
 
@@ -134,7 +131,7 @@ namespace policies{
 
 #define BOOST_MATH_META_INT(Type, name, Default)                                                \
    template <Type N = Default>                                                                  \
-   class name : public std::integral_constant<int, N>{};                                        \
+   class name : public boost::math::integral_constant<int, N>{};                                \
                                                                                                 \
    namespace detail{                                                                            \
    template <Type N>                                                                            \
@@ -158,12 +155,12 @@ namespace policies{
    {                                                                                            \
    public:                                                                                      \
       static constexpr bool value = boost::math::policies::detail::is_##name##_imp<T>::value;   \
-      using type = std::integral_constant<bool, value>;                                         \
+      using type = boost::math::integral_constant<bool, value>;                                 \
    };
 
 #define BOOST_MATH_META_BOOL(name, Default)                                                     \
    template <bool N = Default>                                                                  \
-   class name : public std::integral_constant<bool, N>{};                                       \
+   class name : public boost::math::integral_constant<bool, N>{};                               \
                                                                                                 \
    namespace detail{                                                                            \
    template <bool N>                                                                            \
@@ -178,7 +175,7 @@ namespace policies{
       static char test(const name<N>* = nullptr);                                               \
       static double test(...);                                                                  \
    public:                                                                                      \
-      static constexpr bool value = sizeof(test(static_cast<T*>(nullptr))) == sizeof(char);           \
+      static constexpr bool value = sizeof(test(static_cast<T*>(nullptr))) == sizeof(char);     \
    };                                                                                           \
    }                                                                                            \
                                                                                                 \
@@ -187,7 +184,7 @@ namespace policies{
    {                                                                                            \
    public:                                                                                      \
       static constexpr bool value = boost::math::policies::detail::is_##name##_imp<T>::value;   \
-      using type = std::integral_constant<bool, value>;                                         \
+      using type = boost::math::integral_constant<bool, value>;                                 \
    };
 
 //
@@ -259,18 +256,18 @@ struct precision
    //
    // Now work out the precision:
    //
-   using digits2_type = typename std::conditional<
+   using digits2_type = typename boost::math::conditional<
       (Digits10::value == 0),
       digits2<0>,
       digits2<((Digits10::value + 1) * 1000L) / 301L>
    >::type;
 public:
 #ifdef BOOST_BORLANDC
-   using type = typename std::conditional<
+   using type = typename boost::math::conditional<
       (Digits2::value > ::boost::math::policies::detail::precision<Digits10,Digits2>::digits2_type::value),
       Digits2, digits2_type>::type;
 #else
-   using type = typename std::conditional<
+   using type = typename boost::math::conditional<
       (Digits2::value > digits2_type::value),
       Digits2, digits2_type>::type;
 #endif
@@ -307,7 +304,7 @@ class is_default_policy
 {
 public:
    static constexpr bool value = boost::math::policies::detail::is_default_policy_imp<T>::value;
-   using type = std::integral_constant<bool, value>;
+   using type = boost::math::integral_constant<bool, value>;
 
    template <typename U>
    struct apply
@@ -316,7 +313,7 @@ class is_default_policy
    };
 };
 
-template <class Seq, class T, std::size_t N>
+template <class Seq, class T, BOOST_MATH_SIZE_T N>
 struct append_N
 {
    using type = typename append_N<mp::mp_push_back<Seq, T>, T, N-1>::type;
@@ -405,7 +402,7 @@ class policy
    // Typelist of the arguments:
    //
    using arg_list = mp::mp_list<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11,A12,A13>;
-   static constexpr std::size_t arg_list_size = mp::mp_size<arg_list>::value;
+   static constexpr BOOST_MATH_SIZE_T arg_list_size = mp::mp_size<arg_list>::value;
 
    template<typename A, typename B, bool b>
    struct pick_arg
@@ -536,7 +533,7 @@ class normalise
 {
 private:
    using arg_list = mp::mp_list<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11,A12,A13>;
-   static constexpr std::size_t arg_list_size = mp::mp_size<arg_list>::value;
+   static constexpr BOOST_MATH_SIZE_T arg_list_size = mp::mp_size<arg_list>::value;
 
    template<typename A, typename B, bool b>
    struct pick_arg
@@ -759,47 +756,47 @@ struct evaluation
 template <class Policy>
 struct evaluation<float, Policy>
 {
-   using type = typename std::conditional<Policy::promote_float_type::value, double, float>::type;
+   using type = typename boost::math::conditional<Policy::promote_float_type::value, double, float>::type;
 };
 
 template <class Policy>
 struct evaluation<double, Policy>
 {
-   using type = typename std::conditional<Policy::promote_double_type::value, long double, double>::type;
+   using type = typename boost::math::conditional<Policy::promote_double_type::value, long double, double>::type;
 };
 
 template <class Real, class Policy>
 struct precision
 {
-   static_assert((std::numeric_limits<Real>::radix == 2) || ((std::numeric_limits<Real>::is_specialized == 0) || (std::numeric_limits<Real>::digits == 0)),
-   "(std::numeric_limits<Real>::radix == 2) || ((std::numeric_limits<Real>::is_specialized == 0) || (std::numeric_limits<Real>::digits == 0))");
+   static_assert((boost::math::numeric_limits<Real>::radix == 2) || ((boost::math::numeric_limits<Real>::is_specialized == 0) || (boost::math::numeric_limits<Real>::digits == 0)),
+   "(boost::math::numeric_limits<Real>::radix == 2) || ((boost::math::numeric_limits<Real>::is_specialized == 0) || (boost::math::numeric_limits<Real>::digits == 0))");
 #ifndef BOOST_BORLANDC
    using precision_type = typename Policy::precision_type;
-   using type = typename std::conditional<
-      ((std::numeric_limits<Real>::is_specialized == 0) || (std::numeric_limits<Real>::digits == 0)),
+   using type = typename boost::math::conditional<
+      ((boost::math::numeric_limits<Real>::is_specialized == 0) || (boost::math::numeric_limits<Real>::digits == 0)),
       // Possibly unknown precision:
       precision_type,
-      typename std::conditional<
-         ((std::numeric_limits<Real>::digits <= precision_type::value)
+      typename boost::math::conditional<
+         ((boost::math::numeric_limits<Real>::digits <= precision_type::value)
          || (Policy::precision_type::value <= 0)),
          // Default case, full precision for RealType:
-         digits2< std::numeric_limits<Real>::digits>,
+         digits2< boost::math::numeric_limits<Real>::digits>,
          // User customised precision:
          precision_type
       >::type
    >::type;
 #else
    using precision_type = typename Policy::precision_type;
-   using digits_t = std::integral_constant<int, std::numeric_limits<Real>::digits>;
-   using spec_t = std::integral_constant<bool, std::numeric_limits<Real>::is_specialized>;
-   using type = typename std::conditional<
-      (spec_t::value == true std::true_type || digits_t::value == 0),
+   using digits_t = boost::math::integral_constant<int, boost::math::numeric_limits<Real>::digits>;
+   using spec_t = boost::math::integral_constant<bool, boost::math::numeric_limits<Real>::is_specialized>;
+   using type = typename boost::math::conditional<
+      (spec_t::value == true boost::math::true_type || digits_t::value == 0),
       // Possibly unknown precision:
       precision_type,
-      typename std::conditional<
+      typename boost::math::conditional<
          (digits_t::value <= precision_type::value || precision_type::value <= 0),
          // Default case, full precision for RealType:
-         digits2< std::numeric_limits<Real>::digits>,
+         digits2< boost::math::numeric_limits<Real>::digits>,
          // User customised precision:
          precision_type
       >::type
@@ -812,7 +809,7 @@ struct precision
 template <class Policy>
 struct precision<BOOST_MATH_FLOAT128_TYPE, Policy>
 {
-   typedef std::integral_constant<int, 113> type;
+   typedef boost::math::integral_constant<int, 113> type;
 };
 
 #endif
@@ -820,15 +817,15 @@ struct precision<BOOST_MATH_FLOAT128_TYPE, Policy>
 namespace detail{
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED constexpr int digits_imp(std::true_type const&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits_imp(boost::math::true_type const&) noexcept
 {
-   static_assert( std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
+   static_assert( boost::math::numeric_limits<T>::is_specialized, "boost::math::numeric_limits<T>::is_specialized");
    typedef typename boost::math::policies::precision<T, Policy>::type p_t;
    return p_t::value;
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED constexpr int digits_imp(std::false_type const&) noexcept
+BOOST_MATH_GPU_ENABLED constexpr int digits_imp(boost::math::false_type const&) noexcept
 {
    return tools::digits<T>();
 }
@@ -838,7 +835,7 @@ BOOST_MATH_GPU_ENABLED constexpr int digits_imp(std::false_type const&) noexcept
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept
 {
-   typedef std::integral_constant<bool, std::numeric_limits<T>::is_specialized > tag_type;
+   typedef boost::math::integral_constant<bool, boost::math::numeric_limits<T>::is_specialized > tag_type;
    return detail::digits_imp<T, Policy>(tag_type());
 }
 template <class T, class Policy>
@@ -866,51 +863,51 @@ namespace detail{
 template <class T, class Digits, class Small, class Default>
 struct series_factor_calc
 {
-   BOOST_MATH_GPU_ENABLED static T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static T get() noexcept(boost::math::is_floating_point<T>::value)
    {
       return ldexp(T(1.0), 1 - Digits::value);
    }
 };
 
 template <class T, class Digits>
-struct series_factor_calc<T, Digits, std::true_type, std::true_type>
+struct series_factor_calc<T, Digits, boost::math::true_type, boost::math::true_type>
 {
-   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(boost::math::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
 };
 template <class T, class Digits>
-struct series_factor_calc<T, Digits, std::true_type, std::false_type>
+struct series_factor_calc<T, Digits, boost::math::true_type, boost::math::false_type>
 {
-   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(boost::math::is_floating_point<T>::value)
    {
-      return 1 / static_cast<T>(static_cast<std::uintmax_t>(1u) << (Digits::value - 1));
+      return 1 / static_cast<T>(static_cast<BOOST_MATH_UINTMAX_T>(1u) << (Digits::value - 1));
    }
 };
 template <class T, class Digits>
-struct series_factor_calc<T, Digits, std::false_type, std::true_type>
+struct series_factor_calc<T, Digits, boost::math::false_type, boost::math::true_type>
 {
-   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(std::is_floating_point<T>::value)
+   BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(boost::math::is_floating_point<T>::value)
    {
       return boost::math::tools::epsilon<T>();
    }
 };
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(std::true_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(boost::math::true_type const&) noexcept(boost::math::is_floating_point<T>::value)
 {
-   static_assert(std::numeric_limits<T>::is_specialized, "std::numeric_limits<T>::is_specialized");
-   static_assert(std::numeric_limits<T>::radix == 2, "std::numeric_limits<T>::radix == 2");
+   static_assert(boost::math::numeric_limits<T>::is_specialized, "boost::math::numeric_limits<T>::is_specialized");
+   static_assert(boost::math::numeric_limits<T>::radix == 2, "boost::math::numeric_limits<T>::radix == 2");
 
    typedef typename boost::math::policies::precision<T, Policy>::type p_t;
-   typedef std::integral_constant<bool, p_t::value <= std::numeric_limits<std::uintmax_t>::digits> is_small_int;
-   typedef std::integral_constant<bool, p_t::value >= std::numeric_limits<T>::digits> is_default_value;
+   typedef boost::math::integral_constant<bool, p_t::value <= boost::math::numeric_limits<BOOST_MATH_UINTMAX_T>::digits> is_small_int;
+   typedef boost::math::integral_constant<bool, p_t::value >= boost::math::numeric_limits<T>::digits> is_default_value;
    return series_factor_calc<T, p_t, is_small_int, is_default_value>::get();
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(std::false_type const&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(boost::math::false_type const&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return tools::epsilon<T>();
 }
@@ -918,9 +915,9 @@ BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(std::false_type const&) noexc
 } // namespace detail
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T get_epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
-   typedef std::integral_constant<bool, (std::numeric_limits<T>::is_specialized && (std::numeric_limits<T>::radix == 2)) > tag_type;
+   typedef boost::math::integral_constant<bool, (boost::math::numeric_limits<T>::is_specialized && (boost::math::numeric_limits<T>::radix == 2)) > tag_type;
    return detail::get_epsilon_imp<T, Policy>(tag_type());
 }
 
@@ -954,7 +951,7 @@ class is_policy
 {
 public:
    static constexpr bool value = boost::math::policies::detail::is_policy_imp<P>::value;
-   using type = std::integral_constant<bool, value>;
+   using type = boost::math::integral_constant<bool, value>;
 };
 
 //
@@ -964,20 +961,20 @@ template <class Policy>
 struct constructor_error_check
 {
    using domain_error_type = typename Policy::domain_error_type;
-   using type = typename std::conditional<
+   using type = typename boost::math::conditional<
       (domain_error_type::value == throw_on_error) || (domain_error_type::value == user_error) || (domain_error_type::value == errno_on_error),
-      std::true_type,
-      std::false_type>::type;
+      boost::math::true_type,
+      boost::math::false_type>::type;
 };
 
 template <class Policy>
 struct method_error_check
 {
    using domain_error_type = typename Policy::domain_error_type;
-   using type = typename std::conditional<
+   using type = typename boost::math::conditional<
       (domain_error_type::value == throw_on_error),
-      std::false_type,
-      std::true_type>::type;
+      boost::math::false_type,
+      boost::math::true_type>::type;
 };
 //
 // Does the Policy ever throw on error?

From 79f96fc6ee0313e5bcf9e4f00279c935cd7df28e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 18:01:56 -0400
Subject: [PATCH 280/399] Fix exception specification mismatch

---
 include/boost/math/tools/precision.hpp | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 877d231f1d..eb49ca9178 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -12,6 +12,8 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/policies/policy.hpp>
 #include <type_traits>
 #include <limits>
@@ -279,7 +281,7 @@ BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMP
 #endif
 
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::epsilon<T>(std::integral_constant<bool, ::std::numeric_limits<T>::is_specialized>());

From beeef9b38de6afb154e7d38817b021d4c497cb88 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 8 Aug 2024 18:04:07 -0400
Subject: [PATCH 281/399] Fix CUDA type trait differences

---
 include/boost/math/distributions/bernoulli.hpp | 5 +++--
 include/boost/math/special_functions/beta.hpp  | 5 +++--
 include/boost/math/special_functions/gamma.hpp | 9 +++++----
 3 files changed, 11 insertions(+), 8 deletions(-)

diff --git a/include/boost/math/distributions/bernoulli.hpp b/include/boost/math/distributions/bernoulli.hpp
index 30ab60b6c4..639f9119cd 100644
--- a/include/boost/math/distributions/bernoulli.hpp
+++ b/include/boost/math/distributions/bernoulli.hpp
@@ -31,6 +31,7 @@
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/distributions/complement.hpp> // complements
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
@@ -57,12 +58,12 @@ namespace boost
         return true;
       }
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */, const std::true_type&)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& /* pol */, const boost::math::true_type&)
       {
         return check_success_fraction(function, p, result, Policy());
       }
       template <class RealType, class Policy>
-      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* , const RealType& , RealType* , const Policy& /* pol */, const std::false_type&)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* , const RealType& , RealType* , const Policy& /* pol */, const boost::math::false_type&)
       {
          return true;
       }
diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 07ac9d5a6b..75968f3ebe 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -13,6 +13,7 @@
 
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/binomial.hpp>
 #include <boost/math/special_functions/factorials.hpp>
@@ -1569,7 +1570,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_derivative_imp(T a, T b, T x, const Policy& pol)
 //
 template <class RT1, class RT2, class Policy>
 BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2>::type
-   beta(RT1 a, RT2 b, const Policy&, const std::true_type*)
+   beta(RT1 a, RT2 b, const Policy&, const boost::math::true_type*)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<RT1, RT2>::type result_type;
@@ -1586,7 +1587,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2>::type
 }
 template <class RT1, class RT2, class RT3>
 BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
-   beta(RT1 a, RT2 b, RT3 x, const std::false_type*)
+   beta(RT1 a, RT2 b, RT3 x, const boost::math::false_type*)
 {
    return boost::math::beta(a, b, x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index dc017462e1..0d5e5f0b23 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -21,6 +21,7 @@
 #include <boost/math/tools/fraction.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/tools/assert.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
@@ -1875,7 +1876,7 @@ BOOST_MATH_GPU_ENABLED T gamma_p_derivative_imp(T a, T x, const Policy& pol)
 
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
-   tgamma(T z, const Policy& /* pol */, const std::true_type)
+   tgamma(T z, const Policy& /* pol */, const boost::math::true_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
@@ -1983,7 +1984,7 @@ const typename lgamma_initializer<T, Policy>::init lgamma_initializer<T, Policy>
 
 template <class T1, class T2, class Policy>
 BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
-   tgamma(T1 a, T2 z, const Policy&, const std::false_type)
+   tgamma(T1 a, T2 z, const Policy&, const boost::math::false_type)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef tools::promote_args_t<T1, T2> result_type;
@@ -2006,7 +2007,7 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 
 template <class T1, class T2>
 BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
-   tgamma(T1 a, T2 z, const std::false_type& tag)
+   tgamma(T1 a, T2 z, const boost::math::false_type& tag)
 {
    return tgamma(a, z, policies::policy<>(), tag);
 }
@@ -2107,7 +2108,7 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    tgamma(T1 a, T2 z, const Policy& pol)
 {
    using result_type = tools::promote_args_t<T1, T2>;
-   return static_cast<result_type>(detail::tgamma(a, z, pol, std::false_type()));
+   return static_cast<result_type>(detail::tgamma(a, z, pol, boost::math::false_type()));
 }
 //
 // Full lower incomplete gamma:

From 65096bee14b66788eba3694fc7d317aa8854d845 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 10:01:08 -0400
Subject: [PATCH 282/399] Add formulas for logcdf and logpdf to the tables

---
 doc/distributions/exponential.qbk            | 2 ++
 doc/distributions/extreme_value.qbk          | 2 ++
 doc/distributions/gamma.qbk                  | 1 +
 doc/distributions/geometric.qbk              | 1 +
 doc/distributions/inverse_gamma.qbk          | 3 ++-
 doc/distributions/inverse_gaussian.qbk       | 1 +
 doc/distributions/laplace.qbk                | 8 ++++++++
 doc/distributions/logistic.qbk               | 1 +
 doc/distributions/normal.qbk                 | 1 +
 doc/distributions/pareto.qbk                 | 1 +
 doc/distributions/poisson.qbk                | 1 +
 doc/distributions/rayleigh.qbk               | 2 ++
 doc/distributions/weibull.qbk                | 2 ++
 include/boost/math/distributions/laplace.hpp | 2 +-
 14 files changed, 26 insertions(+), 2 deletions(-)

diff --git a/doc/distributions/exponential.qbk b/doc/distributions/exponential.qbk
index 0b7ea5cbb1..b47f0b8bcd 100644
--- a/doc/distributions/exponential.qbk
+++ b/doc/distributions/exponential.qbk
@@ -74,7 +74,9 @@ In the following table [lambda] is the parameter lambda of the distribution,
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = [lambda] * exp(-[lambda] * x) ]]
+[[logpdf][log(pdf) = -expm1(-x * [lambda]) ]]
 [[cdf][Using the relation: p = 1 - exp(-x * [lambda]) = -expm1(-x * [lambda]) ]]
+[[logcdf][log(cdf) = log1p(-exp(-x * [lambda])) ]]
 [[cdf complement][Using the relation: q = exp(-x * [lambda]) ]]
 [[quantile][Using the relation: x = -log(1-p) / [lambda] = -log1p(-p) / [lambda]]]
 [[quantile from the complement][Using the relation: x = -log(q) / [lambda]]]
diff --git a/doc/distributions/extreme_value.qbk b/doc/distributions/extreme_value.qbk
index 56c4fb5dfd..43f68546f9 100644
--- a/doc/distributions/extreme_value.qbk
+++ b/doc/distributions/extreme_value.qbk
@@ -99,7 +99,9 @@ In the following table:
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = exp((a-x)/b) * exp(-exp((a-x)/b)) / b ]]
+[[logpdf][log(pdf) = log(1/b) + e - exp(e) ]]
 [[cdf][Using the relation: p = exp(-exp((a-x)/b)) ]]
+[[logcdf][log(cdf) = -exp((a-x)/b) ]]
 [[cdf complement][Using the relation: q = -expm1(-exp((a-x)/b)) ]]
 [[quantile][Using the relation: a - log(-log(p)) * b]]
 [[quantile from the complement][Using the relation: a - log(-log1p(-q)) * b]]
diff --git a/doc/distributions/gamma.qbk b/doc/distributions/gamma.qbk
index 8e53ec6ee4..56be002194 100644
--- a/doc/distributions/gamma.qbk
+++ b/doc/distributions/gamma.qbk
@@ -118,6 +118,7 @@ and /q = 1-p/.
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = __gamma_p_derivative(k, x / [theta]) / [theta] ]]
+[[logpdf][log(pdf) = -k*log([theta]) + (k-1)*log(x) - lgamma(k) - (x/[theta]) ]]
 [[cdf][Using the relation: p = __gamma_p(k, x / [theta]) ]]
 [[cdf complement][Using the relation: q = __gamma_q(k, x / [theta]) ]]
 [[quantile][Using the relation: x = [theta] * __gamma_p_inv(k, p) ]]
diff --git a/doc/distributions/geometric.qbk b/doc/distributions/geometric.qbk
index 9992b016de..cf1e2bff08 100644
--- a/doc/distributions/geometric.qbk
+++ b/doc/distributions/geometric.qbk
@@ -325,6 +325,7 @@ the expected number of failures using the quantile.
 [[Function][Implementation Notes]]
 [[pdf][pdf =  p * pow(q, k)]]
 [[cdf][cdf = 1 - q[super k=1]]]
+[[logcdf][log(cdf) = log1p(-exp(log1p(-p) * (k+1)))]]
 [[cdf complement][exp(log1p(-p) * (k+1))]]
 [[quantile][k = log1p(-x) / log1p(-p) -1]]
 [[quantile from the complement][k = log(x) / log1p(-p) -1]]
diff --git a/doc/distributions/inverse_gamma.qbk b/doc/distributions/inverse_gamma.qbk
index 8fb64dde84..51d6538846 100644
--- a/doc/distributions/inverse_gamma.qbk
+++ b/doc/distributions/inverse_gamma.qbk
@@ -102,12 +102,13 @@ But in general, inverse_gamma results are accurate to a few epsilon,
 [h4 Implementation]
 
 In the following table [alpha] is the shape parameter of the distribution, 
-[alpha] is its scale parameter, /x/ is the random variate, /p/ is the probability
+[beta] is its scale parameter, /x/ is the random variate, /p/ is the probability
 and /q = 1-p/.
 
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = __gamma_p_derivative([alpha], [beta]/ x, [beta]) / x * x ]]
+[[logpdf][log(pdf) = [alpha] * log([beta]) + (-[alpha]-1)*log(x) - lgamma([alpha]) - ([beta]/x) ]]
 [[cdf][Using the relation: p = __gamma_q([alpha], [beta] / x) ]]
 [[cdf complement][Using the relation: q = __gamma_p([alpha], [beta] / x) ]]
 [[quantile][Using the relation: x = [beta]/ __gamma_q_inv([alpha], p) ]]
diff --git a/doc/distributions/inverse_gaussian.qbk b/doc/distributions/inverse_gaussian.qbk
index 776a377726..6187a3835b 100644
--- a/doc/distributions/inverse_gaussian.qbk
+++ b/doc/distributions/inverse_gaussian.qbk
@@ -137,6 +137,7 @@ are used for the inverse gaussian function.
 [table
 [[Function] [Implementation Notes] ]
 [[pdf] [ [sqrt]([lambda]/ 2[pi]x[super 3]) e[super -[lambda](x - [mu])[sup2]/ 2[mu][sup2]x]]]
+[[logpdf] [log(pdf) = (-[lambda]*pow([mu]-x, 2)/(x*[mu][super 2]) + log([lambda]) - 3*log(x) - log(2*[pi])) / 2 ]]
 [[cdf][ [Phi]{[sqrt]([lambda]/x) (x/[mu]-1)} + e[super 2[mu]/[lambda]] [Phi]{-[sqrt]([lambda]/[mu]) (1+x/[mu])} ]]
 [[cdf complement] [using complement of [Phi] above.] ]
 [[quantile][No closed form known. Estimated using a guess refined by Newton-Raphson iteration.]]
diff --git a/doc/distributions/laplace.qbk b/doc/distributions/laplace.qbk
index 998072811f..1afa7f4e1e 100644
--- a/doc/distributions/laplace.qbk
+++ b/doc/distributions/laplace.qbk
@@ -93,11 +93,19 @@ and its complement /q = 1-p/.
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = e[super -abs(x-[mu]) \/ [sigma]] \/ (2 * [sigma]) ]]
+[[logpdf][log(pdf) = -abs(x-[mu])/[sigma] - log([sigma]) - log(2) ]]
 [[cdf][Using the relations:
 
 x <  [mu] : p =  e[super (x-[mu])/[sigma] ] \/ [sigma]
 
 x >= [mu] : p =  1 - e[super ([mu]-x)/[sigma] ] \/ [sigma]
+]]
+[[logcdf][log(cdf) = 
+
+x <  [mu] : p = ((x - [mu]) / [sigma]) - ln(2)
+
+x >= [mu] : p = log1p(-exp(([mu]-x) / [sigma]) / 2)
+
 ]]
 [[cdf complement][Using the relation:
 
diff --git a/doc/distributions/logistic.qbk b/doc/distributions/logistic.qbk
index ba1b29a17e..84b3a24f1d 100644
--- a/doc/distributions/logistic.qbk
+++ b/doc/distributions/logistic.qbk
@@ -85,6 +85,7 @@ in such cases, only a low /absolute error/ can be guaranteed.
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = e[super -(x-u)/s] / (s*(1+e[super -(x-u)/s])[super 2])]]
 [[cdf][Using the relation: p = 1/(1+e[super -(x-u)/s])]]
+[[logcdf][log(cdf) = -log1p(exp((u-x)/s)) ]]
 [[cdf complement][Using the relation: q = 1/(1+e[super (x-u)/s])]]
 [[quantile][Using the relation: x = u - s*log(1/p-1)]]
 [[quantile from the complement][Using the relation: x = u + s*log(p/1-p)]]
diff --git a/doc/distributions/normal.qbk b/doc/distributions/normal.qbk
index 52ac44e96b..eefe4e967b 100644
--- a/doc/distributions/normal.qbk
+++ b/doc/distributions/normal.qbk
@@ -97,6 +97,7 @@ and /s/ is its standard deviation.
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = e[super -(x-m)[super 2]\/(2s[super 2])] \/ (s * sqrt(2*pi)) ]]
+[[logpdf][log(pdf) = -log(s) - log(2*[pi])/2 - (x-mean)[super 2]/(2*s[super 2]) ]]
 [[cdf][Using the relation: p = 0.5 * __erfc(-(x-m)/(s*sqrt(2))) ]]
 [[cdf complement][Using the relation: q = 0.5 * __erfc((x-m)/(s*sqrt(2))) ]]
 [[quantile][Using the relation: x = m - s * sqrt(2) * __erfc_inv(2*p)]]
diff --git a/doc/distributions/pareto.qbk b/doc/distributions/pareto.qbk
index 7938ed86d8..6a89b0dbc5 100644
--- a/doc/distributions/pareto.qbk
+++ b/doc/distributions/pareto.qbk
@@ -94,6 +94,7 @@ and its complement /q = 1-p/.
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf p = [alpha][beta][super [alpha]]/x[super [alpha] +1] ]]
 [[cdf][Using the relation: cdf p = 1 - ([beta] / x)[super [alpha]] ]]
+[[logcdf][log(cdf) = log1p(-pow([beta]/x, [alpha])) ]]
 [[cdf complement][Using the relation: q = 1 - p = -([beta] / x)[super [alpha]] ]]
 [[quantile][Using the relation: x = [beta] / (1 - p)[super 1/[alpha]] ]]
 [[quantile from the complement][Using the relation: x =  [beta] / (q)[super 1/[alpha]] ]]
diff --git a/doc/distributions/poisson.qbk b/doc/distributions/poisson.qbk
index a1ccc1b8b7..01cfb13cc5 100644
--- a/doc/distributions/poisson.qbk
+++ b/doc/distributions/poisson.qbk
@@ -84,6 +84,7 @@ In the following table [lambda] is the mean of the distribution,
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = e[super -[lambda]] [lambda][super k] \/ k! ]]
+[[logpdf][log(pdf) = -lgamma(k+1) + k*log([lambda]) - [lambda] if k > 0 and [lambda] > 0 ]]
 [[cdf][Using the relation: p = [Gamma](k+1, [lambda]) \/ k! = __gamma_q(k+1, [lambda])]]
 [[cdf complement][Using the relation: q = __gamma_p(k+1, [lambda]) ]]
 [[quantile][Using the relation: k = __gamma_q_inva([lambda], p) - 1]]
diff --git a/doc/distributions/rayleigh.qbk b/doc/distributions/rayleigh.qbk
index 89054ac0e3..609b654da7 100644
--- a/doc/distributions/rayleigh.qbk
+++ b/doc/distributions/rayleigh.qbk
@@ -95,7 +95,9 @@ In the following table [sigma] is the sigma parameter of the distribution,
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = x * exp(-x[super 2])/2 [sigma][super 2] ]]
+[[logpdf][log(pdf) = -(x[super 2])/(2*[sigma][super 2]) - 2*log([sigma]) + log(x) ]]
 [[cdf][Using the relation: p = 1 - exp(-x[super 2]/2) [sigma][super 2]= -__expm1(-x[super 2]/2) [sigma][super 2]]]
+[[logcdf][log(cdf) = log1p(-exp(-x[super 2] / (2*[sigma][super 2]))) ]]
 [[cdf complement][Using the relation: q =  exp(-x[super 2]/ 2) * [sigma][super 2] ]]
 [[quantile][Using the relation: x = sqrt(-2 * [sigma] [super 2]) * log(1 - p)) = sqrt(-2 * [sigma] [super 2]) * __log1p(-p))]]
 [[quantile from the complement][Using the relation: x = sqrt(-2 * [sigma] [super 2]) * log(q)) ]]
diff --git a/doc/distributions/weibull.qbk b/doc/distributions/weibull.qbk
index d01ceded9e..3ec18b18d9 100644
--- a/doc/distributions/weibull.qbk
+++ b/doc/distributions/weibull.qbk
@@ -107,7 +107,9 @@ and /q = 1-p/.
 [table
 [[Function][Implementation Notes]]
 [[pdf][Using the relation: pdf = [alpha][beta][super -[alpha] ]x[super [alpha] - 1] e[super -(x/beta)[super alpha]] ]]
+[[logpdf][log(pdf) = log([alpha]) - [alpha] * log([beta]) + log(x) * ([alpha]-1) - pow(x/[beta], [alpha]) ]]
 [[cdf][Using the relation: p = -__expm1(-(x\/[beta])[super [alpha]]) ]]
+[[logcdf][log(cdf) = log1p(-exp(-pow(x / [beta], [alpha]))) ]]
 [[cdf complement][Using the relation: q = e[super -(x\/[beta])[super [alpha]]] ]]
 [[quantile][Using the relation: x = [beta] * (-__log1p(-p))[super 1\/[alpha]] ]]
 [[quantile from the complement][Using the relation: x = [beta] * (-log(q))[super 1\/[alpha]] ]]
diff --git a/include/boost/math/distributions/laplace.hpp b/include/boost/math/distributions/laplace.hpp
index 55e2236f99..4d1fc46569 100644
--- a/include/boost/math/distributions/laplace.hpp
+++ b/include/boost/math/distributions/laplace.hpp
@@ -182,7 +182,7 @@ BOOST_MATH_GPU_ENABLED inline RealType logpdf(const laplace_distribution<RealTyp
    const RealType mu = dist.scale();
    const RealType b = dist.location();
 
-   // if b is 0 avoid divde by 0 error
+   // if b is 0 avoid divide by 0 error
    if(abs(b) < boost::math::numeric_limits<RealType>::epsilon())
    {
       result = log(pdf(dist, x));

From ee01d41fd3f978c774d0cb2a91e5accbb24b37c6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:18:56 -0400
Subject: [PATCH 283/399] Add NVRTC support to cos_pi

---
 .../boost/math/special_functions/cos_pi.hpp   | 40 ++++++++++++++++++-
 1 file changed, 39 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/cos_pi.hpp b/include/boost/math/special_functions/cos_pi.hpp
index 5a7c742b49..7c33614de7 100644
--- a/include/boost/math/special_functions/cos_pi.hpp
+++ b/include/boost/math/special_functions/cos_pi.hpp
@@ -11,9 +11,12 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <limits>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/trunc.hpp>
@@ -86,5 +89,40 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cos_pi(T x)
 
 } // namespace math
 } // namespace boost
+
+#else // Special handling for NVRTC
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto cos_pi(T x)
+{
+   return ::cospi(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto cos_pi(float x)
+{
+   return ::cospif(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto cos_pi(T x, const Policy&)
+{
+   return ::cospi(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto cos_pi(float x, const Policy&)
+{
+   return ::cospif(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif
 

From dac34c5853e931341e7bc6076fed5f9009518b27 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:19:10 -0400
Subject: [PATCH 284/399] Add cos_pi NVRTC testing

---
 test/nvrtc_jamfile                |   2 +
 test/test_cos_pi_nvrtc_double.cpp | 186 ++++++++++++++++++++++++++++++
 test/test_cos_pi_nvrtc_float.cpp  | 186 ++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_cos_pi_nvrtc_double.cpp
 create mode 100644 test/test_cos_pi_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 703bf8099a..38f9f2476c 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -12,6 +12,8 @@ project : requirements
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
+run test_cos_pi_nvrtc_double.cpp ;
+run test_cos_pi_nvrtc_float.cpp ;
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
diff --git a/test/test_cos_pi_nvrtc_double.cpp b/test/test_cos_pi_nvrtc_double.cpp
new file mode 100644
index 0000000000..459524bbed
--- /dev/null
+++ b/test/test_cos_pi_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/cos_pi.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/cos_pi.hpp>
+extern "C" __global__ 
+void test_cos_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cos_pi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cos_pi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cos_pi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cos_pi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::cos_pi(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cos_pi_nvrtc_float.cpp b/test/test_cos_pi_nvrtc_float.cpp
new file mode 100644
index 0000000000..7c1eef3faa
--- /dev/null
+++ b/test/test_cos_pi_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/cos_pi.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/cos_pi.hpp>
+extern "C" __global__ 
+void test_cos_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cos_pi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cos_pi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cos_pi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cos_pi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::cos_pi(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 635df5dd5fa139697ac4dbe0152b469413333526 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:23:35 -0400
Subject: [PATCH 285/399] Add NVRTC support to sin_pi

---
 .../boost/math/special_functions/sin_pi.hpp   | 40 ++++++++++++++++++-
 1 file changed, 39 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/sin_pi.hpp b/include/boost/math/special_functions/sin_pi.hpp
index 3e16bfc96b..e59e232e6d 100644
--- a/include/boost/math/special_functions/sin_pi.hpp
+++ b/include/boost/math/special_functions/sin_pi.hpp
@@ -11,10 +11,13 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <limits>
 #include <type_traits>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/trunc.hpp>
@@ -94,5 +97,40 @@ inline typename tools::promote_args<T>::type sin_pi(T x)
 
 } // namespace math
 } // namespace boost
+
+#else // Special handling for NVRTC
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto sin_pi(T x)
+{
+   return ::sinpi(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto sin_pi(float x)
+{
+   return ::sinpif(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto sin_pi(T x, const Policy&)
+{
+   return ::sinpi(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto sin_pi(float x, const Policy&)
+{
+   return ::sinpif(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif
 

From 375d316aacaf1d9eb52559e60bdf90e4043c9b38 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:23:46 -0400
Subject: [PATCH 286/399] Add sin_pi NVRTC testing

---
 test/nvrtc_jamfile                |   2 +
 test/test_sin_pi_nvrtc_double.cpp | 186 ++++++++++++++++++++++++++++++
 test/test_sin_pi_nvrtc_float.cpp  | 186 ++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_sin_pi_nvrtc_double.cpp
 create mode 100644 test/test_sin_pi_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 38f9f2476c..9eebb3df58 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -26,4 +26,6 @@ run test_round_nvrtc_double.cpp ;
 run test_round_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
+run test_sin_pi_nvrtc_double.cpp ;
+run test_sin_pi_nvrtc_float.cpp ;
 run test_trunc_nvrtc_double.cpp ;
diff --git a/test/test_sin_pi_nvrtc_double.cpp b/test/test_sin_pi_nvrtc_double.cpp
new file mode 100644
index 0000000000..b6cff9798b
--- /dev/null
+++ b/test/test_sin_pi_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/sin_pi.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/sin_pi.hpp>
+extern "C" __global__ 
+void test_sin_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sin_pi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sin_pi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sin_pi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sin_pi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::sin_pi(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sin_pi_nvrtc_float.cpp b/test/test_sin_pi_nvrtc_float.cpp
new file mode 100644
index 0000000000..32cc380593
--- /dev/null
+++ b/test/test_sin_pi_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/sin_pi.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/sin_pi.hpp>
+extern "C" __global__ 
+void test_sin_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sin_pi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sin_pi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sin_pi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sin_pi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::sin_pi(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 37a08c0280a84985055a26d092a3164b506af9b1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:38:14 -0400
Subject: [PATCH 287/399] Add NVRTC support to erf and erfc

---
 include/boost/math/special_functions/erf.hpp | 63 +++++++++++++++++++-
 1 file changed, 62 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/erf.hpp b/include/boost/math/special_functions/erf.hpp
index 789d116b90..9f0da9282f 100644
--- a/include/boost/math/special_functions/erf.hpp
+++ b/include/boost/math/special_functions/erf.hpp
@@ -11,8 +11,11 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/tools/roots.hpp>
 #include <boost/math/policies/error_handling.hpp>
@@ -1273,6 +1276,64 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erfc(T z)
 } // namespace math
 } // namespace boost
 
+#else // Special handling for NVRTC platform
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto erf(T x)
+{
+   return ::erf(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto erf(float x)
+{
+   return ::erff(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto erf(T x, const Policy&)
+{
+   return ::erf(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto erf(float x, const Policy&)
+{
+   return ::erff(x);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto erfc(T x)
+{
+   return ::erfc(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto erfc(float x)
+{
+   return ::erfcf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto erfc(T x, const Policy&)
+{
+   return ::erfc(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto erfc(float x, const Policy&)
+{
+   return ::erfcf(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/special_functions/detail/erf_inv.hpp>
 
 #endif // BOOST_MATH_SPECIAL_ERF_HPP

From 666564bdddfb27ea1edcdd5718e416e4fbe8749a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:38:27 -0400
Subject: [PATCH 288/399] Add erf NVRTC testing

---
 test/nvrtc_jamfile             |   2 +
 test/test_erf_nvrtc_double.cpp | 186 +++++++++++++++++++++++++++++++++
 test/test_erf_nvrtc_float.cpp  | 186 +++++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_erf_nvrtc_double.cpp
 create mode 100644 test/test_erf_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 9eebb3df58..5b19c4bd2b 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -14,6 +14,8 @@ run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
 run test_cos_pi_nvrtc_double.cpp ;
 run test_cos_pi_nvrtc_float.cpp ;
+run test_erf_nvrtc_double.cpp ;
+run test_erf_nvrtc_float.cpp ;
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
diff --git a/test/test_erf_nvrtc_double.cpp b/test/test_erf_nvrtc_double.cpp
new file mode 100644
index 0000000000..e20d0188d0
--- /dev/null
+++ b/test/test_erf_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erf(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_erf_nvrtc_float.cpp b/test/test_erf_nvrtc_float.cpp
new file mode 100644
index 0000000000..913b1a14cc
--- /dev/null
+++ b/test/test_erf_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erf(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 463699e8cac4ee00dd1f725b908292746e56b66e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:40:23 -0400
Subject: [PATCH 289/399] Add erfc NVRTC testing

---
 test/nvrtc_jamfile              |   2 +
 test/test_erfc_nvrtc_double.cpp | 186 ++++++++++++++++++++++++++++++++
 test/test_erfc_nvrtc_float.cpp  | 186 ++++++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_erfc_nvrtc_double.cpp
 create mode 100644 test/test_erfc_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 5b19c4bd2b..fa04990e5c 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -16,6 +16,8 @@ run test_cos_pi_nvrtc_double.cpp ;
 run test_cos_pi_nvrtc_float.cpp ;
 run test_erf_nvrtc_double.cpp ;
 run test_erf_nvrtc_float.cpp ;
+run test_erfc_nvrtc_double.cpp ;
+run test_erfc_nvrtc_float.cpp ;
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
diff --git a/test/test_erfc_nvrtc_double.cpp b/test/test_erfc_nvrtc_double.cpp
new file mode 100644
index 0000000000..c43a469acf
--- /dev/null
+++ b/test/test_erfc_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erfc(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_erfc_nvrtc_float.cpp b/test/test_erfc_nvrtc_float.cpp
new file mode 100644
index 0000000000..f8756045a8
--- /dev/null
+++ b/test/test_erfc_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erfc(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From dd711380e261cb5974a375867e31eb34d63c6316 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:47:55 -0400
Subject: [PATCH 290/399] Fix types in NVRTC testing

---
 test/test_cos_pi_nvrtc_float.cpp | 2 +-
 test/test_sin_pi_nvrtc_float.cpp | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/test_cos_pi_nvrtc_float.cpp b/test/test_cos_pi_nvrtc_float.cpp
index 7c1eef3faa..2f541e217d 100644
--- a/test/test_cos_pi_nvrtc_float.cpp
+++ b/test/test_cos_pi_nvrtc_float.cpp
@@ -21,7 +21,7 @@
 typedef float float_type;
 
 const char* cuda_kernel = R"(
-typedef double float_type;
+typedef float float_type;
 #include <boost/math/special_functions/cos_pi.hpp>
 extern "C" __global__ 
 void test_cos_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
diff --git a/test/test_sin_pi_nvrtc_float.cpp b/test/test_sin_pi_nvrtc_float.cpp
index 32cc380593..f67079774f 100644
--- a/test/test_sin_pi_nvrtc_float.cpp
+++ b/test/test_sin_pi_nvrtc_float.cpp
@@ -21,7 +21,7 @@
 typedef float float_type;
 
 const char* cuda_kernel = R"(
-typedef double float_type;
+typedef float float_type;
 #include <boost/math/special_functions/sin_pi.hpp>
 extern "C" __global__ 
 void test_sin_pi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)

From 6a4487453d95c1fbf5ecf3da18f2c020a89fd612 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:48:12 -0400
Subject: [PATCH 291/399] Add NVRTC support to erf_inv and erfc_inv

---
 .../math/special_functions/detail/erf_inv.hpp | 61 +++++++++++++++++++
 1 file changed, 61 insertions(+)

diff --git a/include/boost/math/special_functions/detail/erf_inv.hpp b/include/boost/math/special_functions/detail/erf_inv.hpp
index 69a08abe66..cb65cffbc1 100644
--- a/include/boost/math/special_functions/detail/erf_inv.hpp
+++ b/include/boost/math/special_functions/detail/erf_inv.hpp
@@ -15,6 +15,9 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <type_traits>
 
 namespace boost{ namespace math{
@@ -490,6 +493,64 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type erf_inv(T z)
 } // namespace math
 } // namespace boost
 
+#else // Special handling for NVRTC
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto erf_inv(T x)
+{
+   return ::erfinv(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto erf_inv(float x)
+{
+   return ::erfinvf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto erf_inv(T x, const Policy&)
+{
+   return ::erfinv(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto erf_inv(float x, const Policy&)
+{
+   return ::erfinvf(x);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED auto erfc_inv(T x)
+{
+   return ::erfcinv(x);
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED auto erfc_inv(float x)
+{
+   return ::erfcinvf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto erfc_inv(T x, const Policy&)
+{
+   return ::erfcinv(x);
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED auto erfc_inv(float x, const Policy&)
+{
+   return ::erfcinvf(x);
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_NVRTV
+
 #ifdef _MSC_VER
 #pragma warning(pop)
 #endif

From 6c4b56c9be71a98d6027f6666811eaf350ee8cbe Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:48:26 -0400
Subject: [PATCH 292/399] Add erf_inv NVRTC testing

---
 test/nvrtc_jamfile                 |   2 +
 test/test_erf_inv_nvrtc_double.cpp | 186 +++++++++++++++++++++++++++++
 test/test_erf_inv_nvrtc_float.cpp  | 186 +++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_erf_inv_nvrtc_double.cpp
 create mode 100644 test/test_erf_inv_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index fa04990e5c..d36a3381d6 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -18,6 +18,8 @@ run test_erf_nvrtc_double.cpp ;
 run test_erf_nvrtc_float.cpp ;
 run test_erfc_nvrtc_double.cpp ;
 run test_erfc_nvrtc_float.cpp ;
+run test_erf_inv_nvrtc_double.cpp ;
+run test_erf_inv_nvrtc_float.cpp ;
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
diff --git a/test/test_erf_inv_nvrtc_double.cpp b/test/test_erf_inv_nvrtc_double.cpp
new file mode 100644
index 0000000000..5588b76689
--- /dev/null
+++ b/test/test_erf_inv_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf_inv(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erf_inv(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_erf_inv_nvrtc_float.cpp b/test/test_erf_inv_nvrtc_float.cpp
new file mode 100644
index 0000000000..ff7f6db98b
--- /dev/null
+++ b/test/test_erf_inv_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erf_inv(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erf_inv(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 993d92dc66793a038aba45785c1ea684e1757fb1 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 11:49:56 -0400
Subject: [PATCH 293/399] Add erfc_inv NVRTC testing

---
 test/nvrtc_jamfile                  |   2 +
 test/test_erfc_inv_nvrtc_double.cpp | 186 ++++++++++++++++++++++++++++
 test/test_erfc_inv_nvrtc_float.cpp  | 186 ++++++++++++++++++++++++++++
 3 files changed, 374 insertions(+)
 create mode 100644 test/test_erfc_inv_nvrtc_double.cpp
 create mode 100644 test/test_erfc_inv_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index d36a3381d6..9e59740e61 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -20,6 +20,8 @@ run test_erfc_nvrtc_double.cpp ;
 run test_erfc_nvrtc_float.cpp ;
 run test_erf_inv_nvrtc_double.cpp ;
 run test_erf_inv_nvrtc_float.cpp ;
+run test_erfc_inv_nvrtc_double.cpp ;
+run test_erfc_inv_nvrtc_float.cpp ;
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 run test_fpclassify_nvrtc_double.cpp ;
diff --git a/test/test_erfc_inv_nvrtc_double.cpp b/test/test_erfc_inv_nvrtc_double.cpp
new file mode 100644
index 0000000000..ae961d657e
--- /dev/null
+++ b/test/test_erfc_inv_nvrtc_double.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc_inv(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erfc_inv(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_erfc_inv_nvrtc_float.cpp b/test/test_erfc_inv_nvrtc_float.cpp
new file mode 100644
index 0000000000..b676330ceb
--- /dev/null
+++ b/test/test_erfc_inv_nvrtc_float.cpp
@@ -0,0 +1,186 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/erf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/special_functions/erf.hpp>
+extern "C" __global__ 
+void test_erf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::erfc_inv(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_erf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_erf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_erf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = boost::math::erfc_inv(h_in1[i]);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From aa33cdf7843875b8acfd3f508d3241b821fa58a9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:04:17 -0400
Subject: [PATCH 294/399] Update polynomial evaluation for NVRTC

---
 .../tools/detail/polynomial_horner1_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner1_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner1_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner1_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner1_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner1_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner1_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner1_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner1_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner1_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner1_2.hpp     |  6 +-
 .../tools/detail/polynomial_horner1_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner1_3.hpp     |  8 +--
 .../tools/detail/polynomial_horner1_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner1_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner1_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner1_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner1_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner1_9.hpp     | 20 +++----
 .../tools/detail/polynomial_horner2_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner2_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner2_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner2_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner2_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner2_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner2_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner2_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner2_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner2_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner2_2.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner2_3.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner2_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner2_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner2_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner2_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner2_9.hpp     | 20 +++----
 .../tools/detail/polynomial_horner3_10.hpp    | 22 +++----
 .../tools/detail/polynomial_horner3_11.hpp    | 24 ++++----
 .../tools/detail/polynomial_horner3_12.hpp    | 26 ++++----
 .../tools/detail/polynomial_horner3_13.hpp    | 28 ++++-----
 .../tools/detail/polynomial_horner3_14.hpp    | 30 +++++-----
 .../tools/detail/polynomial_horner3_15.hpp    | 32 +++++-----
 .../tools/detail/polynomial_horner3_16.hpp    | 34 +++++------
 .../tools/detail/polynomial_horner3_17.hpp    | 36 +++++------
 .../tools/detail/polynomial_horner3_18.hpp    | 38 ++++++------
 .../tools/detail/polynomial_horner3_19.hpp    | 40 ++++++-------
 .../tools/detail/polynomial_horner3_2.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_20.hpp    | 42 ++++++-------
 .../tools/detail/polynomial_horner3_3.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_4.hpp     | 10 ++--
 .../tools/detail/polynomial_horner3_5.hpp     | 12 ++--
 .../tools/detail/polynomial_horner3_6.hpp     | 14 ++---
 .../tools/detail/polynomial_horner3_7.hpp     | 16 ++---
 .../tools/detail/polynomial_horner3_8.hpp     | 18 +++---
 .../tools/detail/polynomial_horner3_9.hpp     | 20 +++----
 .../math/tools/detail/rational_horner1_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner1_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner1_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner1_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner1_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner1_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner1_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner1_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner1_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner1_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner1_2.hpp  |  6 +-
 .../math/tools/detail/rational_horner1_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner1_3.hpp  |  8 +--
 .../math/tools/detail/rational_horner1_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner1_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner1_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner1_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner1_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner1_9.hpp  | 20 +++----
 .../math/tools/detail/rational_horner2_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner2_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner2_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner2_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner2_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner2_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner2_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner2_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner2_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner2_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner2_2.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner2_3.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner2_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner2_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner2_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner2_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner2_9.hpp  | 20 +++----
 .../math/tools/detail/rational_horner3_10.hpp | 22 +++----
 .../math/tools/detail/rational_horner3_11.hpp | 24 ++++----
 .../math/tools/detail/rational_horner3_12.hpp | 26 ++++----
 .../math/tools/detail/rational_horner3_13.hpp | 28 ++++-----
 .../math/tools/detail/rational_horner3_14.hpp | 30 +++++-----
 .../math/tools/detail/rational_horner3_15.hpp | 32 +++++-----
 .../math/tools/detail/rational_horner3_16.hpp | 34 +++++------
 .../math/tools/detail/rational_horner3_17.hpp | 36 +++++------
 .../math/tools/detail/rational_horner3_18.hpp | 38 ++++++------
 .../math/tools/detail/rational_horner3_19.hpp | 40 ++++++-------
 .../math/tools/detail/rational_horner3_2.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_20.hpp | 42 ++++++-------
 .../math/tools/detail/rational_horner3_3.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_4.hpp  | 10 ++--
 .../math/tools/detail/rational_horner3_5.hpp  | 12 ++--
 .../math/tools/detail/rational_horner3_6.hpp  | 14 ++---
 .../math/tools/detail/rational_horner3_7.hpp  | 16 ++---
 .../math/tools/detail/rational_horner3_8.hpp  | 18 +++---
 .../math/tools/detail/rational_horner3_9.hpp  | 20 +++----
 include/boost/math/tools/rational.hpp         | 54 ++++++++++-------
 tools/generate_rational_code.cpp              | 60 +++++++++----------
 116 files changed, 1443 insertions(+), 1431 deletions(-)

diff --git a/include/boost/math/tools/detail/polynomial_horner1_10.hpp b/include/boost/math/tools/detail/polynomial_horner1_10.hpp
index 37e4cba010..04ad90b69b 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_10.hpp
@@ -12,67 +12,67 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_11.hpp b/include/boost/math/tools/detail/polynomial_horner1_11.hpp
index 885490f223..f99ab82507 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_11.hpp
@@ -12,73 +12,73 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_12.hpp b/include/boost/math/tools/detail/polynomial_horner1_12.hpp
index f540345926..3006ebe51e 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_12.hpp
@@ -12,79 +12,79 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_13.hpp b/include/boost/math/tools/detail/polynomial_horner1_13.hpp
index e9e13bd529..0f11189097 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_13.hpp
@@ -12,85 +12,85 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_14.hpp b/include/boost/math/tools/detail/polynomial_horner1_14.hpp
index eaa18bdc56..caba4b97ea 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_14.hpp
@@ -12,91 +12,91 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_15.hpp b/include/boost/math/tools/detail/polynomial_horner1_15.hpp
index c4a8804498..c8f42ac813 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_15.hpp
@@ -12,97 +12,97 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_16.hpp b/include/boost/math/tools/detail/polynomial_horner1_16.hpp
index 5c262cc63b..2ed591ccf5 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_16.hpp
@@ -12,103 +12,103 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_17.hpp b/include/boost/math/tools/detail/polynomial_horner1_17.hpp
index 90d49a0bd8..5e9fc8cd7c 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_17.hpp
@@ -12,109 +12,109 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_18.hpp b/include/boost/math/tools/detail/polynomial_horner1_18.hpp
index 58fb83fd36..ffb62ff049 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_18.hpp
@@ -12,115 +12,115 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_19.hpp b/include/boost/math/tools/detail/polynomial_horner1_19.hpp
index 18a6af2d3f..56df108ac8 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_19.hpp
@@ -12,121 +12,121 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_2.hpp b/include/boost/math/tools/detail/polynomial_horner1_2.hpp
index 645e3f8785..63091ebddd 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_2.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_20.hpp b/include/boost/math/tools/detail/polynomial_horner1_20.hpp
index 47584e7871..c16e5143ec 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_20.hpp
@@ -12,127 +12,127 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((((((((((((((a[19] * x + a[18]) * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_3.hpp b/include/boost/math/tools/detail/polynomial_horner1_3.hpp
index 420bbcc28c..0aeccc1115 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_3.hpp
@@ -12,25 +12,25 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_4.hpp b/include/boost/math/tools/detail/polynomial_horner1_4.hpp
index 930798e74f..61058fce84 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_5.hpp b/include/boost/math/tools/detail/polynomial_horner1_5.hpp
index b97a8f9ebc..47021bc509 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_6.hpp b/include/boost/math/tools/detail/polynomial_horner1_6.hpp
index 6a699f5175..bfd24371d5 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_6.hpp
@@ -12,43 +12,43 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_7.hpp b/include/boost/math/tools/detail/polynomial_horner1_7.hpp
index 2aceeeca16..50ddca63ff 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_7.hpp
@@ -12,49 +12,49 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_8.hpp b/include/boost/math/tools/detail/polynomial_horner1_8.hpp
index 0486d642fe..3be7ba4d16 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_8.hpp
@@ -12,55 +12,55 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner1_9.hpp b/include/boost/math/tools/detail/polynomial_horner1_9.hpp
index b0838014b7..4ec53c48bd 100644
--- a/include/boost/math/tools/detail/polynomial_horner1_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner1_9.hpp
@@ -12,61 +12,61 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_10.hpp b/include/boost/math/tools/detail/polynomial_horner2_10.hpp
index 2a680d7560..f242d7464e 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_10.hpp
@@ -12,72 +12,72 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_11.hpp b/include/boost/math/tools/detail/polynomial_horner2_11.hpp
index 7036eec3f5..edf7f86c52 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_11.hpp
@@ -12,79 +12,79 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_12.hpp b/include/boost/math/tools/detail/polynomial_horner2_12.hpp
index fbbf2a3fa8..969c9c4ddd 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_12.hpp
@@ -12,86 +12,86 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_13.hpp b/include/boost/math/tools/detail/polynomial_horner2_13.hpp
index 46fb3859db..ed4559d11e 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_13.hpp
@@ -12,93 +12,93 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_14.hpp b/include/boost/math/tools/detail/polynomial_horner2_14.hpp
index d1c326e0f6..4b79eb78a4 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_14.hpp
@@ -12,100 +12,100 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_15.hpp b/include/boost/math/tools/detail/polynomial_horner2_15.hpp
index d679cfeaf5..28b62eee75 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_15.hpp
@@ -12,107 +12,107 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_16.hpp b/include/boost/math/tools/detail/polynomial_horner2_16.hpp
index 0f3ed8f6c8..6368b40548 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_16.hpp
@@ -12,114 +12,114 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_17.hpp b/include/boost/math/tools/detail/polynomial_horner2_17.hpp
index 7783c4c81d..551e6191cf 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_17.hpp
@@ -12,121 +12,121 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_18.hpp b/include/boost/math/tools/detail/polynomial_horner2_18.hpp
index 4e3b57f987..19cfdc19e1 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_18.hpp
@@ -12,128 +12,128 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_19.hpp b/include/boost/math/tools/detail/polynomial_horner2_19.hpp
index 9eca8ef114..9ea87fd93b 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_19.hpp
@@ -12,135 +12,135 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_2.hpp b/include/boost/math/tools/detail/polynomial_horner2_2.hpp
index 857d43fdb9..1982a81f3f 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_20.hpp b/include/boost/math/tools/detail/polynomial_horner2_20.hpp
index 2a83590256..23afe55e05 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_20.hpp
@@ -12,142 +12,142 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((a[9] * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((a[10] * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((a[11] * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((a[12] * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((a[13] * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((a[14] * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((((((a[15] * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + (((((((a[16] * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((((((((a[17] * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((((((((a[19] * x2 + a[17]) * x2 + a[15]) * x2 + a[13]) * x2 + a[11]) * x2 + a[9]) * x2 + a[7]) * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((((((((a[18] * x2 + a[16]) * x2 + a[14]) * x2 + a[12]) * x2 + a[10]) * x2 + a[8]) * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_3.hpp b/include/boost/math/tools/detail/polynomial_horner2_3.hpp
index b5956cdaf3..f9d6953b82 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_4.hpp b/include/boost/math/tools/detail/polynomial_horner2_4.hpp
index 9194a18682..8f11de5b31 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner2_5.hpp b/include/boost/math/tools/detail/polynomial_horner2_5.hpp
index 4e20c214a1..eba9ee9e6d 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_6.hpp b/include/boost/math/tools/detail/polynomial_horner2_6.hpp
index a33168d5ed..ef77c6255b 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_6.hpp
@@ -12,44 +12,44 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_7.hpp b/include/boost/math/tools/detail/polynomial_horner2_7.hpp
index 2f135756c5..fe8d21b95f 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_7.hpp
@@ -12,51 +12,51 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_8.hpp b/include/boost/math/tools/detail/polynomial_horner2_8.hpp
index 4c59602f9e..de1810a940 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_8.hpp
@@ -12,58 +12,58 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
diff --git a/include/boost/math/tools/detail/polynomial_horner2_9.hpp b/include/boost/math/tools/detail/polynomial_horner2_9.hpp
index 0b60c3c04d..5c53b73299 100644
--- a/include/boost/math/tools/detail/polynomial_horner2_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner2_9.hpp
@@ -12,65 +12,65 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((a[4] * x2 + a[2]) * x2 + a[0] + (a[3] * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[5] * x2 + a[3]) * x2 + a[1]) * x + (a[4] * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>(((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + ((a[5] * x2 + a[3]) * x2 + a[1]) * x);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x + ((a[6] * x2 + a[4]) * x2 + a[2]) * x2 + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    return static_cast<V>((((a[8] * x2 + a[6]) * x2 + a[4]) * x2 + a[2]) * x2 + a[0] + (((a[7] * x2 + a[5]) * x2 + a[3]) * x2 + a[1]) * x);
diff --git a/include/boost/math/tools/detail/polynomial_horner3_10.hpp b/include/boost/math/tools/detail/polynomial_horner3_10.hpp
index 3386fcae4f..7fb5bb4745 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_10.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_11.hpp b/include/boost/math/tools/detail/polynomial_horner3_11.hpp
index f24ebb0249..9f22820dea 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_11.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_12.hpp b/include/boost/math/tools/detail/polynomial_horner3_12.hpp
index 73916940d4..b049613766 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_12.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_13.hpp b/include/boost/math/tools/detail/polynomial_horner3_13.hpp
index 44ec9a84ce..f39a33cc90 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_13.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_14.hpp b/include/boost/math/tools/detail/polynomial_horner3_14.hpp
index 4d4e9e21c4..32b9e7db29 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_14.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_15.hpp b/include/boost/math/tools/detail/polynomial_horner3_15.hpp
index b7cf83dd11..55325c84b9 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_15.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_16.hpp b/include/boost/math/tools/detail/polynomial_horner3_16.hpp
index fbf504f3f6..f71d62f50c 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_16.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_17.hpp b/include/boost/math/tools/detail/polynomial_horner3_17.hpp
index c7af11b654..783a34558c 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_17.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_18.hpp b/include/boost/math/tools/detail/polynomial_horner3_18.hpp
index feceac694b..b10b270c41 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_18.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_19.hpp b/include/boost/math/tools/detail/polynomial_horner3_19.hpp
index 6a9a4ea6f0..21147591c8 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_19.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -406,7 +406,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_2.hpp b/include/boost/math/tools/detail/polynomial_horner3_2.hpp
index 69925be1cd..ee3e35e6ca 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_2.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_20.hpp b/include/boost/math/tools/detail/polynomial_horner3_20.hpp
index 8dda51139f..338aeb7dbc 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_20.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -127,7 +127,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -150,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -175,7 +175,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -231,7 +231,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -262,7 +262,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -295,7 +295,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -330,7 +330,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -367,7 +367,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -406,7 +406,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -447,7 +447,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_3.hpp b/include/boost/math/tools/detail/polynomial_horner3_3.hpp
index 30e68ac2a4..1eee0cfac0 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_3.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_4.hpp b/include/boost/math/tools/detail/polynomial_horner3_4.hpp
index e3c9b16f36..efa7fba485 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_4.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
diff --git a/include/boost/math/tools/detail/polynomial_horner3_5.hpp b/include/boost/math/tools/detail/polynomial_horner3_5.hpp
index c02467da08..f150e2a4a4 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_5.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_6.hpp b/include/boost/math/tools/detail/polynomial_horner3_6.hpp
index ad71255bf7..fe679e74d2 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_6.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_7.hpp b/include/boost/math/tools/detail/polynomial_horner3_7.hpp
index 31e0afa66a..76f080ad9c 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_7.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_8.hpp b/include/boost/math/tools/detail/polynomial_horner3_8.hpp
index 33121b204d..75634bdfc6 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_8.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/polynomial_horner3_9.hpp b/include/boost/math/tools/detail/polynomial_horner3_9.hpp
index c9f717133b..63a40580d1 100644
--- a/include/boost/math/tools/detail/polynomial_horner3_9.hpp
+++ b/include/boost/math/tools/detail/polynomial_horner3_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[1] * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[2] * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -55,7 +55,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -70,7 +70,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x
 }
 
 template <class T, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    V x2 = x * x;
    V t[2];
diff --git a/include/boost/math/tools/detail/rational_horner1_10.hpp b/include/boost/math/tools/detail/rational_horner1_10.hpp
index 346ac34ecc..e2f6c6d2fb 100644
--- a/include/boost/math/tools/detail/rational_horner1_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_10.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_11.hpp b/include/boost/math/tools/detail/rational_horner1_11.hpp
index 74ed24a744..31d480a65a 100644
--- a/include/boost/math/tools/detail/rational_horner1_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_11.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_12.hpp b/include/boost/math/tools/detail/rational_horner1_12.hpp
index 9072d1698b..c08a85b3a6 100644
--- a/include/boost/math/tools/detail/rational_horner1_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_12.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_13.hpp b/include/boost/math/tools/detail/rational_horner1_13.hpp
index 1e5c750926..cc87ec2dc7 100644
--- a/include/boost/math/tools/detail/rational_horner1_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_13.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_14.hpp b/include/boost/math/tools/detail/rational_horner1_14.hpp
index 75b9bde42c..256473710f 100644
--- a/include/boost/math/tools/detail/rational_horner1_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_14.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_15.hpp b/include/boost/math/tools/detail/rational_horner1_15.hpp
index 47f18a3c44..2ab24814e7 100644
--- a/include/boost/math/tools/detail/rational_horner1_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_15.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_16.hpp b/include/boost/math/tools/detail/rational_horner1_16.hpp
index fec9a51a2e..dce0b5e9b1 100644
--- a/include/boost/math/tools/detail/rational_horner1_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_16.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_17.hpp b/include/boost/math/tools/detail/rational_horner1_17.hpp
index b26dac95c6..8e875d6576 100644
--- a/include/boost/math/tools/detail/rational_horner1_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_17.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_18.hpp b/include/boost/math/tools/detail/rational_horner1_18.hpp
index 074a6359bb..ab67a970b0 100644
--- a/include/boost/math/tools/detail/rational_horner1_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_18.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_19.hpp b/include/boost/math/tools/detail/rational_horner1_19.hpp
index a1cceaeab8..dc300343a5 100644
--- a/include/boost/math/tools/detail/rational_horner1_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_19.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -228,7 +228,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((((b[18] * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_2.hpp b/include/boost/math/tools/detail/rational_horner1_2.hpp
index 81250ba10a..c6b1ef9ef9 100644
--- a/include/boost/math/tools/detail/rational_horner1_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_2.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_20.hpp b/include/boost/math/tools/detail/rational_horner1_20.hpp
index 63763fd8c9..5b8b170c15 100644
--- a/include/boost/math/tools/detail/rational_horner1_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_20.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -120,7 +120,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((a[9] * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((b[9] * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -132,7 +132,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((a[10] * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((b[10] * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -144,7 +144,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((a[11] * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((b[11] * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -156,7 +156,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((a[12] * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((b[12] * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -168,7 +168,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((a[13] * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((b[13] * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((a[14] * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((b[14] * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -192,7 +192,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((a[15] * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((b[15] * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -204,7 +204,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((a[16] * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((b[16] * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -216,7 +216,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((a[17] * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((b[17] * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -228,7 +228,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((((((((((((a[18] * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((((((((((((b[18] * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -240,7 +240,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((((((((((((((a[19] * x + a[18]) * x + a[17]) * x + a[16]) * x + a[15]) * x + a[14]) * x + a[13]) * x + a[12]) * x + a[11]) * x + a[10]) * x + a[9]) * x + a[8]) * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((((((((((((((b[19] * x + b[18]) * x + b[17]) * x + b[16]) * x + b[15]) * x + b[14]) * x + b[13]) * x + b[12]) * x + b[11]) * x + b[10]) * x + b[9]) * x + b[8]) * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_3.hpp b/include/boost/math/tools/detail/rational_horner1_3.hpp
index 1aebe20d31..6933e22bf1 100644
--- a/include/boost/math/tools/detail/rational_horner1_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_3.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_4.hpp b/include/boost/math/tools/detail/rational_horner1_4.hpp
index 8175f348cd..49b9835778 100644
--- a/include/boost/math/tools/detail/rational_horner1_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_4.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_5.hpp b/include/boost/math/tools/detail/rational_horner1_5.hpp
index 93c11c1ef3..91e97ff445 100644
--- a/include/boost/math/tools/detail/rational_horner1_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_5.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_6.hpp b/include/boost/math/tools/detail/rational_horner1_6.hpp
index a59cceb247..876b026cde 100644
--- a/include/boost/math/tools/detail/rational_horner1_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_6.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_7.hpp b/include/boost/math/tools/detail/rational_horner1_7.hpp
index eaa023a502..bcac18293c 100644
--- a/include/boost/math/tools/detail/rational_horner1_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_7.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_8.hpp b/include/boost/math/tools/detail/rational_horner1_8.hpp
index 5624c814f3..55e30a53e8 100644
--- a/include/boost/math/tools/detail/rational_horner1_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_8.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner1_9.hpp b/include/boost/math/tools/detail/rational_horner1_9.hpp
index c94e7ed421..c7087de508 100644
--- a/include/boost/math/tools/detail/rational_horner1_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner1_9.hpp
@@ -12,19 +12,19 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
@@ -36,7 +36,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
@@ -48,7 +48,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
@@ -60,7 +60,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((a[4] * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((b[4] * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -72,7 +72,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((a[5] * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((b[5] * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -84,7 +84,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((a[6] * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((b[6] * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -96,7 +96,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>((((((((a[7] * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / (((((((b[7] * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
@@ -108,7 +108,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
      return static_cast<V>(((((((((a[8] * x + a[7]) * x + a[6]) * x + a[5]) * x + a[4]) * x + a[3]) * x + a[2]) * x + a[1]) * x + a[0]) / ((((((((b[8] * x + b[7]) * x + b[6]) * x + b[5]) * x + b[4]) * x + b[3]) * x + b[2]) * x + b[1]) * x + b[0]));
diff --git a/include/boost/math/tools/detail/rational_horner2_10.hpp b/include/boost/math/tools/detail/rational_horner2_10.hpp
index 0e4fd54ead..4d74a714d5 100644
--- a/include/boost/math/tools/detail/rational_horner2_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_11.hpp b/include/boost/math/tools/detail/rational_horner2_11.hpp
index 841c8bd490..15f1cf2556 100644
--- a/include/boost/math/tools/detail/rational_horner2_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_12.hpp b/include/boost/math/tools/detail/rational_horner2_12.hpp
index 3e783c577c..24e9d9e7f7 100644
--- a/include/boost/math/tools/detail/rational_horner2_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_13.hpp b/include/boost/math/tools/detail/rational_horner2_13.hpp
index a3afa653d9..495f88525d 100644
--- a/include/boost/math/tools/detail/rational_horner2_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_14.hpp b/include/boost/math/tools/detail/rational_horner2_14.hpp
index 377c1ad42a..273e723b6c 100644
--- a/include/boost/math/tools/detail/rational_horner2_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_15.hpp b/include/boost/math/tools/detail/rational_horner2_15.hpp
index 9082d03f8b..c7e24ec7db 100644
--- a/include/boost/math/tools/detail/rational_horner2_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_16.hpp b/include/boost/math/tools/detail/rational_horner2_16.hpp
index 64173bffe0..2eebd702bc 100644
--- a/include/boost/math/tools/detail/rational_horner2_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_17.hpp b/include/boost/math/tools/detail/rational_horner2_17.hpp
index 5ae8cb4281..1fee63047f 100644
--- a/include/boost/math/tools/detail/rational_horner2_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_18.hpp b/include/boost/math/tools/detail/rational_horner2_18.hpp
index ebe440e62c..7aedbf2aad 100644
--- a/include/boost/math/tools/detail/rational_horner2_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_19.hpp b/include/boost/math/tools/detail/rational_horner2_19.hpp
index c1a2d43830..1c36a267cb 100644
--- a/include/boost/math/tools/detail/rational_horner2_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -266,7 +266,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_2.hpp b/include/boost/math/tools/detail/rational_horner2_2.hpp
index e1dd400ae4..bb2e2c4dcf 100644
--- a/include/boost/math/tools/detail/rational_horner2_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_20.hpp b/include/boost/math/tools/detail/rational_horner2_20.hpp
index 50a63c1287..a591b901c9 100644
--- a/include/boost/math/tools/detail/rational_horner2_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -122,7 +122,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -138,7 +138,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -154,7 +154,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -170,7 +170,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -186,7 +186,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -202,7 +202,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -218,7 +218,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -234,7 +234,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -250,7 +250,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -266,7 +266,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -282,7 +282,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_3.hpp b/include/boost/math/tools/detail/rational_horner2_3.hpp
index ab0d029aac..0b410d8bbe 100644
--- a/include/boost/math/tools/detail/rational_horner2_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_4.hpp b/include/boost/math/tools/detail/rational_horner2_4.hpp
index 147f5d1da6..07a9a2c5ad 100644
--- a/include/boost/math/tools/detail/rational_horner2_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner2_5.hpp b/include/boost/math/tools/detail/rational_horner2_5.hpp
index db5907b6fb..0933ddfbc4 100644
--- a/include/boost/math/tools/detail/rational_horner2_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_6.hpp b/include/boost/math/tools/detail/rational_horner2_6.hpp
index b71bc150a8..dee9c6e168 100644
--- a/include/boost/math/tools/detail/rational_horner2_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_7.hpp b/include/boost/math/tools/detail/rational_horner2_7.hpp
index da5b1476ac..6f9a85838c 100644
--- a/include/boost/math/tools/detail/rational_horner2_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_8.hpp b/include/boost/math/tools/detail/rational_horner2_8.hpp
index b047ad9486..33dda23bba 100644
--- a/include/boost/math/tools/detail/rational_horner2_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner2_9.hpp b/include/boost/math/tools/detail/rational_horner2_9.hpp
index 4eed1c4307..a9025a8900 100644
--- a/include/boost/math/tools/detail/rational_horner2_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner2_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -58,7 +58,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -74,7 +74,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -90,7 +90,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -106,7 +106,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_10.hpp b/include/boost/math/tools/detail/rational_horner3_10.hpp
index 1fe94f8e39..b7cec124e2 100644
--- a/include/boost/math/tools/detail/rational_horner3_10.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_10.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_11.hpp b/include/boost/math/tools/detail/rational_horner3_11.hpp
index 1a4277a82f..579f0e4868 100644
--- a/include/boost/math/tools/detail/rational_horner3_11.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_11.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_12.hpp b/include/boost/math/tools/detail/rational_horner3_12.hpp
index 5deb0f3743..54300dd08e 100644
--- a/include/boost/math/tools/detail/rational_horner3_12.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_12.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_13.hpp b/include/boost/math/tools/detail/rational_horner3_13.hpp
index 6c6857f31d..d2fc7b6331 100644
--- a/include/boost/math/tools/detail/rational_horner3_13.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_13.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_14.hpp b/include/boost/math/tools/detail/rational_horner3_14.hpp
index 1aadb35deb..0b7675f494 100644
--- a/include/boost/math/tools/detail/rational_horner3_14.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_14.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_15.hpp b/include/boost/math/tools/detail/rational_horner3_15.hpp
index 0f79e5b0dd..8286caed0b 100644
--- a/include/boost/math/tools/detail/rational_horner3_15.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_15.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_16.hpp b/include/boost/math/tools/detail/rational_horner3_16.hpp
index b7c6e96c1c..fc823e4162 100644
--- a/include/boost/math/tools/detail/rational_horner3_16.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_16.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_17.hpp b/include/boost/math/tools/detail/rational_horner3_17.hpp
index 25328e7ff9..cf7f75a706 100644
--- a/include/boost/math/tools/detail/rational_horner3_17.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_17.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_18.hpp b/include/boost/math/tools/detail/rational_horner3_18.hpp
index 335b895c48..f853ed3e0c 100644
--- a/include/boost/math/tools/detail/rational_horner3_18.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_18.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_19.hpp b/include/boost/math/tools/detail/rational_horner3_19.hpp
index 22d24403ef..d44e22c90b 100644
--- a/include/boost/math/tools/detail/rational_horner3_19.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_19.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1302,7 +1302,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_2.hpp b/include/boost/math/tools/detail/rational_horner3_2.hpp
index e1dd400ae4..bb2e2c4dcf 100644
--- a/include/boost/math/tools/detail/rational_horner3_2.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_2.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_20.hpp b/include/boost/math/tools/detail/rational_horner3_20.hpp
index f97124afb9..967edf0832 100644
--- a/include/boost/math/tools/detail/rational_horner3_20.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_20.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -312,7 +312,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 10>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -390,7 +390,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 11>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -476,7 +476,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 12>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -570,7 +570,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 13>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -672,7 +672,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 14>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -782,7 +782,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 15>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -900,7 +900,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 16>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1026,7 +1026,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 17>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1160,7 +1160,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 18>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1302,7 +1302,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 19>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -1452,7 +1452,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 20>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_3.hpp b/include/boost/math/tools/detail/rational_horner3_3.hpp
index ab0d029aac..0b410d8bbe 100644
--- a/include/boost/math/tools/detail/rational_horner3_3.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_3.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_4.hpp b/include/boost/math/tools/detail/rational_horner3_4.hpp
index 147f5d1da6..07a9a2c5ad 100644
--- a/include/boost/math/tools/detail/rational_horner3_4.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_4.hpp
@@ -12,31 +12,31 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
diff --git a/include/boost/math/tools/detail/rational_horner3_5.hpp b/include/boost/math/tools/detail/rational_horner3_5.hpp
index af1c76f1c6..62c76dd506 100644
--- a/include/boost/math/tools/detail/rational_horner3_5.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_5.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_6.hpp b/include/boost/math/tools/detail/rational_horner3_6.hpp
index 05d626ac8a..f81a068acb 100644
--- a/include/boost/math/tools/detail/rational_horner3_6.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_6.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_7.hpp b/include/boost/math/tools/detail/rational_horner3_7.hpp
index 2d91a5c501..fea457ccf8 100644
--- a/include/boost/math/tools/detail/rational_horner3_7.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_7.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_8.hpp b/include/boost/math/tools/detail/rational_horner3_8.hpp
index 3a6ea4ff09..306e2a41d9 100644
--- a/include/boost/math/tools/detail/rational_horner3_8.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_8.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/detail/rational_horner3_9.hpp b/include/boost/math/tools/detail/rational_horner3_9.hpp
index d20149b22f..93a3527c18 100644
--- a/include/boost/math/tools/detail/rational_horner3_9.hpp
+++ b/include/boost/math/tools/detail/rational_horner3_9.hpp
@@ -12,37 +12,37 @@
 namespace boost{ namespace math{ namespace tools{ namespace detail{
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(0);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(a[0]) / static_cast<V>(b[0]);
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*) BOOST_MATH_NOEXCEPT(V)
 {
    return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 5>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -80,7 +80,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 6>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -126,7 +126,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 7>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -180,7 +180,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 8>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
@@ -242,7 +242,7 @@ BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b,
 }
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 9>*) BOOST_MATH_NOEXCEPT(V)
 {
    if((-1 <= x) && (x <= 1))
    {
diff --git a/include/boost/math/tools/rational.hpp b/include/boost/math/tools/rational.hpp
index b65700f623..e3c3e7e338 100644
--- a/include/boost/math/tools/rational.hpp
+++ b/include/boost/math/tools/rational.hpp
@@ -10,9 +10,13 @@
 #pragma once
 #endif
 
-#include <array>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/type_traits.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <array>
+#endif
 
 #if BOOST_MATH_POLY_METHOD == 1
 #  define BOOST_HEADER() <BOOST_MATH_JOIN(boost/math/tools/detail/polynomial_horner1_, BOOST_MATH_MAX_POLY_ORDER).hpp>
@@ -168,7 +172,7 @@ namespace boost{ namespace math{ namespace tools{
 // Forward declaration to keep two phase lookup happy:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U);
+BOOST_MATH_GPU_ENABLED U evaluate_polynomial(const T* poly, U const& z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U);
 
 namespace detail{
 
@@ -186,7 +190,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp
 // the loop expanded versions above:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
 {
    BOOST_MATH_ASSERT(count > 0);
    U sum = static_cast<U>(poly[count - 1]);
@@ -201,64 +205,70 @@ BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, s
 // Compile time sized polynomials, just inline forwarders to the
 // implementations above:
 //
-template <std::size_t N, class T, class V>
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const T(&a)[N], const V& val) BOOST_MATH_NOEXCEPT(V)
 {
-   typedef std::integral_constant<int, N> tag_type;
+   typedef boost::math::integral_constant<int, N> tag_type;
    return detail::evaluate_polynomial_c_imp(static_cast<const T*>(a), val, static_cast<tag_type const*>(nullptr));
 }
 
-template <std::size_t N, class T, class V>
+#ifndef BOOST_MATH_HAS_NVRTC
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const std::array<T,N>& a, const V& val) BOOST_MATH_NOEXCEPT(V)
 {
-   typedef std::integral_constant<int, N> tag_type;
+   typedef boost::math::integral_constant<int, N> tag_type;
    return detail::evaluate_polynomial_c_imp(static_cast<const T*>(a.data()), val, static_cast<tag_type const*>(nullptr));
 }
+#endif
 //
 // Even polynomials are trivial: just square the argument!
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_even_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_even_polynomial(const T* poly, U z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
 {
    return evaluate_polynomial(poly, U(z*z), count);
 }
 
-template <std::size_t N, class T, class V>
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
 }
 
-template <std::size_t N, class T, class V>
+#ifndef BOOST_MATH_HAS_NVRTC
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
 }
+#endif
 //
 // Odd polynomials come next:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_odd_polynomial(const T* poly, U z, std::size_t count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_odd_polynomial(const T* poly, U z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
 {
    return poly[0] + z * evaluate_polynomial(poly+1, U(z*z), count-1);
 }
 
-template <std::size_t N, class T, class V>
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
-   typedef std::integral_constant<int, N-1> tag_type;
+   typedef boost::math::integral_constant<int, N-1> tag_type;
    return a[0] + z * detail::evaluate_polynomial_c_imp(static_cast<const T*>(a) + 1, V(z*z), static_cast<tag_type const*>(nullptr));
 }
 
-template <std::size_t N, class T, class V>
+#ifndef BOOST_MATH_HAS_NVRTC
+template <BOOST_MATH_SIZE_T N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
-   typedef std::integral_constant<int, N-1> tag_type;
+   typedef boost::math::integral_constant<int, N-1> tag_type;
    return a[0] + z * detail::evaluate_polynomial_c_imp(static_cast<const T*>(a.data()) + 1, V(z*z), static_cast<tag_type const*>(nullptr));
 }
+#endif
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V);
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(V);
 
 namespace detail{
 
@@ -278,7 +288,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(c
 // in our Lanczos code for example.
 //
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, std::size_t count) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(V)
 {
    V z(z_);
    V s1, s2;
@@ -310,17 +320,19 @@ BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V
    return s1 / s2;
 }
 
-template <std::size_t N, class T, class U, class V>
+template <BOOST_MATH_SIZE_T N, class T, class U, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const T(&a)[N], const U(&b)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
-   return detail::evaluate_rational_c_imp(a, b, z, static_cast<const std::integral_constant<int, N>*>(nullptr));
+   return detail::evaluate_rational_c_imp(a, b, z, static_cast<const boost::math::integral_constant<int, N>*>(nullptr));
 }
 
-template <std::size_t N, class T, class U, class V>
+#ifndef BOOST_MATH_HAS_NVRTC
+template <BOOST_MATH_SIZE_T N, class T, class U, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const std::array<T,N>& a, const std::array<U,N>& b, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
-   return detail::evaluate_rational_c_imp(a.data(), b.data(), z, static_cast<std::integral_constant<int, N>*>(nullptr));
+   return detail::evaluate_rational_c_imp(a.data(), b.data(), z, static_cast<boost::math::integral_constant<int, N>*>(nullptr));
 }
+#endif
 
 } // namespace tools
 } // namespace math
diff --git a/tools/generate_rational_code.cpp b/tools/generate_rational_code.cpp
index 92b7da9a10..20ffde8503 100644
--- a/tools/generate_rational_code.cpp
+++ b/tools/generate_rational_code.cpp
@@ -40,13 +40,13 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n";
@@ -55,7 +55,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   return static_cast<V>(";
          
@@ -90,28 +90,28 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>(a[1] * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>((a[2] * x + a[1]) * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);\n"
          "}\n\n";
@@ -120,7 +120,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   V x2 = x * x;\n"
          "   return static_cast<V>(";
@@ -186,28 +186,28 @@ void print_polynomials(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>(a[1] * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>((a[2] * x + a[1]) * x + a[0]);\n"
          "}\n\n"
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>(((a[3] * x + a[2]) * x + a[1]) * x + a[0]);\n"
          "}\n\n";
@@ -216,7 +216,7 @@ void print_polynomials(int max_order)
       {
          ofs << 
          "template <class T, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp(const T* a, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   V x2 = x * x;\n"
          "   V t[2];\n";
@@ -281,13 +281,13 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_POLY_RAT_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n";
@@ -296,7 +296,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n"
          "     return static_cast<V>((";
@@ -361,28 +361,28 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_RAT_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));\n"
          "}\n\n";
@@ -391,7 +391,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n   {\n"
          "      V x2 = x * x;\n"
@@ -577,28 +577,28 @@ void print_rationals(int max_order)
          "#define BOOST_MATH_TOOLS_RAT_EVAL_" << i << "_HPP\n\n"
          "namespace boost{ namespace math{ namespace tools{ namespace detail{\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const std::integral_constant<int, 0>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T*, const U*, const V&, const boost::math::integral_constant<int, 0>*)\n"
          "{\n"
          "   return static_cast<V>(0);\n"
          "}\n"
          "\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const std::integral_constant<int, 1>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V&, const boost::math::integral_constant<int, 1>*)\n"
          "{\n"
          "   return static_cast<V>(a[0]) / static_cast<V>(b[0]);\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 2>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 2>*)\n"
          "{\n"
          "   return static_cast<V>((a[1] * x + a[0]) / (b[1] * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 3>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 3>*)\n"
          "{\n"
          "   return static_cast<V>(((a[2] * x + a[1]) * x + a[0]) / ((b[2] * x + b[1]) * x + b[0]));\n"
          "}\n\n"
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, 4>*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, 4>*)\n"
          "{\n"
          "   return static_cast<V>((((a[3] * x + a[2]) * x + a[1]) * x + a[0]) / (((b[3] * x + b[2]) * x + b[1]) * x + b[0]));\n"
          "}\n\n";
@@ -607,7 +607,7 @@ void print_rationals(int max_order)
       {
          ofs << 
          "template <class T, class U, class V>\n"
-         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const std::integral_constant<int, " << order << ">*)\n"
+         "BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(const T* a, const U* b, const V& x, const boost::math::integral_constant<int, " << order << ">*)\n"
          "{\n"
          "   if((-1 <= x) && (x <= 1))\n   {\n"
          "      V x2 = x * x;\n"

From 68e73ad2dc8bacba89d3b339f731d3951386e7bc Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:16:42 -0400
Subject: [PATCH 295/399] Add GPU definition of assertions

---
 include/boost/math/tools/assert.hpp | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/assert.hpp b/include/boost/math/tools/assert.hpp
index 3d5655923a..3f57351fc1 100644
--- a/include/boost/math/tools/assert.hpp
+++ b/include/boost/math/tools/assert.hpp
@@ -10,6 +10,19 @@
 #ifndef BOOST_MATH_TOOLS_ASSERT_HPP
 #define BOOST_MATH_TOOLS_ASSERT_HPP
 
+#include <boost/math/tools/config.hpp>
+
+#ifdef BOOST_MATH_HAS_GPU_SUPPORT
+
+// Run time asserts are generally unsupported
+
+#define BOOST_MATH_ASSERT(expr)
+#define BOOST_MATH_ASSERT_MSG(expr, msg)
+#define BOOST_MATH_STATIC_ASSERT(expr) static_assert(expr, #expr " failed")
+#define BOOST_MATH_STATIC_ASSERT_MSG(expr, msg) static_assert(expr, msg)
+
+#else
+
 #include <boost/math/tools/is_standalone.hpp>
 
 #ifndef BOOST_MATH_STANDALONE
@@ -29,6 +42,8 @@
 #define BOOST_MATH_STATIC_ASSERT(expr) static_assert(expr, #expr " failed")
 #define BOOST_MATH_STATIC_ASSERT_MSG(expr, msg) static_assert(expr, msg)
 
-#endif
+#endif // Is standalone
+
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 #endif // BOOST_MATH_TOOLS_ASSERT_HPP

From 0b403b70eebd69f9285aaa94739a6861b7165b9c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:37:51 -0400
Subject: [PATCH 296/399] Apply promotion changes from
 https://github.com/boostorg/math/pull/1022

---
 include/boost/math/tools/promotion.hpp | 318 ++++++-------------------
 1 file changed, 71 insertions(+), 247 deletions(-)

diff --git a/include/boost/math/tools/promotion.hpp b/include/boost/math/tools/promotion.hpp
index c117e9575d..a65f3703f4 100644
--- a/include/boost/math/tools/promotion.hpp
+++ b/include/boost/math/tools/promotion.hpp
@@ -3,6 +3,7 @@
 // Copyright John Maddock 2006.
 // Copyright Paul A. Bristow 2006.
 // Copyright Matt Borland 2023.
+// Copyright Ryan Elandt 2023.
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -24,15 +25,7 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-#include <type_traits>
-
-#if defined __has_include
-#  if __cplusplus > 202002L || (defined(_MSVC_LANG) && _MSVC_LANG > 202002L)
-#    if __has_include (<stdfloat>)
-#    include <stdfloat>
-#    endif
-#  endif
-#endif
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost
 {
@@ -40,272 +33,103 @@ namespace boost
   {
     namespace tools
     {
+      ///// This promotion system works as follows:
+      // 
+      // Rule<T1> (one argument promotion rule):
+      //   - Promotes `T` to `double` if `T` is an integer type as identified by
+      //     `std::is_integral`, otherwise is `T`
+      //
+      // Rule<T1, T2_to_TN...> (two or more argument promotion rule):
+      //   - 1. Calculates type using applying Rule<T1>.
+      //   - 2. Calculates type using applying Rule<T2_to_TN...> 
+      //   - If the type calculated in 1 and 2 are both floating point types, as
+      //     identified by `std::is_floating_point`, then return the type
+      //     determined by `std::common_type`. Otherwise return the type using
+      //     an asymmetric convertibility rule.
+      //
+      ///// Discussion:
+      //
       // If either T1 or T2 is an integer type,
       // pretend it was a double (for the purposes of further analysis).
       // Then pick the wider of the two floating-point types
       // as the actual signature to forward to.
       // For example:
-      // foo(int, short) -> double foo(double, double);
-      // foo(int, float) -> double foo(double, double);
-      // Note: NOT float foo(float, float)
-      // foo(int, double) -> foo(double, double);
-      // foo(double, float) -> double foo(double, double);
-      // foo(double, float) -> double foo(double, double);
-      // foo(any-int-or-float-type, long double) -> foo(long double, long double);
-      // but ONLY float foo(float, float) is unchanged.
-      // So the only way to get an entirely float version is to call foo(1.F, 2.F),
-      // But since most (all?) the math functions convert to double internally,
-      // probably there would not be the hoped-for gain by using float here.
-
+      //    foo(int, short) -> double foo(double, double);  // ***NOT*** float foo(float, float)
+      //    foo(int, float) -> double foo(double, double);  // ***NOT*** float foo(float, float)
+      //    foo(int, double) -> foo(double, double);
+      //    foo(double, float) -> double foo(double, double);
+      //    foo(double, float) -> double foo(double, double);
+      //    foo(any-int-or-float-type, long double) -> foo(long double, long double);
+      // ONLY float foo(float, float) is unchanged, so the only way to get an
+      // entirely float version is to call foo(1.F, 2.F). But since most (all?) the
+      // math functions convert to double internally, probably there would not be the
+      // hoped-for gain by using float here.
+      //
       // This follows the C-compatible conversion rules of pow, etc
       // where pow(int, float) is converted to pow(double, double).
 
+
+      // Promotes a single argument to double if it is an integer type
       template <class T>
-      struct promote_arg
-      { // If T is integral type, then promote to double.
-        using type = typename std::conditional<std::is_integral<T>::value, double, T>::type;
+      struct promote_arg {
+         using type = typename boost::math::conditional<boost::math::is_integral<T>::value, double, T>::type;
       };
-      // These full specialisations reduce std::conditional usage and speed up
-      // compilation:
-      template <> struct promote_arg<float> { using type = float; };
-      template <> struct promote_arg<double>{ using type = double; };
-      template <> struct promote_arg<long double> { using type = long double; };
-      template <> struct promote_arg<int> {  using type = double; };
 
-      #ifdef __STDCPP_FLOAT16_T__
-      template <> struct promote_arg<std::float16_t> { using type = std::float16_t; };
-      #endif
-      #ifdef __STDCPP_FLOAT32_T__
-      template <> struct promote_arg<std::float32_t> { using type = std::float32_t; };
-      #endif
-      #ifdef __STDCPP_FLOAT64_T__
-      template <> struct promote_arg<std::float64_t> { using type = std::float64_t; };
-      #endif
-      #ifdef __STDCPP_FLOAT128_T__
-      template <> struct promote_arg<std::float128_t> { using type = std::float128_t; };
-      #endif
-
-      template <typename T>
-      using promote_arg_t = typename promote_arg<T>::type;
 
+      // Promotes two arguments, neither of which is an integer type using an asymmetric
+      // convertibility rule.
+      template <class T1, class T2, bool = (boost::math::is_floating_point<T1>::value && boost::math::is_floating_point<T2>::value)>
+      struct pa2_integral_already_removed {
+         using type = typename boost::math::conditional<
+            !boost::math::is_floating_point<T2>::value && boost::math::is_convertible<T1, T2>::value, 
+            T2, T1>::type;
+      };
+      // For two floating point types, promotes using `std::common_type` functionality 
       template <class T1, class T2>
-      struct promote_args_2
-      { // Promote, if necessary, & pick the wider of the two floating-point types.
-        // for both parameter types, if integral promote to double.
-        using T1P = typename promote_arg<T1>::type; // T1 perhaps promoted.
-        using T2P = typename promote_arg<T2>::type; // T2 perhaps promoted.
-        using intermediate_type = typename std::conditional<
-          std::is_floating_point<T1P>::value && std::is_floating_point<T2P>::value, // both T1P and T2P are floating-point?
-#ifdef __STDCPP_FLOAT128_T__
-           typename std::conditional<std::is_same<std::float128_t, T1P>::value || std::is_same<std::float128_t, T2P>::value, // either long double?
-            std::float128_t,
-#endif 
-#ifdef BOOST_MATH_USE_FLOAT128
-           typename std::conditional<std::is_same<__float128, T1P>::value || std::is_same<__float128, T2P>::value, // either long double?
-            __float128,
-#endif 
-             typename std::conditional<std::is_same<long double, T1P>::value || std::is_same<long double, T2P>::value, // either long double?
-               long double, // then result type is long double.
-#ifdef __STDCPP_FLOAT64_T__
-             typename std::conditional<std::is_same<std::float64_t, T1P>::value || std::is_same<std::float64_t, T2P>::value, // either float64?
-               std::float64_t, // then result type is float64_t.
-#endif
-               typename std::conditional<std::is_same<double, T1P>::value || std::is_same<double, T2P>::value, // either double?
-                  double, // result type is double.
-#ifdef __STDCPP_FLOAT32_T__
-             typename std::conditional<std::is_same<std::float32_t, T1P>::value || std::is_same<std::float32_t, T2P>::value, // either float32?
-               std::float32_t, // then result type is float32_t.
-#endif
-                  float // else result type is float.
-             >::type
-#ifdef BOOST_MATH_USE_FLOAT128
-             >::type
-#endif
-#ifdef __STDCPP_FLOAT128_T__
-             >::type
-#endif
-#ifdef __STDCPP_FLOAT64_T__
-             >::type
-#endif
-#ifdef __STDCPP_FLOAT32_T__
-             >::type
-#endif
-             >::type,
-          // else one or the other is a user-defined type:
-          typename std::conditional<!std::is_floating_point<T2P>::value && std::is_convertible<T1P, T2P>::value, T2P, T1P>::type>::type;
-
-#ifdef __STDCPP_FLOAT64_T__
-          // If long doubles are doubles then we should prefer to use std::float64_t when available
-          using type = std::conditional_t<(sizeof(double) == sizeof(long double) && std::is_same<intermediate_type, long double>::value), std::float64_t, intermediate_type>;
-#else
-          using type = intermediate_type;
-#endif
-      }; // promote_arg2
-      // These full specialisations reduce std::conditional usage and speed up
-      // compilation:
-      template <> struct promote_args_2<float, float> { using type = float; };
-      template <> struct promote_args_2<double, double>{ using type = double; };
-      template <> struct promote_args_2<long double, long double> { using type = long double; };
-      template <> struct promote_args_2<int, int> {  using type = double; };
-      template <> struct promote_args_2<int, float> {  using type = double; };
-      template <> struct promote_args_2<float, int> {  using type = double; };
-      template <> struct promote_args_2<int, double> {  using type = double; };
-      template <> struct promote_args_2<double, int> {  using type = double; };
-      template <> struct promote_args_2<int, long double> {  using type = long double; };
-      template <> struct promote_args_2<long double, int> {  using type = long double; };
-      template <> struct promote_args_2<float, double> {  using type = double; };
-      template <> struct promote_args_2<double, float> {  using type = double; };
-      template <> struct promote_args_2<float, long double> {  using type = long double; };
-      template <> struct promote_args_2<long double, float> {  using type = long double; };
-      template <> struct promote_args_2<double, long double> {  using type = long double; };
-      template <> struct promote_args_2<long double, double> {  using type = long double; };
-
-      #ifdef __STDCPP_FLOAT128_T__
-      template <> struct promote_args_2<int, std::float128_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float128_t, int> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float128_t, float> { using type = std::float128_t; };
-      template <> struct promote_args_2<float, std::float128_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float128_t, double> { using type = std::float128_t; };
-      template <> struct promote_args_2<double, std::float128_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float128_t, long double> { using type = std::float128_t; };
-      template <> struct promote_args_2<long double, std::float128_t> { using type = std::float128_t; };
-
-      #ifdef __STDCPP_FLOAT16_T__
-      template <> struct promote_args_2<std::float128_t, std::float16_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float16_t, std::float128_t> { using type = std::float128_t; };
-      #endif
-
-      #ifdef __STDCPP_FLOAT32_T__
-      template <> struct promote_args_2<std::float128_t, std::float32_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float32_t, std::float128_t> { using type = std::float128_t; };
-      #endif
-
-      #ifdef __STDCPP_FLOAT64_T__
-      template <> struct promote_args_2<std::float128_t, std::float64_t> { using type = std::float128_t; };
-      template <> struct promote_args_2<std::float64_t, std::float128_t> { using type = std::float128_t; };
-      #endif
-
-      template <> struct promote_args_2<std::float128_t, std::float128_t> { using type = std::float128_t; };
-      #endif
-
-      #ifdef __STDCPP_FLOAT64_T__
-      template <> struct promote_args_2<int, std::float64_t> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float64_t, int> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float64_t, float> { using type = std::float64_t; };
-      template <> struct promote_args_2<float, std::float64_t> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float64_t, double> { using type = std::float64_t; };
-      template <> struct promote_args_2<double, std::float64_t> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float64_t, long double> { using type = long double; };
-      template <> struct promote_args_2<long double, std::float64_t> { using type = long double; };
-
-      #ifdef __STDCPP_FLOAT16_T__
-      template <> struct promote_args_2<std::float64_t, std::float16_t> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float16_t, std::float64_t> { using type = std::float64_t; };
-      #endif
-
-      #ifdef __STDCPP_FLOAT32_T__
-      template <> struct promote_args_2<std::float64_t, std::float32_t> { using type = std::float64_t; };
-      template <> struct promote_args_2<std::float32_t, std::float64_t> { using type = std::float64_t; };
-      #endif
-
-      template <> struct promote_args_2<std::float64_t, std::float64_t> { using type = std::float64_t; };
-      #endif
-
-      #ifdef __STDCPP_FLOAT32_T__
-      template <> struct promote_args_2<int, std::float32_t> { using type = std::float32_t; };
-      template <> struct promote_args_2<std::float32_t, int> { using type = std::float32_t; };
-      template <> struct promote_args_2<std::float32_t, float> { using type = std::float32_t; };
-      template <> struct promote_args_2<float, std::float32_t> { using type = std::float32_t; };
-      template <> struct promote_args_2<std::float32_t, double> { using type = double; };
-      template <> struct promote_args_2<double, std::float32_t> { using type = double; };
-      template <> struct promote_args_2<std::float32_t, long double> { using type = long double; };
-      template <> struct promote_args_2<long double, std::float32_t> { using type = long double; };
-
-      #ifdef __STDCPP_FLOAT16_T__
-      template <> struct promote_args_2<std::float32_t, std::float16_t> { using type = std::float32_t; };
-      template <> struct promote_args_2<std::float16_t, std::float32_t> { using type = std::float32_t; };
-      #endif
-
-      template <> struct promote_args_2<std::float32_t, std::float32_t> { using type = std::float32_t; };
-      #endif
+      struct pa2_integral_already_removed<T1, T2, true> {
+         using type = boost::math::common_type_t<T1, T2, float>;
+      };
 
-      #ifdef __STDCPP_FLOAT16_T__
-      template <> struct promote_args_2<int, std::float16_t> { using type = std::float16_t; };
-      template <> struct promote_args_2<std::float16_t, int> { using type = std::float16_t; };
-      template <> struct promote_args_2<std::float16_t, float> { using type = float; };
-      template <> struct promote_args_2<float, std::float16_t> { using type = float; };
-      template <> struct promote_args_2<std::float16_t, double> { using type = double; };
-      template <> struct promote_args_2<double, std::float16_t> { using type = double; };
-      template <> struct promote_args_2<std::float16_t, long double> { using type = long double; };
-      template <> struct promote_args_2<long double, std::float16_t> { using type = long double; };
 
-      template <> struct promote_args_2<std::float16_t, std::float16_t> { using type = std::float16_t; };
-      #endif
+      // Template definition for promote_args_permissive
+      template <typename... Args>
+      struct promote_args_permissive;
+      // Specialization for one argument
+      template <typename T>
+      struct promote_args_permissive<T> {
+         using type = typename promote_arg<typename boost::math::remove_cv<T>::type>::type;
+      };
+      // Specialization for two or more arguments
+      template <typename T1, typename... T2_to_TN>
+      struct promote_args_permissive<T1, T2_to_TN...> {
+         using type = typename pa2_integral_already_removed<
+                  typename promote_args_permissive<T1>::type,
+                  typename promote_args_permissive<T2_to_TN...>::type
+               >::type;
+      };
 
-      template <typename T, typename U>
-      using promote_args_2_t = typename promote_args_2<T, U>::type;
+      template <class... Args>
+      using promote_args_permissive_t = typename promote_args_permissive<Args...>::type;
 
-      template <class T1, class T2=float, class T3=float, class T4=float, class T5=float, class T6=float>
-      struct promote_args
-      {
-         using type = typename promote_args_2<
-            typename std::remove_cv<T1>::type,
-            typename promote_args_2<
-               typename std::remove_cv<T2>::type,
-               typename promote_args_2<
-                  typename std::remove_cv<T3>::type,
-                  typename promote_args_2<
-                     typename std::remove_cv<T4>::type,
-                     typename promote_args_2<
-                        typename std::remove_cv<T5>::type, typename std::remove_cv<T6>::type
-                     >::type
-                  >::type
-               >::type
-            >::type
-         >::type;
 
+      // Same as `promote_args_permissive` but with a static assertion that the promoted type
+      // is not `long double` if `BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS` is defined
+      template <class... Args>
+      struct promote_args {
+         using type = typename promote_args_permissive<Args...>::type;
 #if defined(BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS)
          //
          // Guard against use of long double if it's not supported:
          //
-         static_assert((0 == std::is_same<type, long double>::value), "Sorry, but this platform does not have sufficient long double support for the special functions to be reliably implemented.");
+         static_assert((0 == boost::math::is_same<type, long double>::value), "Sorry, but this platform does not have sufficient long double support for the special functions to be reliably implemented.");
 #endif
       };
 
-      template <class T1, class T2=float, class T3=float, class T4=float, class T5=float, class T6=float>
-      using promote_args_t = typename promote_args<T1, T2, T3, T4, T5, T6>::type;
-
-      //
-      // This struct is the same as above, but has no static assert on long double usage,
-      // it should be used only on functions that can be implemented for long double
-      // even when std lib support is missing or broken for that type.
-      //
-      template <class T1, class T2=float, class T3=float, class T4=float, class T5=float, class T6=float>
-      struct promote_args_permissive
-      {
-         using type = typename promote_args_2<
-            typename std::remove_cv<T1>::type,
-            typename promote_args_2<
-               typename std::remove_cv<T2>::type,
-               typename promote_args_2<
-                  typename std::remove_cv<T3>::type,
-                  typename promote_args_2<
-                     typename std::remove_cv<T4>::type,
-                     typename promote_args_2<
-                        typename std::remove_cv<T5>::type, typename std::remove_cv<T6>::type
-                     >::type
-                  >::type
-               >::type
-            >::type
-         >::type;
-      };
-
-      template <class T1, class T2=float, class T3=float, class T4=float, class T5=float, class T6=float>
-      using promote_args_permissive_t = typename promote_args_permissive<T1, T2, T3, T4, T5, T6>::type;
+      template <class... Args>
+      using promote_args_t = typename promote_args<Args...>::type;
 
     } // namespace tools
   } // namespace math
 } // namespace boost
 
 #endif // BOOST_MATH_PROMOTION_HPP
-

From 494f2f2dc96fcf0009454a04111559f9cdc05f8b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:38:07 -0400
Subject: [PATCH 297/399] Fix old promotion args

---
 include/boost/math/ccmath/copysign.hpp          |  2 +-
 include/boost/math/ccmath/fdim.hpp              |  2 +-
 include/boost/math/ccmath/fmax.hpp              |  2 +-
 include/boost/math/ccmath/fmin.hpp              |  2 +-
 include/boost/math/ccmath/hypot.hpp             |  2 +-
 include/boost/math/differentiation/autodiff.hpp | 14 +++++++-------
 6 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/ccmath/copysign.hpp b/include/boost/math/ccmath/copysign.hpp
index 90a58102b1..e117e57faa 100644
--- a/include/boost/math/ccmath/copysign.hpp
+++ b/include/boost/math/ccmath/copysign.hpp
@@ -54,7 +54,7 @@ constexpr auto copysign(T1 mag, T2 sgn) noexcept
 {
     if (BOOST_MATH_IS_CONSTANT_EVALUATED(mag))
     {        
-        using promoted_type = boost::math::tools::promote_args_2_t<T1, T2>;
+        using promoted_type = boost::math::tools::promote_args_t<T1, T2>;
         return boost::math::ccmath::copysign(static_cast<promoted_type>(mag), static_cast<promoted_type>(sgn));
     }
     else
diff --git a/include/boost/math/ccmath/fdim.hpp b/include/boost/math/ccmath/fdim.hpp
index cdcbc223c6..d6b4e25cec 100644
--- a/include/boost/math/ccmath/fdim.hpp
+++ b/include/boost/math/ccmath/fdim.hpp
@@ -66,7 +66,7 @@ constexpr auto fdim(T1 x, T2 y) noexcept
 {
     if (BOOST_MATH_IS_CONSTANT_EVALUATED(x))
     {
-        using promoted_type = boost::math::tools::promote_args_2_t<T1, T2>;
+        using promoted_type = boost::math::tools::promote_args_t<T1, T2>;
         return boost::math::ccmath::fdim(promoted_type(x), promoted_type(y));
     }
     else
diff --git a/include/boost/math/ccmath/fmax.hpp b/include/boost/math/ccmath/fmax.hpp
index 237355275b..8a0d17d03e 100644
--- a/include/boost/math/ccmath/fmax.hpp
+++ b/include/boost/math/ccmath/fmax.hpp
@@ -62,7 +62,7 @@ constexpr auto fmax(T1 x, T2 y) noexcept
 {
     if (BOOST_MATH_IS_CONSTANT_EVALUATED(x))
     {
-        using promoted_type = boost::math::tools::promote_args_2_t<T1, T2>;
+        using promoted_type = boost::math::tools::promote_args_t<T1, T2>;
         return boost::math::ccmath::fmax(static_cast<promoted_type>(x), static_cast<promoted_type>(y));
     }
     else
diff --git a/include/boost/math/ccmath/fmin.hpp b/include/boost/math/ccmath/fmin.hpp
index 1c113e0d6e..29885b69c8 100644
--- a/include/boost/math/ccmath/fmin.hpp
+++ b/include/boost/math/ccmath/fmin.hpp
@@ -62,7 +62,7 @@ constexpr auto fmin(T1 x, T2 y) noexcept
 {
     if (BOOST_MATH_IS_CONSTANT_EVALUATED(x))
     {
-        using promoted_type = boost::math::tools::promote_args_2_t<T1, T2>;
+        using promoted_type = boost::math::tools::promote_args_t<T1, T2>;
         return boost::math::ccmath::fmin(static_cast<promoted_type>(x), static_cast<promoted_type>(y));
     }
     else
diff --git a/include/boost/math/ccmath/hypot.hpp b/include/boost/math/ccmath/hypot.hpp
index 4e0e245b4e..34dd5ab2c0 100644
--- a/include/boost/math/ccmath/hypot.hpp
+++ b/include/boost/math/ccmath/hypot.hpp
@@ -89,7 +89,7 @@ constexpr auto hypot(T1 x, T2 y) noexcept
 {
     if(BOOST_MATH_IS_CONSTANT_EVALUATED(x))
     {
-        using promoted_type = boost::math::tools::promote_args_2_t<T1, T2>;
+        using promoted_type = boost::math::tools::promote_args_t<T1, T2>;
         return boost::math::ccmath::hypot(static_cast<promoted_type>(x), static_cast<promoted_type>(y));
     }
     else
diff --git a/include/boost/math/differentiation/autodiff.hpp b/include/boost/math/differentiation/autodiff.hpp
index 7a57aa2f92..b8880f24de 100644
--- a/include/boost/math/differentiation/autodiff.hpp
+++ b/include/boost/math/differentiation/autodiff.hpp
@@ -39,7 +39,7 @@ namespace detail {
 
 template <typename RealType, typename... RealTypes>
 struct promote_args_n {
-  using type = typename tools::promote_args_2<RealType, typename promote_args_n<RealTypes...>::type>::type;
+  using type = typename tools::promote_args<RealType, typename promote_args_n<RealTypes...>::type>::type;
 };
 
 template <typename RealType>
@@ -2002,9 +2002,9 @@ using autodiff_root_type = typename autodiff_fvar_type<RealType, Order>::root_ty
 
 // See boost/math/tools/promotion.hpp
 template <typename RealType0, size_t Order0, typename RealType1, size_t Order1>
-struct promote_args_2<detail::autodiff_fvar_type<RealType0, Order0>,
+struct promote_args<detail::autodiff_fvar_type<RealType0, Order0>,
                       detail::autodiff_fvar_type<RealType1, Order1>> {
-  using type = detail::autodiff_fvar_type<typename promote_args_2<RealType0, RealType1>::type,
+  using type = detail::autodiff_fvar_type<typename promote_args<RealType0, RealType1>::type,
 #ifndef BOOST_MATH_NO_CXX14_CONSTEXPR
                                           (std::max)(Order0, Order1)>;
 #else
@@ -2018,13 +2018,13 @@ struct promote_args<detail::autodiff_fvar_type<RealType, Order>> {
 };
 
 template <typename RealType0, size_t Order0, typename RealType1>
-struct promote_args_2<detail::autodiff_fvar_type<RealType0, Order0>, RealType1> {
-  using type = detail::autodiff_fvar_type<typename promote_args_2<RealType0, RealType1>::type, Order0>;
+struct promote_args<detail::autodiff_fvar_type<RealType0, Order0>, RealType1> {
+  using type = detail::autodiff_fvar_type<typename promote_args<RealType0, RealType1>::type, Order0>;
 };
 
 template <typename RealType0, typename RealType1, size_t Order1>
-struct promote_args_2<RealType0, detail::autodiff_fvar_type<RealType1, Order1>> {
-  using type = detail::autodiff_fvar_type<typename promote_args_2<RealType0, RealType1>::type, Order1>;
+struct promote_args<RealType0, detail::autodiff_fvar_type<RealType1, Order1>> {
+  using type = detail::autodiff_fvar_type<typename promote_args<RealType0, RealType1>::type, Order1>;
 };
 
 template <typename destination_t, typename RealType, std::size_t Order>

From 93d630720b47f9c56819980a997212db4929a765 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:38:30 -0400
Subject: [PATCH 298/399] Add NVRTC definition of BOOST_MATH_NOEXCEPT

---
 include/boost/math/tools/config.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index eeee116711..2048cfbc1e 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -793,6 +793,8 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 
 #define BOOST_MATH_STATIC static
 
+#define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
+
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
 

From ede033ee7958539410df73181fdbcfc81e7c19e9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:59:05 -0400
Subject: [PATCH 299/399] Add GPU to macro definitions

---
 include/boost/math/policies/policy.hpp | 28 +++++++++++++-------------
 1 file changed, 14 insertions(+), 14 deletions(-)

diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index a17dfe6dbf..432191362e 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -135,16 +135,16 @@ namespace policies{
                                                                                                 \
    namespace detail{                                                                            \
    template <Type N>                                                                            \
-   char test_is_valid_arg(const name<N>* = nullptr);                                            \
-   char test_is_default_arg(const name<Default>* = nullptr);                                    \
+   BOOST_MATH_GPU_ENABLED char test_is_valid_arg(const name<N>* = nullptr);                     \
+   BOOST_MATH_GPU_ENABLED char test_is_default_arg(const name<Default>* = nullptr);             \
                                                                                                 \
    template <typename T>                                                                        \
    class is_##name##_imp                                                                        \
    {                                                                                            \
    private:                                                                                     \
       template <Type N>                                                                         \
-      static char test(const name<N>* = nullptr);                                               \
-      static double test(...);                                                                  \
+      BOOST_MATH_GPU_ENABLED static char test(const name<N>* = nullptr);                        \
+      BOOST_MATH_GPU_ENABLED static double test(...);                                           \
    public:                                                                                      \
       static constexpr bool value = sizeof(test(static_cast<T*>(nullptr))) == sizeof(char);     \
    };                                                                                           \
@@ -164,16 +164,16 @@ namespace policies{
                                                                                                 \
    namespace detail{                                                                            \
    template <bool N>                                                                            \
-   char test_is_valid_arg(const name<N>* = nullptr);                                            \
-   char test_is_default_arg(const name<Default>* = nullptr);                                    \
+   BOOST_MATH_GPU_ENABLED char test_is_valid_arg(const name<N>* = nullptr);                     \
+   BOOST_MATH_GPU_ENABLED char test_is_default_arg(const name<Default>* = nullptr);             \
                                                                                                 \
    template <typename T>                                                                        \
    class is_##name##_imp                                                                        \
    {                                                                                            \
    private:                                                                                     \
       template <bool N>                                                                         \
-      static char test(const name<N>* = nullptr);                                               \
-      static double test(...);                                                                  \
+      BOOST_MATH_GPU_ENABLED static char test(const name<N>* = nullptr);                        \
+      BOOST_MATH_GPU_ENABLED static double test(...);                                           \
    public:                                                                                      \
       static constexpr bool value = sizeof(test(static_cast<T*>(nullptr))) == sizeof(char);     \
    };                                                                                           \
@@ -273,10 +273,10 @@ struct precision
 #endif
 };
 
-double test_is_valid_arg(...);
-double test_is_default_arg(...);
-char test_is_valid_arg(const default_policy*);
-char test_is_default_arg(const default_policy*);
+BOOST_MATH_GPU_ENABLED double test_is_valid_arg(...);
+BOOST_MATH_GPU_ENABLED double test_is_default_arg(...);
+BOOST_MATH_GPU_ENABLED char test_is_valid_arg(const default_policy*);
+BOOST_MATH_GPU_ENABLED char test_is_default_arg(const default_policy*);
 
 template <typename T>
 class is_valid_policy_imp
@@ -934,8 +934,8 @@ template <class A1,
           class A9,
           class A10,
           class A11>
-char test_is_policy(const policy<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11>*);
-double test_is_policy(...);
+BOOST_MATH_GPU_ENABLED char test_is_policy(const policy<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11>*);
+BOOST_MATH_GPU_ENABLED double test_is_policy(...);
 
 template <typename P>
 class is_policy_imp

From 3a6eacc358de29fe84332533f6dead71cd7a6af7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 14:59:21 -0400
Subject: [PATCH 300/399] Add more macro definitions

---
 include/boost/math/tools/config.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 2048cfbc1e..dc358852b5 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -794,6 +794,8 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_STATIC static
 
 #define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
+#define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T) 
+#define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
 
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }

From 81ccdb3659325480ac58bd94e1880827bab15cab Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 15:53:53 -0400
Subject: [PATCH 301/399] Remove old workaround

---
 .../boost/math/policies/error_handling.hpp    | 26 -------------------
 1 file changed, 26 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 0f85023be0..b1c0d8e3ec 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -336,32 +336,6 @@ BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
    return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : boost::math::tools::max_value<T>();
 }
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr float raise_overflow_error<float>(
-           const char* ,
-           const char* ,
-           const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(float)
-{
-   // This may or may not do the right thing, but the user asked for the error
-   // to be ignored so here we go anyway:
-   return static_cast<float>(INFINITY);
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr double raise_overflow_error<double>(
-           const char* ,
-           const char* ,
-           const  ::boost::math::policies::overflow_error< ::boost::math::policies::ignore_error>&) BOOST_MATH_NOEXCEPT(double)
-{
-   // This may or may not do the right thing, but the user asked for the error
-   // to be ignored so here we go anyway:
-   return INFINITY;
-}
-
-#endif
-
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
            const char* ,

From e48890febdd27823fab4dd6b21cd58dd8e90380b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 16:19:12 -0400
Subject: [PATCH 302/399] Add NVRTC capable error handling

---
 .../boost/math/policies/error_handling.hpp    | 147 ++++++++++++++++++
 1 file changed, 147 insertions(+)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index b1c0d8e3ec..d1d74c5349 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -10,6 +10,9 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <iomanip>
 #include <string>
 #include <cstring>
@@ -892,5 +895,149 @@ BOOST_MATH_GPU_ENABLED std::pair<T, T> pair_from_single(const T& val) BOOST_MATH
 
 }} // namespaces boost/math
 
+#else // Special values for NVRTC
+
+namespace boost {
+namespace math {
+namespace policies {
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_domain_error(
+           const char* ,
+           const char* ,
+           const T& ,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return boost::math::numeric_limits<T>::quiet_NaN();
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_pole_error(
+           const char* function,
+           const char* message,
+           const T& val,
+           const  Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   return boost::math::numeric_limits<T>::quiet_NaN();
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
+           const char* ,
+           const char* ,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : (boost::math::numeric_limits<T>::max)();
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_overflow_error(
+           const char* ,
+           const char* ,
+           const T&,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return boost::math::numeric_limits<T>::has_infinity ? boost::math::numeric_limits<T>::infinity() : (boost::math::numeric_limits<T>::max)();
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_underflow_error(
+           const char* ,
+           const char* ,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return static_cast<T>(0);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED inline constexpr T raise_denorm_error(
+           const char* ,
+           const char* ,
+           const T& val,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return val;
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr T raise_evaluation_error(
+           const char* ,
+           const char* ,
+           const T& val,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return val;
+}
+
+template <class T, class TargetType, class Policy>
+BOOST_MATH_GPU_ENABLED constexpr TargetType raise_rounding_error(
+           const char* ,
+           const char* ,
+           const T& val,
+           const TargetType&,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   static_assert(boost::math::numeric_limits<TargetType>::is_specialized, "The target type must have std::numeric_limits specialized.");
+   return  val > 0 ? (boost::math::numeric_limits<TargetType>::max)() : (boost::math::numeric_limits<TargetType>::is_integer ? (boost::math::numeric_limits<TargetType>::min)() : -(boost::math::numeric_limits<TargetType>::max)());
+}
+
+template <class T, class R, class Policy>
+BOOST_MATH_GPU_ENABLED inline constexpr T raise_indeterminate_result_error(
+           const char* ,
+           const char* ,
+           const T& ,
+           const R& result,
+           const Policy&) BOOST_MATH_NOEXCEPT(T)
+{
+   // This may or may not do the right thing, but the user asked for the error
+   // to be ignored so here we go anyway:
+   return result;
+}
+
+template <class R, class Policy, class T>
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, const char* function) noexcept(boost::math::is_floating_point_v<R> && boost::math::is_floating_point_v<T>)
+{
+   // We only have ignore error policy so no reason to check
+   return static_cast<R>(val);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED inline void check_series_iterations(const char* function, BOOST_MATH_UINTMAX_T max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
+{
+   if(max_iter >= policies::get_max_series_iterations<Policy>())
+      raise_evaluation_error<T>(
+         function,
+         "Series evaluation exceeded %1% iterations, giving up now.", static_cast<T>(static_cast<double>(max_iter)), pol);
+}
+
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, BOOST_MATH_UINTMAX_T max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
+{
+   if(max_iter >= policies::get_max_root_iterations<Policy>())
+      raise_evaluation_error<T>(
+         function,
+         "Root finding evaluation exceeded %1% iterations, giving up now.", static_cast<T>(static_cast<double>(max_iter)), pol);
+}
+
+} // namespace policies
+} // namespace math
+} // namespace boost
+
+#endif
+
 #endif // BOOST_MATH_POLICY_ERROR_HANDLING_HPP
 

From b3088322365ac438eb7f0c1263e9be916e0476bb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 16:19:24 -0400
Subject: [PATCH 303/399] Add missing macros

---
 include/boost/math/tools/config.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index dc358852b5..4c8e3dcf30 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -796,6 +796,8 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
 #define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T) 
 #define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
+#define BOOST_MATH_FORCEINLINE __forceinline__
+#define BOOST_MATH_STD_USING  
 
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }

From e4c107ca5c6b7ca8a59177f1d69d9672a8a5c43d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 16:27:36 -0400
Subject: [PATCH 304/399] Add NVRTC support to constants

---
 include/boost/math/constants/constants.hpp | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/constants/constants.hpp b/include/boost/math/constants/constants.hpp
index bd2afd714a..df702bf899 100644
--- a/include/boost/math/constants/constants.hpp
+++ b/include/boost/math/constants/constants.hpp
@@ -1,5 +1,6 @@
 //  Copyright John Maddock 2005-2006, 2011.
 //  Copyright Paul A. Bristow 2006-2011.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -8,6 +9,9 @@
 #define BOOST_MATH_CONSTANTS_CONSTANTS_INCLUDED
 
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/tools/cxx03_warn.hpp>
 #include <boost/math/policies/policy.hpp>
 #include <boost/math/tools/precision.hpp>
@@ -243,6 +247,16 @@ namespace boost{ namespace math
    namespace long_double_constants{ static constexpr long double name = BOOST_MATH_JOIN(x, L); }\
    namespace constants{
 
+#else // NVRTC simplified macro definition
+
+#define BOOST_DEFINE_MATH_CONSTANT(name, value, str_value) template <typename T> BOOST_MATH_GPU_ENABLED constexpr T name() noexcept { return static_cast<T>(value); }
+
+namespace boost {
+namespace math {
+namespace constants {
+
+#endif
+
   BOOST_DEFINE_MATH_CONSTANT(half, 5.000000000000000000000000000000000000e-01, "5.00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000e-01")
   BOOST_DEFINE_MATH_CONSTANT(third, 3.333333333333333333333333333333333333e-01, "3.33333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333333e-01")
   BOOST_DEFINE_MATH_CONSTANT(twothirds, 6.666666666666666666666666666666666666e-01, "6.66666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666666667e-01")
@@ -318,14 +332,12 @@ namespace boost{ namespace math
   BOOST_DEFINE_MATH_CONSTANT(one_div_pi, 0.3183098861837906715377675267450287240689192, "0.31830988618379067153776752674502872406891929148091289749533468811779359526845307018022760553250617191214568545351")
   BOOST_DEFINE_MATH_CONSTANT(two_div_root_pi, 1.12837916709551257389615890312154517168810125, "1.12837916709551257389615890312154517168810125865799771368817144342128493688298682897348732040421472688605669581272")
 
-#if __cplusplus >= 201103L || (defined(_MSC_VER) && _MSC_VER >= 1900)
   BOOST_DEFINE_MATH_CONSTANT(first_feigenbaum, 4.66920160910299067185320382046620161725818557747576863274,  "4.6692016091029906718532038204662016172581855774757686327456513430041343302113147371386897440239480138171")
   BOOST_DEFINE_MATH_CONSTANT(plastic, 1.324717957244746025960908854478097340734404056901733364534, "1.32471795724474602596090885447809734073440405690173336453401505030282785124554759405469934798178728032991")
   BOOST_DEFINE_MATH_CONSTANT(gauss, 0.834626841674073186281429732799046808993993013490347002449, "0.83462684167407318628142973279904680899399301349034700244982737010368199270952641186969116035127532412906785")
   BOOST_DEFINE_MATH_CONSTANT(dottie, 0.739085133215160641655312087673873404013411758900757464965, "0.739085133215160641655312087673873404013411758900757464965680635773284654883547594599376106931766531849801246")
   BOOST_DEFINE_MATH_CONSTANT(reciprocal_fibonacci, 3.35988566624317755317201130291892717968890513, "3.35988566624317755317201130291892717968890513373196848649555381532513031899668338361541621645679008729704")
   BOOST_DEFINE_MATH_CONSTANT(laplace_limit, 0.662743419349181580974742097109252907056233549115022417, "0.66274341934918158097474209710925290705623354911502241752039253499097185308651127724965480259895818168")
-#endif
 
 template <typename T>
 BOOST_MATH_GPU_ENABLED inline constexpr T tau() {  return two_pi<T>(); }
@@ -338,7 +350,11 @@ BOOST_MATH_GPU_ENABLED inline constexpr T tau() {  return two_pi<T>(); }
 // We deliberately include this *after* all the declarations above,
 // that way the calculation routines can call on other constants above:
 //
+// NVRTC will not have a type that needs runtime calculation
+//
+#ifndef BOOST_MATH_HAS_NVRTC
 #include <boost/math/constants/calculate_constants.hpp>
+#endif
 
 #endif // BOOST_MATH_CONSTANTS_CONSTANTS_INCLUDED
 

From ce9ecc7f5f6ef5cbc1efcf0da4616ded6fceeb15 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 16:27:46 -0400
Subject: [PATCH 305/399] Add NVRTC support to digamma

---
 .../boost/math/special_functions/digamma.hpp  | 50 +++++++++++++------
 1 file changed, 35 insertions(+), 15 deletions(-)

diff --git a/include/boost/math/special_functions/digamma.hpp b/include/boost/math/special_functions/digamma.hpp
index bde80f7ddb..382ad0d6b9 100644
--- a/include/boost/math/special_functions/digamma.hpp
+++ b/include/boost/math/special_functions/digamma.hpp
@@ -14,13 +14,20 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-#include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/tools/rational.hpp>
-#include <boost/math/tools/series.hpp>
 #include <boost/math/tools/promotion.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/constants/constants.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/tools/series.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
+#endif
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -39,9 +46,9 @@ namespace detail{
 // Begin by defining the smallest value for which it is safe to
 // use the asymptotic expansion for digamma:
 //
-BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const std::integral_constant<int, 0>*)
+BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const boost::math::integral_constant<int, 0>*)
 {  return 20;  }
-BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const std::integral_constant<int, 113>*)
+BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const boost::math::integral_constant<int, 113>*)
 {  return 20;  }
 BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const void*)
 {  return 10;  }
@@ -55,8 +62,10 @@ BOOST_MATH_GPU_ENABLED inline unsigned digamma_large_lim(const void*)
 //
 // This first one gives 34-digit precision for x >= 20:
 //
+
+#ifndef BOOST_MATH_HAS_NVRTC
 template <class T>
-inline T digamma_imp_large(T x, const std::integral_constant<int, 113>*)
+inline T digamma_imp_large(T x, const boost::math::integral_constant<int, 113>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
    static const T P[] = {
@@ -89,7 +98,7 @@ inline T digamma_imp_large(T x, const std::integral_constant<int, 113>*)
 // 19-digit precision for x >= 10:
 //
 template <class T>
-inline T digamma_imp_large(T x, const std::integral_constant<int, 64>*)
+inline T digamma_imp_large(T x, const boost::math::integral_constant<int, 64>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
    static const T P[] = {
@@ -112,11 +121,12 @@ inline T digamma_imp_large(T x, const std::integral_constant<int, 64>*)
    result -= z * tools::evaluate_polynomial(P, z);
    return result;
 }
+#endif
 //
 // 17-digit precision for x >= 10:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_constant<int, 53>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const boost::math::integral_constant<int, 53>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
    BOOST_MATH_STATIC const T P[] = {
@@ -140,7 +150,7 @@ BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_const
 // 9-digit precision for x >= 10:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_constant<int, 24>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const boost::math::integral_constant<int, 24>*)
 {
    BOOST_MATH_STD_USING // ADL of std functions.
    BOOST_MATH_STATIC const T P[] = {
@@ -155,6 +165,8 @@ BOOST_MATH_GPU_ENABLED inline T digamma_imp_large(T x, const std::integral_const
    result -= z * tools::evaluate_polynomial(P, z);
    return result;
 }
+
+#ifndef BOOST_MATH_HAS_NVRTC
 //
 // Fully generic asymptotic expansion in terms of Bernoulli numbers, see:
 // http://functions.wolfram.com/06.14.06.0012.01
@@ -179,7 +191,7 @@ struct digamma_series_func
 };
 
 template <class T, class Policy>
-inline T digamma_imp_large(T x, const Policy& pol, const std::integral_constant<int, 0>*)
+inline T digamma_imp_large(T x, const Policy& pol, const boost::math::integral_constant<int, 0>*)
 {
    BOOST_MATH_STD_USING
    digamma_series_func<T> s(x);
@@ -196,7 +208,7 @@ inline T digamma_imp_large(T x, const Policy& pol, const std::integral_constant<
 // 35-digit precision:
 //
 template <class T>
-T digamma_imp_1_2(T x, const std::integral_constant<int, 113>*)
+T digamma_imp_1_2(T x, const boost::math::integral_constant<int, 113>*)
 {
    //
    // Now the approximation, we use the form:
@@ -260,7 +272,7 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 113>*)
 // 19-digit precision:
 //
 template <class T>
-T digamma_imp_1_2(T x, const std::integral_constant<int, 64>*)
+T digamma_imp_1_2(T x, const boost::math::integral_constant<int, 64>*)
 {
    //
    // Now the approximation, we use the form:
@@ -308,11 +320,13 @@ T digamma_imp_1_2(T x, const std::integral_constant<int, 64>*)
 
    return result;
 }
+
+#endif
 //
 // 18-digit precision:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED T digamma_imp_1_2(T x, const std::integral_constant<int, 53>*)
+BOOST_MATH_GPU_ENABLED T digamma_imp_1_2(T x, const boost::math::integral_constant<int, 53>*)
 {
    //
    // Now the approximation, we use the form:
@@ -363,7 +377,7 @@ BOOST_MATH_GPU_ENABLED T digamma_imp_1_2(T x, const std::integral_constant<int,
 // 9-digit precision:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED inline T digamma_imp_1_2(T x, const std::integral_constant<int, 24>*)
+BOOST_MATH_GPU_ENABLED inline T digamma_imp_1_2(T x, const boost::math::integral_constant<int, 24>*)
 {
    //
    // Now the approximation, we use the form:
@@ -441,11 +455,13 @@ BOOST_MATH_GPU_ENABLED T digamma_imp(T x, const Tag* t, const Policy& pol)
    // If we're above the lower-limit for the
    // asymptotic expansion then use it:
    //
+   #ifndef BOOST_MATH_HAS_NVRTC
    if(x >= digamma_large_lim(t))
    {
       result += digamma_imp_large(x, t);
    }
    else
+   #endif
    {
       //
       // If x > 2 reduce to the interval [1,2]:
@@ -468,8 +484,10 @@ BOOST_MATH_GPU_ENABLED T digamma_imp(T x, const Tag* t, const Policy& pol)
    return result;
 }
 
+#ifndef BOOST_MATH_HAS_NVRTC
+
 template <class T, class Policy>
-T digamma_imp(T x, const std::integral_constant<int, 0>* t, const Policy& pol)
+T digamma_imp(T x, const boost::math::integral_constant<int, 0>* t, const Policy& pol)
 {
    //
    // This handles reflection of negative arguments, and all our
@@ -566,6 +584,8 @@ T digamma_imp(T x, const std::integral_constant<int, 0>* t, const Policy& pol)
    // LCOV_EXCL_STOP
 }
 
+#endif
+
 } // namespace detail
 
 template <class T, class Policy>
@@ -575,7 +595,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::precision<T, Policy>::type precision_type;
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       (precision_type::value <= 0) || (precision_type::value > 113) ? 0 :
       precision_type::value <= 24 ? 24 :
       precision_type::value <= 53 ? 53 :

From d0e156bb7ee7b3696fb807336b2535e735d61210 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 13 Aug 2024 16:39:53 -0400
Subject: [PATCH 306/399] Add NVRTC digamma tests

---
 test/nvrtc_jamfile                 |   2 +
 test/test_digamma_nvrtc_double.cpp | 190 +++++++++++++++++++++++++++++
 test/test_digamma_nvrtc_float.cpp  | 190 +++++++++++++++++++++++++++++
 3 files changed, 382 insertions(+)
 create mode 100644 test/test_digamma_nvrtc_double.cpp
 create mode 100644 test/test_digamma_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 9e59740e61..434ca002be 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -14,6 +14,8 @@ run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
 run test_cos_pi_nvrtc_double.cpp ;
 run test_cos_pi_nvrtc_float.cpp ;
+run test_digamma_nvrtc_double.cpp ;
+run test_digamma_nvrtc_float.cpp ;
 run test_erf_nvrtc_double.cpp ;
 run test_erf_nvrtc_float.cpp ;
 run test_erfc_nvrtc_double.cpp ;
diff --git a/test/test_digamma_nvrtc_double.cpp b/test/test_digamma_nvrtc_double.cpp
new file mode 100644
index 0000000000..d3da101881
--- /dev/null
+++ b/test/test_digamma_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/digamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/digamma.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::digamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::digamma(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_digamma_nvrtc_float.cpp b/test/test_digamma_nvrtc_float.cpp
new file mode 100644
index 0000000000..a698cbd56d
--- /dev/null
+++ b/test/test_digamma_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/digamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/digamma.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::digamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::digamma(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 788eb24c126755a8178418ccfcbd1a5fde82070c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 11:06:06 -0400
Subject: [PATCH 307/399] Add NVRTC support to precision tools

---
 include/boost/math/tools/precision.hpp | 159 ++++++++++---------------
 1 file changed, 65 insertions(+), 94 deletions(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index eb49ca9178..0055d90281 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -15,12 +15,15 @@
 #include <boost/math/tools/type_traits.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/policies/policy.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
 #include <type_traits>
 #include <limits>
 #include <climits>
 #include <cmath>
 #include <cstdint>
 #include <cfloat> // LDBL_MANT_DIG
+#endif
 
 namespace boost{ namespace math
 {
@@ -41,62 +44,30 @@ namespace tools
 template <class T>
 inline constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept
 {
-   static_assert( ::std::numeric_limits<T>::is_specialized, "Type T must be specialized");
-   static_assert( ::std::numeric_limits<T>::radix == 2 || ::std::numeric_limits<T>::radix == 10, "Type T must have a radix of 2 or 10");
+   static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
+   static_assert( ::boost::math::numeric_limits<T>::radix == 2 || ::boost::math::numeric_limits<T>::radix == 10, "Type T must have a radix of 2 or 10");
 
-   return std::numeric_limits<T>::radix == 2
-      ? std::numeric_limits<T>::digits
-      : ((std::numeric_limits<T>::digits + 1) * 1000L) / 301L;
+   return boost::math::numeric_limits<T>::radix == 2
+      ? boost::math::numeric_limits<T>::digits
+      : ((boost::math::numeric_limits<T>::digits + 1) * 1000L) / 301L;
 }
 
 template <class T>
-inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(std::is_floating_point<T>::value)
+inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(boost::math::is_floating_point<T>::value)
 {
-   static_assert( ::std::numeric_limits<T>::is_specialized, "Type T must be specialized");
-   return (std::numeric_limits<T>::max)();
+   static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
+   return (boost::math::numeric_limits<T>::max)();
 } // Also used as a finite 'infinite' value for - and +infinity, for example:
 // -max_value<double> = -1.79769e+308, max_value<double> = 1.79769e+308.
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr float max_value<float>() noexcept
-{
-   return FLT_MAX;
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr double max_value<double>() noexcept
-{
-   return DBL_MAX;
-}
-
-#endif
-
 template <class T>
-inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
-   static_assert( ::std::numeric_limits<T>::is_specialized, "Type T must be specialized");
-
-   return (std::numeric_limits<T>::min)();
-}
+   static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr float min_value<float>() noexcept
-{
-   return FLT_MIN;
+   return (boost::math::numeric_limits<T>::min)();
 }
 
-template <>
-BOOST_MATH_GPU_ENABLED constexpr double min_value<double>() noexcept
-{
-   return DBL_MIN;
-}
-
-#endif
-
 namespace detail{
 //
 // Logarithmic limits come next, note that although
@@ -107,13 +78,13 @@ namespace detail{
 // For type float first:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const boost::math::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return 88.0f;
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const boost::math::integral_constant<int, 128>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return -87.0f;
 }
@@ -121,13 +92,13 @@ BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<in
 // Now double:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_max_value(const boost::math::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return 709.0;
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const boost::math::integral_constant<int, 1024>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return -708.0;
 }
@@ -135,19 +106,19 @@ BOOST_MATH_GPU_ENABLED constexpr T log_min_value(const std::integral_constant<in
 // 80 and 128-bit long doubles:
 //
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(const boost::math::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return 11356.0L;
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(const std::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(const boost::math::integral_constant<int, 16384>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return -11355.0L;
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline T log_max_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+BOOST_MATH_GPU_ENABLED inline T log_max_value(const boost::math::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    BOOST_MATH_STD_USING
 #ifdef __SUNPRO_CC
@@ -160,7 +131,7 @@ BOOST_MATH_GPU_ENABLED inline T log_max_value(const std::integral_constant<int,
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline T log_min_value(const std::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+BOOST_MATH_GPU_ENABLED inline T log_min_value(const boost::math::integral_constant<int, 0>& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    BOOST_MATH_STD_USING
 #ifdef __SUNPRO_CC
@@ -173,21 +144,21 @@ BOOST_MATH_GPU_ENABLED inline T log_min_value(const std::integral_constant<int,
 }
 
 template <class T>
-constexpr T epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(std::is_floating_point<T>::value)
+constexpr T epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
-   return std::numeric_limits<T>::epsilon();
+   return boost::math::numeric_limits<T>::epsilon();
 }
 
 #ifdef BOOST_MATH_HAS_GPU_SUPPORT
 
 template <>
-BOOST_MATH_GPU_ENABLED constexpr float epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
+BOOST_MATH_GPU_ENABLED constexpr float epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
 {
    return FLT_EPSILON;
 }
 
 template <>
-BOOST_MATH_GPU_ENABLED constexpr double epsilon(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
+BOOST_MATH_GPU_ENABLED constexpr double epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
 {
    return DBL_EPSILON;
 }
@@ -196,7 +167,7 @@ BOOST_MATH_GPU_ENABLED constexpr double epsilon(const std::true_type& BOOST_MATH
 
 #if defined(__GNUC__) && ((LDBL_MANT_DIG == 106) || (__LDBL_MANT_DIG__ == 106))
 template <>
-inline constexpr long double epsilon<long double>(const std::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(long double)) noexcept
+inline constexpr long double epsilon<long double>(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(long double)) noexcept(boost::math::is_floating_point<long double>::value)
 {
    // numeric_limits on Darwin (and elsewhere) tells lies here:
    // the issue is that long double on a few platforms is
@@ -215,7 +186,7 @@ inline constexpr long double epsilon<long double>(const std::true_type& BOOST_MA
 #endif
 
 template <class T>
-inline T epsilon(const std::false_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+inline T epsilon(const boost::math::false_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    // Note: don't cache result as precision may vary at runtime:
    BOOST_MATH_STD_USING  // for ADL of std names
@@ -225,23 +196,23 @@ inline T epsilon(const std::false_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE
 template <class T>
 struct log_limit_traits
 {
-   typedef typename std::conditional<
-      (std::numeric_limits<T>::radix == 2) &&
-      (std::numeric_limits<T>::max_exponent == 128
-         || std::numeric_limits<T>::max_exponent == 1024
-         || std::numeric_limits<T>::max_exponent == 16384),
-      std::integral_constant<int, (std::numeric_limits<T>::max_exponent > INT_MAX ? INT_MAX : static_cast<int>(std::numeric_limits<T>::max_exponent))>,
-      std::integral_constant<int, 0>
+   typedef typename boost::math::conditional<
+      (boost::math::numeric_limits<T>::radix == 2) &&
+      (boost::math::numeric_limits<T>::max_exponent == 128
+         || boost::math::numeric_limits<T>::max_exponent == 1024
+         || boost::math::numeric_limits<T>::max_exponent == 16384),
+      boost::math::integral_constant<int, (boost::math::numeric_limits<T>::max_exponent > (boost::math::numeric_limits<int>::max)() ? (boost::math::numeric_limits<int>::max)() : static_cast<int>(boost::math::numeric_limits<T>::max_exponent))>,
+      boost::math::integral_constant<int, 0>
    >::type tag_type;
    static constexpr bool value = (tag_type::value != 0);
-   static_assert(::std::numeric_limits<T>::is_specialized || !value, "Type T must be specialized or equal to 0");
+   static_assert(::boost::math::numeric_limits<T>::is_specialized || !value, "Type T must be specialized or equal to 0");
 };
 
 template <class T, bool b> struct log_limit_noexcept_traits_imp : public log_limit_traits<T> {};
-template <class T> struct log_limit_noexcept_traits_imp<T, false> : public std::integral_constant<bool, false> {};
+template <class T> struct log_limit_noexcept_traits_imp<T, false> : public boost::math::integral_constant<bool, false> {};
 
 template <class T>
-struct log_limit_noexcept_traits : public log_limit_noexcept_traits_imp<T, std::is_floating_point<T>::value> {};
+struct log_limit_noexcept_traits : public log_limit_noexcept_traits_imp<T, boost::math::is_floating_point<T>::value> {};
 
 } // namespace detail
 
@@ -256,9 +227,9 @@ BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(BOOST_MATH_EXPLICIT_TEMP
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::log_max_value<T>(typename detail::log_limit_traits<T>::tag_type());
 #else
-   BOOST_MATH_ASSERT(::std::numeric_limits<T>::is_specialized);
+   BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
    BOOST_MATH_STD_USING
-   static const T val = log((std::numeric_limits<T>::max)());
+   static const T val = log((boost::math::numeric_limits<T>::max)());
    return val;
 #endif
 }
@@ -269,9 +240,9 @@ BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMP
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
    return detail::log_min_value<T>(typename detail::log_limit_traits<T>::tag_type());
 #else
-   BOOST_MATH_ASSERT(::std::numeric_limits<T>::is_specialized);
+   BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
    BOOST_MATH_STD_USING
-   static const T val = log((std::numeric_limits<T>::min)());
+   static const T val = log((boost::math::numeric_limits<T>::min)());
    return val;
 #endif
 }
@@ -284,11 +255,11 @@ template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
 #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
-   return detail::epsilon<T>(std::integral_constant<bool, ::std::numeric_limits<T>::is_specialized>());
+   return detail::epsilon<T>(boost::math::integral_constant<bool, ::boost::math::numeric_limits<T>::is_specialized>());
 #else
-   return ::std::numeric_limits<T>::is_specialized ?
-      detail::epsilon<T>(std::true_type()) :
-      detail::epsilon<T>(std::false_type());
+   return ::boost::math::numeric_limits<T>::is_specialized ?
+      detail::epsilon<T>(boost::math::true_type()) :
+      detail::epsilon<T>(boost::math::false_type());
 #endif
 }
 
@@ -318,25 +289,25 @@ BOOST_MATH_GPU_ENABLED constexpr long double epsilon(BOOST_MATH_EXPLICIT_TEMPLAT
 namespace detail{
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const boost::math::integral_constant<int, 24>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.00034526698300124390839884978618400831996329879769945L);
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 53>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.1490116119384765625e-7L);
 }
 
 template <class T>
-inline constexpr T root_epsilon_imp(const T*, const std::integral_constant<int, 64>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.32927225399135962333569506281281311031656150598474e-9L);
 }
 
 template <class T>
-inline constexpr T root_epsilon_imp(const T*, const std::integral_constant<int, 113>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.1387778780781445675529539585113525390625e-16L);
 }
@@ -350,32 +321,32 @@ inline T root_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T root_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
+inline T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING
    return sqrt(tools::epsilon<T>());
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const boost::math::integral_constant<int, 24>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.0049215666011518482998719164346805794944150447839903L);
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 53>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(6.05545445239333906078989272793696693569753008995e-6L);
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 64>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(4.76837158203125e-7L);
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 113>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(5.7749313854154005630396773604745549542403508090496e-12L);
 }
@@ -389,32 +360,32 @@ inline T cbrt_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T cbrt_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
+inline T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING;
    return pow(tools::epsilon<T>(), T(1) / 3);
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 24>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 24>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.018581361171917516667460937040007436176452688944747L);
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 53>&) noexcept(std::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 53>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.0001220703125L);
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 64>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.18145860519450699870567321328132261891067079047605e-4L);
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 113>&) noexcept(std::is_floating_point<T>::value)
+inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.37252902984619140625e-8L);
 }
@@ -428,7 +399,7 @@ inline T forth_root_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
+inline T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING
    return sqrt(sqrt(tools::epsilon<T>()));
@@ -437,26 +408,26 @@ inline T forth_root_epsilon_imp(const T*, const std::integral_constant<int, 0>&)
 template <class T>
 struct root_epsilon_traits
 {
-   typedef std::integral_constant<int, (::std::numeric_limits<T>::radix == 2) && (::std::numeric_limits<T>::digits != INT_MAX) ? std::numeric_limits<T>::digits : 0> tag_type;
+   typedef boost::math::integral_constant<int, (::boost::math::numeric_limits<T>::radix == 2) && (::boost::math::numeric_limits<T>::digits != (boost::math::numeric_limits<int>::max)()) ? boost::math::numeric_limits<T>::digits : 0> tag_type;
    static constexpr bool has_noexcept = (tag_type::value == 113) || (tag_type::value == 64) || (tag_type::value == 53) || (tag_type::value == 24);
 };
 
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon() noexcept(boost::math::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::root_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon() noexcept(boost::math::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::cbrt_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon() noexcept(std::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon() noexcept(boost::math::is_floating_point<T>::value && detail::root_epsilon_traits<T>::has_noexcept)
 {
    return detail::forth_root_epsilon_imp(static_cast<T const*>(nullptr), typename detail::root_epsilon_traits<T>::tag_type());
 }

From 586b9cf0a9d099e4b33de6f12668f826c2f8b27c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 11:51:23 -0400
Subject: [PATCH 308/399] Fix missing header in error handling

---
 include/boost/math/policies/error_handling.hpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index d1d74c5349..07e1127218 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -10,6 +10,7 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 
 #ifndef BOOST_MATH_HAS_NVRTC
 

From f6bc4af513aebb59001035b503d8bb8879daab4a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 11:52:00 -0400
Subject: [PATCH 309/399] Add minimal implantation of pair for NVRTC platform

---
 include/boost/math/tools/tuple.hpp | 27 ++++++++++++++++++++++++++-
 1 file changed, 26 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index f132b97f51..fba37fb4f8 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -9,7 +9,32 @@
 
 #include <boost/math/tools/config.hpp>
 
-#ifdef BOOST_MATH_ENABLE_CUDA
+#ifdef BOOST_MATH_HAS_NVRTC
+
+namespace boost {
+namespace math {
+
+template <typename T, typename U>
+class pair
+{
+public:
+    T first;
+    U second;
+
+    BOOST_MATH_GPU_ENABLED pair(T x, U y) noexcept : first {x}, second {y} {}
+};
+
+template <typename T, typename U>
+BOOST_MATH_GPU_ENABLED auto make_pair(T x, U y) noexcept
+{
+    return pair(x, y);
+}
+
+} // namespace math
+} // namespace boost
+
+
+#elif defined(BOOST_MATH_ENABLE_CUDA)
 
 #include <thrust/pair.h>
 #include <thrust/tuple.h>

From 408f8af1d8f77f4e15f65d39635e9ba4d7680458 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 11:52:15 -0400
Subject: [PATCH 310/399] Add NVRTC support to derived accessors

---
 .../boost/math/distributions/detail/derived_accessors.hpp  | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/distributions/detail/derived_accessors.hpp b/include/boost/math/distributions/detail/derived_accessors.hpp
index 9d39f2d59d..90679ef21f 100644
--- a/include/boost/math/distributions/detail/derived_accessors.hpp
+++ b/include/boost/math/distributions/detail/derived_accessors.hpp
@@ -28,9 +28,12 @@
 // can find the definitions referred to herein.
 //
 
-#include <cmath>
-#include <boost/math/tools/assert.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/assert.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <cmath>
+#endif
 
 #ifdef _MSC_VER
 # pragma warning(push)

From fc6bc006ddba04e5cdfff39c976e65c4867bf6cb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 11:52:32 -0400
Subject: [PATCH 311/399] Add NVRTC support to the arcsine dist

---
 include/boost/math/distributions/arcsine.hpp | 15 +++++++++------
 1 file changed, 9 insertions(+), 6 deletions(-)

diff --git a/include/boost/math/distributions/arcsine.hpp b/include/boost/math/distributions/arcsine.hpp
index d921e1145f..899bfb1b2b 100644
--- a/include/boost/math/distributions/arcsine.hpp
+++ b/include/boost/math/distributions/arcsine.hpp
@@ -30,15 +30,21 @@
 #ifndef BOOST_MATH_DIST_ARCSINE_HPP
 #define BOOST_MATH_DIST_ARCSINE_HPP
 
-#include <cmath>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/complement.hpp> // complements.
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks.
 #include <boost/math/constants/constants.hpp>
-
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
+#include <cmath>
+#include <utility>
+#include <exception>  // For std::domain_error.
+#endif
 
 #if defined (BOOST_MSVC)
 #  pragma warning(push)
@@ -46,9 +52,6 @@
 // in domain_error_imp in error_handling.
 #endif
 
-#include <utility>
-#include <exception>  // For std::domain_error.
-
 namespace boost
 {
   namespace math

From 866f12a42a294c73711ffd4ae59381fe00300e3f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 12:01:23 -0400
Subject: [PATCH 312/399] Undef BOOST_FPU_EXCEPTION_GUARD if exists and give a
 new empty def

---
 include/boost/math/tools/config.hpp | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 4c8e3dcf30..d886e420d0 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -799,6 +799,13 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_FORCEINLINE __forceinline__
 #define BOOST_MATH_STD_USING  
 
+// This should be defined to nothing but since it is not specifically a math macro
+// we need to undef before proceeding
+#ifdef BOOST_FPU_EXCEPTION_GUARD
+#  undef BOOST_FPU_EXCEPTION_GUARD
+#  define BOOST_FPU_EXCEPTION_GUARD
+#endif
+
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
 

From c47ac631ffc12146747c50782a58c81071e2e0b3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 12:01:34 -0400
Subject: [PATCH 313/399] Add testing of the arcsine dist

---
 test/nvrtc_jamfile                          |   8 +
 test/test_arcsine_cdf_nvrtc_double.cpp      | 191 ++++++++++++++++++++
 test/test_arcsine_cdf_nvrtc_float.cpp       | 191 ++++++++++++++++++++
 test/test_arcsine_pdf_nvrtc_double.cpp      | 191 ++++++++++++++++++++
 test/test_arcsine_pdf_nvrtc_float.cpp       | 191 ++++++++++++++++++++
 test/test_arcsine_quantile_nvrtc_double.cpp | 191 ++++++++++++++++++++
 test/test_arcsine_quantile_nvrtc_float.cpp  | 191 ++++++++++++++++++++
 7 files changed, 1154 insertions(+)
 create mode 100644 test/test_arcsine_cdf_nvrtc_double.cpp
 create mode 100644 test/test_arcsine_cdf_nvrtc_float.cpp
 create mode 100644 test/test_arcsine_pdf_nvrtc_double.cpp
 create mode 100644 test/test_arcsine_pdf_nvrtc_float.cpp
 create mode 100644 test/test_arcsine_quantile_nvrtc_double.cpp
 create mode 100644 test/test_arcsine_quantile_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 434ca002be..325dcfb141 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -9,6 +9,14 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
+# Distributions
+run test_arcsine_cdf_nvrtc_double.cpp ;
+run test_arcsine_cdf_nvrtc_float.cpp ;
+run test_arcsine_pdf_nvrtc_double.cpp ;
+run test_arcsine_pdf_nvrtc_float.cpp ;
+run test_arcsine_quantile_nvrtc_double.cpp ;
+run test_arcsine_quantile_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_arcsine_cdf_nvrtc_double.cpp b/test/test_arcsine_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..814d7491a9
--- /dev/null
+++ b/test/test_arcsine_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_arcsine_cdf_nvrtc_float.cpp b/test/test_arcsine_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..a159e608c7
--- /dev/null
+++ b/test/test_arcsine_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_arcsine_pdf_nvrtc_double.cpp b/test/test_arcsine_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..dde8756292
--- /dev/null
+++ b/test/test_arcsine_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_arcsine_pdf_nvrtc_float.cpp b/test/test_arcsine_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..82b39c3cf6
--- /dev/null
+++ b/test/test_arcsine_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_arcsine_quantile_nvrtc_double.cpp b/test/test_arcsine_quantile_nvrtc_double.cpp
new file mode 100644
index 0000000000..8a2d39ed5a
--- /dev/null
+++ b/test/test_arcsine_quantile_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_arcsine_quantile_nvrtc_float.cpp b/test/test_arcsine_quantile_nvrtc_float.cpp
new file mode 100644
index 0000000000..7491b7e111
--- /dev/null
+++ b/test/test_arcsine_quantile_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/arcsine.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/arcsine.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::arcsine_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::arcsine_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 9c1ce96df4353fcf008d5e029b733d6ab6dd1da3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 13:42:13 -0400
Subject: [PATCH 314/399] Fix FPU Guard macro

---
 include/boost/math/tools/config.hpp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index d886e420d0..a5c8b3fc98 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -803,9 +803,10 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 // we need to undef before proceeding
 #ifdef BOOST_FPU_EXCEPTION_GUARD
 #  undef BOOST_FPU_EXCEPTION_GUARD
-#  define BOOST_FPU_EXCEPTION_GUARD
 #endif
 
+#define BOOST_FPU_EXCEPTION_GUARD
+
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b; b = t; }
 

From 480045bab8a3c926cc55cd86a52aa34b157c989e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 13:42:30 -0400
Subject: [PATCH 315/399] Add NVRTC support to bernoulli dist

---
 include/boost/math/distributions/bernoulli.hpp | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/bernoulli.hpp b/include/boost/math/distributions/bernoulli.hpp
index 639f9119cd..f1c693f7f0 100644
--- a/include/boost/math/distributions/bernoulli.hpp
+++ b/include/boost/math/distributions/bernoulli.hpp
@@ -28,15 +28,19 @@
 #ifndef BOOST_MATH_SPECIAL_BERNOULLI_HPP
 #define BOOST_MATH_SPECIAL_BERNOULLI_HPP
 
-#include <boost/math/distributions/fwd.hpp>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/type_traits.hpp>
 #include <boost/math/distributions/complement.hpp> // complements
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
+#ifndef BOOST_MATH_HAS_NVRTC
 #include <utility>
+#include <boost/math/distributions/fwd.hpp>
+#endif
 
 namespace boost
 {

From 98d6a594b0a75653166df0e1ddb2d96ab29b26c9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 13:42:45 -0400
Subject: [PATCH 316/399] Add bernoulli dist NVRTC testing

---
 test/nvrtc_jamfile                        |   7 +
 test/test_bernoulli_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_bernoulli_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_bernoulli_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_bernoulli_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_bernoulli_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++++
 test/test_bernoulli_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_bernoulli_cdf_nvrtc_double.cpp
 create mode 100644 test/test_bernoulli_cdf_nvrtc_float.cpp
 create mode 100644 test/test_bernoulli_pdf_nvrtc_double.cpp
 create mode 100644 test/test_bernoulli_pdf_nvrtc_float.cpp
 create mode 100644 test/test_bernoulli_quan_nvrtc_double.cpp
 create mode 100644 test/test_bernoulli_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 325dcfb141..10e7077d19 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -17,6 +17,13 @@ run test_arcsine_pdf_nvrtc_float.cpp ;
 run test_arcsine_quantile_nvrtc_double.cpp ;
 run test_arcsine_quantile_nvrtc_float.cpp ;
 
+run test_bernoulli_cdf_nvrtc_double.cpp ;
+run test_bernoulli_cdf_nvrtc_float.cpp ;
+run test_bernoulli_pdf_nvrtc_double.cpp ;
+run test_bernoulli_pdf_nvrtc_float.cpp ;
+run test_bernoulli_quan_nvrtc_double.cpp ;
+run test_bernoulli_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_bernoulli_cdf_nvrtc_double.cpp b/test/test_bernoulli_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..fc21b9ef63
--- /dev/null
+++ b/test/test_bernoulli_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::bernoulli_distribution<float_type>(), round(in1[i]));
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::bernoulli_distribution<float_type>(), round(h_in1[i]));
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bernoulli_cdf_nvrtc_float.cpp b/test/test_bernoulli_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..d5112b6beb
--- /dev/null
+++ b/test/test_bernoulli_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::bernoulli_distribution<float_type>(), round(in1[i]));
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::bernoulli_distribution<float_type>(), round(h_in1[i]));
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bernoulli_pdf_nvrtc_double.cpp b/test/test_bernoulli_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f1b4bdf996
--- /dev/null
+++ b/test/test_bernoulli_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::bernoulli_distribution<float_type>(), round(in1[i]));
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::bernoulli_distribution<float_type>(), round(h_in1[i]));
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bernoulli_pdf_nvrtc_float.cpp b/test/test_bernoulli_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..245945cded
--- /dev/null
+++ b/test/test_bernoulli_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::bernoulli_distribution<float_type>(), round(in1[i]));
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::bernoulli_distribution<float_type>(), round(h_in1[i]));
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bernoulli_quan_nvrtc_double.cpp b/test/test_bernoulli_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..63c8ae7fbe
--- /dev/null
+++ b/test/test_bernoulli_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::bernoulli_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::bernoulli_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bernoulli_quan_nvrtc_float.cpp b/test/test_bernoulli_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..5264388674
--- /dev/null
+++ b/test/test_bernoulli_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/bernoulli.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/bernoulli.hpp>
+extern "C" __global__ 
+void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::bernoulli_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::bernoulli_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 45745c8f230e119298352fb1a3e6a176d70a51ed Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 14:39:14 -0400
Subject: [PATCH 317/399] Fix kernel naming

---
 test/test_arcsine_cdf_nvrtc_double.cpp      | 8 ++++----
 test/test_arcsine_cdf_nvrtc_float.cpp       | 8 ++++----
 test/test_arcsine_pdf_nvrtc_double.cpp      | 8 ++++----
 test/test_arcsine_pdf_nvrtc_float.cpp       | 8 ++++----
 test/test_arcsine_quantile_nvrtc_double.cpp | 8 ++++----
 test/test_arcsine_quantile_nvrtc_float.cpp  | 8 ++++----
 test/test_bernoulli_cdf_nvrtc_double.cpp    | 8 ++++----
 test/test_bernoulli_cdf_nvrtc_float.cpp     | 8 ++++----
 test/test_bernoulli_pdf_nvrtc_double.cpp    | 8 ++++----
 test/test_bernoulli_pdf_nvrtc_float.cpp     | 8 ++++----
 test/test_bernoulli_quan_nvrtc_double.cpp   | 8 ++++----
 test/test_bernoulli_quan_nvrtc_float.cpp    | 8 ++++----
 12 files changed, 48 insertions(+), 48 deletions(-)

diff --git a/test/test_arcsine_cdf_nvrtc_double.cpp b/test/test_arcsine_cdf_nvrtc_double.cpp
index 814d7491a9..58b6b8297f 100644
--- a/test/test_arcsine_cdf_nvrtc_double.cpp
+++ b/test/test_arcsine_cdf_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_arcsine_cdf_nvrtc_float.cpp b/test/test_arcsine_cdf_nvrtc_float.cpp
index a159e608c7..3f8b04bb0b 100644
--- a/test/test_arcsine_cdf_nvrtc_float.cpp
+++ b/test/test_arcsine_cdf_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_arcsine_pdf_nvrtc_double.cpp b/test/test_arcsine_pdf_nvrtc_double.cpp
index dde8756292..c76b47f883 100644
--- a/test/test_arcsine_pdf_nvrtc_double.cpp
+++ b/test/test_arcsine_pdf_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_arcsine_pdf_nvrtc_float.cpp b/test/test_arcsine_pdf_nvrtc_float.cpp
index 82b39c3cf6..e9145a1624 100644
--- a/test/test_arcsine_pdf_nvrtc_float.cpp
+++ b/test/test_arcsine_pdf_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_arcsine_quantile_nvrtc_double.cpp b/test/test_arcsine_quantile_nvrtc_double.cpp
index 8a2d39ed5a..ba8e2e5df5 100644
--- a/test/test_arcsine_quantile_nvrtc_double.cpp
+++ b/test/test_arcsine_quantile_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_arcsine_quantile_nvrtc_float.cpp b/test/test_arcsine_quantile_nvrtc_float.cpp
index 7491b7e111..1fd2e4884a 100644
--- a/test/test_arcsine_quantile_nvrtc_float.cpp
+++ b/test/test_arcsine_quantile_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/arcsine.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_cdf_nvrtc_double.cpp b/test/test_bernoulli_cdf_nvrtc_double.cpp
index fc21b9ef63..887c3430a0 100644
--- a/test/test_bernoulli_cdf_nvrtc_double.cpp
+++ b/test/test_bernoulli_cdf_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_cdf_nvrtc_float.cpp b/test/test_bernoulli_cdf_nvrtc_float.cpp
index d5112b6beb..1a38c43480 100644
--- a/test/test_bernoulli_cdf_nvrtc_float.cpp
+++ b/test/test_bernoulli_cdf_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_pdf_nvrtc_double.cpp b/test/test_bernoulli_pdf_nvrtc_double.cpp
index f1b4bdf996..f3e21a0951 100644
--- a/test/test_bernoulli_pdf_nvrtc_double.cpp
+++ b/test/test_bernoulli_pdf_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_pdf_nvrtc_float.cpp b/test/test_bernoulli_pdf_nvrtc_float.cpp
index 245945cded..bf9b760168 100644
--- a/test/test_bernoulli_pdf_nvrtc_float.cpp
+++ b/test/test_bernoulli_pdf_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_quan_nvrtc_double.cpp b/test/test_bernoulli_quan_nvrtc_double.cpp
index 63c8ae7fbe..dcdd0e1f1b 100644
--- a/test/test_bernoulli_quan_nvrtc_double.cpp
+++ b/test/test_bernoulli_quan_nvrtc_double.cpp
@@ -28,7 +28,7 @@ typedef double float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;
diff --git a/test/test_bernoulli_quan_nvrtc_float.cpp b/test/test_bernoulli_quan_nvrtc_float.cpp
index 5264388674..24c4923818 100644
--- a/test/test_bernoulli_quan_nvrtc_float.cpp
+++ b/test/test_bernoulli_quan_nvrtc_float.cpp
@@ -28,7 +28,7 @@ typedef float float_type;
 #include <cuda/std/type_traits>
 #include <boost/math/distributions/bernoulli.hpp>
 extern "C" __global__ 
-void test_digamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
 {
     int i = blockDim.x * blockIdx.x + threadIdx.x;
     if (i < numElements)
@@ -83,10 +83,10 @@ int main()
         nvrtcProgram prog;
         nvrtcResult res;
 
-        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_digamma_kernel.cu", 0, nullptr, nullptr);
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
         checkNVRTCError(res, "Failed to create NVRTC program");
 
-        nvrtcAddNameExpression(prog, "test_digamma_kernel");
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
@@ -117,7 +117,7 @@ int main()
         CUmodule module;
         CUfunction kernel;
         checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
-        checkCUError(cuModuleGetFunction(&kernel, module, "test_digamma_kernel"), "Failed to get kernel function");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
 
         int numElements = 5000;
         float_type *h_in1, *h_in2, *h_out;

From 1aaf659efa1e9c152155228485cb16a0bb28a75e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 14:39:38 -0400
Subject: [PATCH 318/399] Remove workarounds and markup functions that will
 never be taken anyway

---
 include/boost/math/tools/config.hpp    |  1 +
 include/boost/math/tools/precision.hpp | 90 ++++++++------------------
 2 files changed, 29 insertions(+), 62 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index a5c8b3fc98..b67ce0ae91 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -795,6 +795,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 
 #define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
 #define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T) 
+#define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) 
 #define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
 #define BOOST_MATH_FORCEINLINE __forceinline__
 #define BOOST_MATH_STD_USING  
diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 0055d90281..096a3265ae 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -42,7 +42,7 @@ namespace tools
 // See  Conceptual Requirements for Real Number Types.
 
 template <class T>
-inline constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept
+BOOST_MATH_GPU_ENABLED inline constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept
 {
    static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
    static_assert( ::boost::math::numeric_limits<T>::radix == 2 || ::boost::math::numeric_limits<T>::radix == 10, "Type T must have a radix of 2 or 10");
@@ -53,7 +53,7 @@ inline constexpr int digits(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept
 }
 
 template <class T>
-inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(boost::math::is_floating_point<T>::value)
 {
    static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
    return (boost::math::numeric_limits<T>::max)();
@@ -61,7 +61,7 @@ inline constexpr T max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T))  noexcept(boo
 // -max_value<double> = -1.79769e+308, max_value<double> = 1.79769e+308.
 
 template <class T>
-inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    static_assert( ::boost::math::numeric_limits<T>::is_specialized, "Type T must be specialized");
 
@@ -144,30 +144,14 @@ BOOST_MATH_GPU_ENABLED inline T log_min_value(const boost::math::integral_consta
 }
 
 template <class T>
-constexpr T epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED constexpr T epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
    return boost::math::numeric_limits<T>::epsilon();
 }
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr float epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(float)) noexcept(true)
-{
-   return FLT_EPSILON;
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr double epsilon(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(double)) noexcept(true)
-{
-   return DBL_EPSILON;
-}
-
-#endif
-
 #if defined(__GNUC__) && ((LDBL_MANT_DIG == 106) || (__LDBL_MANT_DIG__ == 106))
 template <>
-inline constexpr long double epsilon<long double>(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(long double)) noexcept(boost::math::is_floating_point<long double>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr long double epsilon<long double>(const boost::math::true_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(long double)) noexcept(boost::math::is_floating_point<long double>::value)
 {
    // numeric_limits on Darwin (and elsewhere) tells lies here:
    // the issue is that long double on a few platforms is
@@ -186,7 +170,7 @@ inline constexpr long double epsilon<long double>(const boost::math::true_type&
 #endif
 
 template <class T>
-inline T epsilon(const boost::math::false_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
+BOOST_MATH_GPU_ENABLED inline T epsilon(const boost::math::false_type& BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(T))
 {
    // Note: don't cache result as precision may vary at runtime:
    BOOST_MATH_STD_USING  // for ADL of std names
@@ -254,38 +238,20 @@ BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMP
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T)) noexcept(boost::math::is_floating_point<T>::value)
 {
-#ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
-   return detail::epsilon<T>(boost::math::integral_constant<bool, ::boost::math::numeric_limits<T>::is_specialized>());
+   // NVRTC does not like this dispatching method so we just skip to where we want to go
+#ifndef BOOST_MATH_HAS_NVRTC
+   #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
+      return detail::epsilon<T>(boost::math::integral_constant<bool, ::boost::math::numeric_limits<T>::is_specialized>());
+   #else
+      return ::boost::math::numeric_limits<T>::is_specialized ?
+         detail::epsilon<T>(boost::math::true_type()) :
+         detail::epsilon<T>(boost::math::false_type());
+   #endif
 #else
-   return ::boost::math::numeric_limits<T>::is_specialized ?
-      detail::epsilon<T>(boost::math::true_type()) :
-      detail::epsilon<T>(boost::math::false_type());
+   return boost::math::numeric_limits<T>::epsilon();
 #endif
 }
 
-#ifdef BOOST_MATH_HAS_GPU_SUPPORT
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr float epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(float)) noexcept(true)
-{
-   return FLT_EPSILON;
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr double epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(double)) noexcept(true)
-{
-   return DBL_EPSILON;
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED constexpr long double epsilon(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(long double)) noexcept(true)
-{
-   return LDBL_EPSILON;
-}
-
-
-#endif
-
 namespace detail{
 
 template <class T>
@@ -301,19 +267,19 @@ BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const boost
 }
 
 template <class T>
-inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.32927225399135962333569506281281311031656150598474e-9L);
 }
 
 template <class T>
-inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.1387778780781445675529539585113525390625e-16L);
 }
 
 template <class T, class Tag>
-inline T root_epsilon_imp(const T*, const Tag&)
+BOOST_MATH_GPU_ENABLED inline T root_epsilon_imp(const T*, const Tag&)
 {
    BOOST_MATH_STD_USING
    static const T r_eps = sqrt(tools::epsilon<T>());
@@ -321,7 +287,7 @@ inline T root_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED inline T root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING
    return sqrt(tools::epsilon<T>());
@@ -340,19 +306,19 @@ BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const boost
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(4.76837158203125e-7L);
 }
 
 template <class T>
-inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(5.7749313854154005630396773604745549542403508090496e-12L);
 }
 
 template <class T, class Tag>
-inline T cbrt_epsilon_imp(const T*, const Tag&)
+BOOST_MATH_GPU_ENABLED inline T cbrt_epsilon_imp(const T*, const Tag&)
 {
    BOOST_MATH_STD_USING;
    static const T cbrt_eps = pow(tools::epsilon<T>(), T(1) / 3);
@@ -360,7 +326,7 @@ inline T cbrt_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED inline T cbrt_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING;
    return pow(tools::epsilon<T>(), T(1) / 3);
@@ -379,19 +345,19 @@ BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 64>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.18145860519450699870567321328132261891067079047605e-4L);
 }
 
 template <class T>
-inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
+BOOST_MATH_GPU_ENABLED inline constexpr T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 113>&) noexcept(boost::math::is_floating_point<T>::value)
 {
    return static_cast<T>(0.37252902984619140625e-8L);
 }
 
 template <class T, class Tag>
-inline T forth_root_epsilon_imp(const T*, const Tag&)
+BOOST_MATH_GPU_ENABLED inline T forth_root_epsilon_imp(const T*, const Tag&)
 {
    BOOST_MATH_STD_USING
    static const T r_eps = sqrt(sqrt(tools::epsilon<T>()));
@@ -399,7 +365,7 @@ inline T forth_root_epsilon_imp(const T*, const Tag&)
 }
 
 template <class T>
-inline T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED inline T forth_root_epsilon_imp(const T*, const boost::math::integral_constant<int, 0>&)
 {
    BOOST_MATH_STD_USING
    return sqrt(sqrt(tools::epsilon<T>()));

From 46a37ffebe3844abaf39ba9bae7c0867048802f0 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 14:39:59 -0400
Subject: [PATCH 319/399] Add NVRTC support to cauchy dist

---
 include/boost/math/distributions/cauchy.hpp | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index 716940119c..4cc93b260b 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -17,12 +17,18 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
-#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
 #include <utility>
 #include <cmath>
+#endif
 
 namespace boost{ namespace math
 {

From fb9d2fe974e304727c8e02738042ecd868d9fa67 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 14:40:09 -0400
Subject: [PATCH 320/399] Add cauchy dist NVRTC testing

---
 test/nvrtc_jamfile                     |   7 +
 test/test_cauchy_cdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++++
 test/test_cauchy_cdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++++
 test/test_cauchy_pdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++++
 test/test_cauchy_pdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++++
 test/test_cauchy_quan_nvrtc_double.cpp | 191 +++++++++++++++++++++++++
 test/test_cauchy_quan_nvrtc_float.cpp  | 191 +++++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_cauchy_cdf_nvrtc_double.cpp
 create mode 100644 test/test_cauchy_cdf_nvrtc_float.cpp
 create mode 100644 test/test_cauchy_pdf_nvrtc_double.cpp
 create mode 100644 test/test_cauchy_pdf_nvrtc_float.cpp
 create mode 100644 test/test_cauchy_quan_nvrtc_double.cpp
 create mode 100644 test/test_cauchy_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 10e7077d19..2825fb9697 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -24,6 +24,13 @@ run test_bernoulli_pdf_nvrtc_float.cpp ;
 run test_bernoulli_quan_nvrtc_double.cpp ;
 run test_bernoulli_quan_nvrtc_float.cpp ;
 
+run test_cauchy_cdf_nvrtc_double.cpp ;
+run test_cauchy_cdf_nvrtc_float.cpp ;
+run test_cauchy_pdf_nvrtc_double.cpp ;
+run test_cauchy_pdf_nvrtc_float.cpp ;
+run test_cauchy_quan_nvrtc_double.cpp ;
+run test_cauchy_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_cauchy_cdf_nvrtc_double.cpp b/test/test_cauchy_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f9b16b6e0e
--- /dev/null
+++ b/test/test_cauchy_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cauchy_cdf_nvrtc_float.cpp b/test/test_cauchy_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..0870900ae4
--- /dev/null
+++ b/test/test_cauchy_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cauchy_pdf_nvrtc_double.cpp b/test/test_cauchy_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..24e2808c93
--- /dev/null
+++ b/test/test_cauchy_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cauchy_pdf_nvrtc_float.cpp b/test/test_cauchy_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..605d257831
--- /dev/null
+++ b/test/test_cauchy_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cauchy_quan_nvrtc_double.cpp b/test/test_cauchy_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..08fa01c4f9
--- /dev/null
+++ b/test/test_cauchy_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cauchy_quan_nvrtc_float.cpp b/test/test_cauchy_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..6d63d1c2d6
--- /dev/null
+++ b/test/test_cauchy_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/cauchy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/cauchy.hpp>
+extern "C" __global__ 
+void test_cauchy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::cauchy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cauchy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cauchy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cauchy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::cauchy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 2e887c78bfdd06ed7586a940ebffbe7259ffe1a5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 15:54:15 -0400
Subject: [PATCH 321/399] Add NVRTC support to exponential dist

---
 include/boost/math/distributions/exponential.hpp | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/exponential.hpp b/include/boost/math/distributions/exponential.hpp
index 01c442fa81..9d45ac4933 100644
--- a/include/boost/math/distributions/exponential.hpp
+++ b/include/boost/math/distributions/exponential.hpp
@@ -10,12 +10,13 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
-#include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/expm1.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -23,8 +24,11 @@
 # pragma warning(disable: 4702) // unreachable code (return after domain_error throw).
 #endif
 
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
 #include <utility>
 #include <cmath>
+#endif
 
 namespace boost{ namespace math{
 

From baa1bf3623ccf4994ea2e6d90dbeee8add4497bd Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 15:54:28 -0400
Subject: [PATCH 322/399] Add exponential dist NVRTC testing

---
 test/nvrtc_jamfile                          |   7 +
 test/test_exponential_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++
 test/test_exponential_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++
 test/test_exponential_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++
 test/test_exponential_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++
 test/test_exponential_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++
 test/test_exponential_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_exponential_cdf_nvrtc_double.cpp
 create mode 100644 test/test_exponential_cdf_nvrtc_float.cpp
 create mode 100644 test/test_exponential_pdf_nvrtc_double.cpp
 create mode 100644 test/test_exponential_pdf_nvrtc_float.cpp
 create mode 100644 test/test_exponential_quan_nvrtc_double.cpp
 create mode 100644 test/test_exponential_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 2825fb9697..da734ce070 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -31,6 +31,13 @@ run test_cauchy_pdf_nvrtc_float.cpp ;
 run test_cauchy_quan_nvrtc_double.cpp ;
 run test_cauchy_quan_nvrtc_float.cpp ;
 
+run test_exponential_cdf_nvrtc_double.cpp ;
+run test_exponential_cdf_nvrtc_float.cpp ;
+run test_exponential_pdf_nvrtc_double.cpp ;
+run test_exponential_pdf_nvrtc_float.cpp ;
+run test_exponential_quan_nvrtc_double.cpp ;
+run test_exponential_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_exponential_cdf_nvrtc_double.cpp b/test/test_exponential_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..42849f8abe
--- /dev/null
+++ b/test/test_exponential_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exponential_cdf_nvrtc_float.cpp b/test/test_exponential_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..9417abf026
--- /dev/null
+++ b/test/test_exponential_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exponential_pdf_nvrtc_double.cpp b/test/test_exponential_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..2c52a4b38e
--- /dev/null
+++ b/test/test_exponential_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exponential_pdf_nvrtc_float.cpp b/test/test_exponential_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..ef1aff3f3c
--- /dev/null
+++ b/test/test_exponential_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exponential_quan_nvrtc_double.cpp b/test/test_exponential_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..b05f77ffef
--- /dev/null
+++ b/test/test_exponential_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exponential_quan_nvrtc_float.cpp b/test/test_exponential_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..fb932c5d7c
--- /dev/null
+++ b/test/test_exponential_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/exponential.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/exponential.hpp>
+extern "C" __global__ 
+void test_exponential_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::exponential_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_exponential_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_exponential_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_exponential_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::exponential_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 5f3ca8c3da194a66de69bbfee941798c777fbc5a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 16:15:26 -0400
Subject: [PATCH 323/399] Add NVRTC support to extreme value dist

---
 include/boost/math/distributions/extreme_value.hpp | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/distributions/extreme_value.hpp b/include/boost/math/distributions/extreme_value.hpp
index 0d638092b5..73454d29d4 100644
--- a/include/boost/math/distributions/extreme_value.hpp
+++ b/include/boost/math/distributions/extreme_value.hpp
@@ -10,12 +10,14 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/expm1.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 //
 // This is the maximum extreme value distribution, see
@@ -24,8 +26,11 @@
 // Also known as a Fisher-Tippett distribution, a log-Weibull
 // distribution or a Gumbel distribution.
 
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
 #include <utility>
 #include <cmath>
+#endif
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -280,7 +285,7 @@ BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<extreme_v
 }
 
 template <class RealType, class Policy>
-RealType quantile(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED RealType quantile(const complemented2_type<extreme_value_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 

From 7cd1f3b5250b5e62d2b629569eac3d26b4fddc15 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 16:15:48 -0400
Subject: [PATCH 324/399] Add NVRTC paths to log_max_value and log_min_value

---
 include/boost/math/tools/precision.hpp | 32 ++++++++++++++++----------
 1 file changed, 20 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 096a3265ae..1e4bf58ac0 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -208,26 +208,34 @@ struct log_limit_noexcept_traits : public log_limit_noexcept_traits_imp<T, boost
 template <class T>
 BOOST_MATH_GPU_ENABLED inline constexpr T log_max_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
 {
-#ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
-   return detail::log_max_value<T>(typename detail::log_limit_traits<T>::tag_type());
+#ifndef BOOST_MATH_HAS_NVRTC
+   #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
+      return detail::log_max_value<T>(typename detail::log_limit_traits<T>::tag_type());
+   #else
+      BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
+      BOOST_MATH_STD_USING
+      static const T val = log((boost::math::numeric_limits<T>::max)());
+      return val;
+   #endif
 #else
-   BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
-   BOOST_MATH_STD_USING
-   static const T val = log((boost::math::numeric_limits<T>::max)());
-   return val;
+   return log((boost::math::numeric_limits<T>::max)());
 #endif
 }
 
 template <class T>
 BOOST_MATH_GPU_ENABLED inline constexpr T log_min_value(BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T)) noexcept(detail::log_limit_noexcept_traits<T>::value)
 {
-#ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
-   return detail::log_min_value<T>(typename detail::log_limit_traits<T>::tag_type());
+#ifndef BOOST_MATH_HAS_NVRTC
+   #ifndef BOOST_NO_LIMITS_COMPILE_TIME_CONSTANTS
+      return detail::log_min_value<T>(typename detail::log_limit_traits<T>::tag_type());
+   #else
+      BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
+      BOOST_MATH_STD_USING
+      static const T val = log((boost::math::numeric_limits<T>::min)());
+      return val;
+   #endif
 #else
-   BOOST_MATH_ASSERT(::boost::math::numeric_limits<T>::is_specialized);
-   BOOST_MATH_STD_USING
-   static const T val = log((boost::math::numeric_limits<T>::min)());
-   return val;
+   return log((boost::math::numeric_limits<T>::min)());
 #endif
 }
 

From 069edffc6dbd350fc68ba033f0d0f1e405acc641 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 16:16:03 -0400
Subject: [PATCH 325/399] Add extreme value dist NVRTC testing

---
 test/nvrtc_jamfile                            |   7 +
 test/test_extreme_value_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++
 test/test_extreme_value_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++
 test/test_extreme_value_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++
 test/test_extreme_value_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++
 test/test_extreme_value_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_extreme_value_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_extreme_value_cdf_nvrtc_double.cpp
 create mode 100644 test/test_extreme_value_cdf_nvrtc_float.cpp
 create mode 100644 test/test_extreme_value_pdf_nvrtc_double.cpp
 create mode 100644 test/test_extreme_value_pdf_nvrtc_float.cpp
 create mode 100644 test/test_extreme_value_quan_nvrtc_double.cpp
 create mode 100644 test/test_extreme_value_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index da734ce070..9620115d85 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -38,6 +38,13 @@ run test_exponential_pdf_nvrtc_float.cpp ;
 run test_exponential_quan_nvrtc_double.cpp ;
 run test_exponential_quan_nvrtc_float.cpp ;
 
+run test_extreme_value_cdf_nvrtc_double.cpp ;
+run test_extreme_value_cdf_nvrtc_float.cpp ;
+run test_extreme_value_pdf_nvrtc_double.cpp ;
+run test_extreme_value_pdf_nvrtc_float.cpp ;
+run test_extreme_value_quan_nvrtc_double.cpp ;
+run test_extreme_value_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_extreme_value_cdf_nvrtc_double.cpp b/test/test_extreme_value_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..b3600b21bf
--- /dev/null
+++ b/test/test_extreme_value_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_extreme_value_cdf_nvrtc_float.cpp b/test/test_extreme_value_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..b3600b21bf
--- /dev/null
+++ b/test/test_extreme_value_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_extreme_value_pdf_nvrtc_double.cpp b/test/test_extreme_value_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..049f45d890
--- /dev/null
+++ b/test/test_extreme_value_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_extreme_value_pdf_nvrtc_float.cpp b/test/test_extreme_value_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..adbd263489
--- /dev/null
+++ b/test/test_extreme_value_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_extreme_value_quan_nvrtc_double.cpp b/test/test_extreme_value_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..239df99949
--- /dev/null
+++ b/test/test_extreme_value_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_extreme_value_quan_nvrtc_float.cpp b/test/test_extreme_value_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..fc9d8c5f41
--- /dev/null
+++ b/test/test_extreme_value_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/extreme_value.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/extreme_value.hpp>
+extern "C" __global__ 
+void test_extreme_value_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::extreme_value_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_extreme_value_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_extreme_value_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_extreme_value_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::extreme_value_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 9d19e56692a893e7d41bb18c512081764d2a9abe Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 17:03:02 -0400
Subject: [PATCH 326/399] Replace thurst::pair with cuda::std::pair for NVRTC
 compat

---
 include/boost/math/tools/config.hpp |  1 +
 include/boost/math/tools/tuple.hpp  | 44 ++++++-----------------------
 2 files changed, 9 insertions(+), 36 deletions(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index b67ce0ae91..3fa05b3511 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -674,6 +674,7 @@ namespace boost{ namespace math{
 #include <cuda.h>
 #include <cuda_runtime.h>
 #include <cuda/std/type_traits>
+#include <cuda/std/utility>
 
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index fba37fb4f8..26f81042f8 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -9,50 +9,22 @@
 
 #include <boost/math/tools/config.hpp>
 
-#ifdef BOOST_MATH_HAS_NVRTC
+#ifdef BOOST_MATH_ENABLE_CUDA
 
-namespace boost {
-namespace math {
-
-template <typename T, typename U>
-class pair
-{
-public:
-    T first;
-    U second;
-
-    BOOST_MATH_GPU_ENABLED pair(T x, U y) noexcept : first {x}, second {y} {}
-};
-
-template <typename T, typename U>
-BOOST_MATH_GPU_ENABLED auto make_pair(T x, U y) noexcept
-{
-    return pair(x, y);
-}
-
-} // namespace math
-} // namespace boost
-
-
-#elif defined(BOOST_MATH_ENABLE_CUDA)
-
-#include <thrust/pair.h>
-#include <thrust/tuple.h>
+#include <cuda/std/utility>
 
 namespace boost { 
 namespace math {
 
-using thrust::pair;
-using thrust::tuple;
+using cuda::std::pair;
+using cuda::std::tuple;
 
-using thrust::make_pair;
-using thrust::make_tuple;
+using cuda::std::make_pair;
 
-using thrust::tie;
-using thrust::get;
+using cuda::std::get;
 
-using thrust::tuple_size;
-using thrust::tuple_element;
+using cuda::std::tuple_size;
+using cuda::std::tuple_element;
 
 } // namespace math
 } // namespace boost

From f6369d8af5fccf3b62846c06fc8adf62555ae03a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 14 Aug 2024 17:13:29 -0400
Subject: [PATCH 327/399] Implement make_tuple since it's missing from cuda/std

---
 include/boost/math/tools/tuple.hpp | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)

diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index 26f81042f8..6a949d5e5a 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -11,6 +11,7 @@
 
 #ifdef BOOST_MATH_ENABLE_CUDA
 
+#include <boost/math/tools/type_traits.hpp>
 #include <cuda/std/utility>
 
 namespace boost { 
@@ -26,6 +27,31 @@ using cuda::std::get;
 using cuda::std::tuple_size;
 using cuda::std::tuple_element;
 
+namespace detail {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED T&& forward(boost::math::remove_reference_t<T>& arg) noexcept
+{
+    return static_cast<T&&>(arg);
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED T&& forward(boost::math::remove_reference_t<T>&& arg) noexcept
+{
+    static_assert(!boost::math::is_lvalue_reference<T>::value, "Cannot forward an rvalue as an lvalue.");
+    return static_cast<T&&>(arg);
+}
+
+} // namespace detail
+
+template <typename T, typename... Ts>
+BOOST_MATH_GPU_ENABLED auto make_tuple(T&& t, Ts&&... ts) 
+{
+    return cuda::std::tuple<boost::math::decay_t<T>, boost::math::decay_t<Ts>...>(
+        boost::math::detail::forward<T>(t), boost::math::detail::forward<Ts>(ts)...
+    );
+}
+
 } // namespace math
 } // namespace boost
 

From 6c78285c86add164fd7140b921697bbd07bcc456 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 09:42:17 -0400
Subject: [PATCH 328/399] Add more macro definitions

---
 include/boost/math/tools/config.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 3fa05b3511..364aa8f548 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -793,6 +793,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_GPU_ENABLED __host__ __device__
 
 #define BOOST_MATH_STATIC static
+#define BOOST_MATH_STATIC_LOCAL_VARIABLE
 
 #define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
 #define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T) 
@@ -800,6 +801,7 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
 #define BOOST_MATH_FORCEINLINE __forceinline__
 #define BOOST_MATH_STD_USING  
+#define BOOST_MATH_IF_CONSTEXPR if constexpr
 
 // This should be defined to nothing but since it is not specifically a math macro
 // we need to undef before proceeding

From 74f803ab74782e78474e7716eb7dac8464648c30 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 09:42:34 -0400
Subject: [PATCH 329/399] Add NVRTC support to holtsmark dist

---
 .../boost/math/distributions/holtsmark.hpp    | 47 +++++++++++--------
 1 file changed, 27 insertions(+), 20 deletions(-)

diff --git a/include/boost/math/distributions/holtsmark.hpp b/include/boost/math/distributions/holtsmark.hpp
index 8c976b8c82..04f5484f4e 100644
--- a/include/boost/math/distributions/holtsmark.hpp
+++ b/include/boost/math/distributions/holtsmark.hpp
@@ -15,16 +15,23 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/special_functions/cbrt.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/big_constant.hpp>
 #include <utility>
 #include <cmath>
+#endif
 
 namespace boost { namespace math {
 template <class RealType, class Policy>
@@ -33,7 +40,7 @@ class holtsmark_distribution;
 namespace detail {
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -263,7 +270,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealTyp
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -615,14 +622,14 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_plus_imp_prec(const RealTyp
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53> &tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>& tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return holtsmark_pdf_plus_imp_prec<RealType>(abs(x), tag);
@@ -655,7 +662,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp(const holtsmark_distrib
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -671,7 +678,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_pdf_imp(const holtsmark_distrib
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -920,7 +927,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealTyp
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1303,7 +1310,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_plus_imp_prec(const RealTyp
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
     }
@@ -1316,7 +1323,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x,
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? holtsmark_cdf_plus_imp_prec(x, tag) : 1 - holtsmark_cdf_plus_imp_prec(x, tag);
     }
@@ -1355,7 +1362,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp(const holtsmark_distrib
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -1371,7 +1378,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_cdf_imp(const holtsmark_distrib
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1634,7 +1641,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const R
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2230,7 +2237,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_upper_imp_prec(const R
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
         return !complement ? holtsmark_quantile_upper_imp_prec(1 - p, tag) : -holtsmark_quantile_upper_imp_prec(1 - p, tag);
@@ -2240,7 +2247,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealTyp
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
         return !complement ? holtsmark_quantile_upper_imp_prec(1 - p, tag) : -holtsmark_quantile_upper_imp_prec(1 - p, tag);
@@ -2277,7 +2284,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp(const holtsmark_di
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -2291,13 +2298,13 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_quantile_imp(const holtsmark_di
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.06944850513462440032);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0694485051346244003155800384542166381);
 }
@@ -2320,7 +2327,7 @@ BOOST_MATH_GPU_ENABLED inline RealType holtsmark_entropy_imp(const holtsmark_dis
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0

From 537e68fd7df499afe7e487ff455021f2b414c775 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 09:42:48 -0400
Subject: [PATCH 330/399] Add holtsmark dist NVRTC testing

---
 test/nvrtc_jamfile                        |   7 +
 test/test_holtsmark_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_holtsmark_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_holtsmark_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_holtsmark_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_holtsmark_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++++
 test/test_holtsmark_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_holtsmark_cdf_nvrtc_double.cpp
 create mode 100644 test/test_holtsmark_cdf_nvrtc_float.cpp
 create mode 100644 test/test_holtsmark_pdf_nvrtc_double.cpp
 create mode 100644 test/test_holtsmark_pdf_nvrtc_float.cpp
 create mode 100644 test/test_holtsmark_quan_nvrtc_double.cpp
 create mode 100644 test/test_holtsmark_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 9620115d85..93e6deddd9 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -45,6 +45,13 @@ run test_extreme_value_pdf_nvrtc_float.cpp ;
 run test_extreme_value_quan_nvrtc_double.cpp ;
 run test_extreme_value_quan_nvrtc_float.cpp ;
 
+run test_holtsmark_cdf_nvrtc_double.cpp ;
+run test_holtsmark_cdf_nvrtc_float.cpp ;
+run test_holtsmark_pdf_nvrtc_double.cpp ;
+run test_holtsmark_pdf_nvrtc_float.cpp ;
+run test_holtsmark_quan_nvrtc_double.cpp ;
+run test_holtsmark_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_holtsmark_cdf_nvrtc_double.cpp b/test/test_holtsmark_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..3b8c9ba946
--- /dev/null
+++ b/test/test_holtsmark_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_cdf_nvrtc_float.cpp b/test/test_holtsmark_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..a3ffec5942
--- /dev/null
+++ b/test/test_holtsmark_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_pdf_nvrtc_double.cpp b/test/test_holtsmark_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..a8355d368c
--- /dev/null
+++ b/test/test_holtsmark_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_pdf_nvrtc_float.cpp b/test/test_holtsmark_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..7a02d19832
--- /dev/null
+++ b/test/test_holtsmark_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_quan_nvrtc_double.cpp b/test/test_holtsmark_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..1c2cc61fa3
--- /dev/null
+++ b/test/test_holtsmark_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_quan_nvrtc_float.cpp b/test/test_holtsmark_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..a343f232e0
--- /dev/null
+++ b/test/test_holtsmark_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/holtsmark.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/holtsmark.hpp>
+extern "C" __global__ 
+void test_holtsmark_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::holtsmark_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_holtsmark_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_holtsmark_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_holtsmark_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::holtsmark_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 0197bee43f1337a906b900a3118091c07a38c13e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 09:59:34 -0400
Subject: [PATCH 331/399] Add NVRTC support to landau dist

---
 include/boost/math/distributions/landau.hpp | 74 ++++++++++++---------
 1 file changed, 41 insertions(+), 33 deletions(-)

diff --git a/include/boost/math/distributions/landau.hpp b/include/boost/math/distributions/landau.hpp
index 424931c276..129eca2879 100644
--- a/include/boost/math/distributions/landau.hpp
+++ b/include/boost/math/distributions/landau.hpp
@@ -15,15 +15,22 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/big_constant.hpp>
 #include <utility>
 #include <cmath>
+#endif
 
 namespace boost { namespace math {
 template <class RealType, class Policy>
@@ -32,7 +39,7 @@ class landau_distribution;
 namespace detail {
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -345,7 +352,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType&
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -873,7 +880,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_plus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1013,7 +1020,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1224,7 +1231,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_minus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53> &tag) {
     if (x >= 0) {
         return landau_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1237,7 +1244,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, co
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return landau_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1277,7 +1284,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp(const landau_distribution<
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -1293,7 +1300,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_pdf_imp(const landau_distribution<
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1600,7 +1607,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType&
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2123,7 +2130,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_plus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2266,7 +2273,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2482,7 +2489,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_minus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
     }
@@ -2495,7 +2502,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bo
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? landau_cdf_plus_imp_prec(x, tag) : 1 - landau_cdf_plus_imp_prec(x, tag);
     }
@@ -2535,7 +2542,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp(const landau_distribution<
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -2551,7 +2558,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_cdf_imp(const landau_distribution<
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2882,7 +2889,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const Real
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3542,7 +3549,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_lower_imp_prec(const Real
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3782,7 +3789,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const Real
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -4229,7 +4236,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_upper_imp_prec(const Real
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) 
     {
@@ -4240,7 +4247,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) 
     {
@@ -4279,7 +4286,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp(const landau_distribu
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -4293,13 +4300,13 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_quantile_imp(const landau_distribu
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-0.42931452986133525017);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.42931452986133525016556463510885028346);
 }
@@ -4328,7 +4335,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp(const landau_distribution
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -4342,13 +4349,13 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_mode_imp(const landau_distribution
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(0.57563014394507821440);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 0.57563014394507821439627930892257517269);
 }
@@ -4377,7 +4384,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp(const landau_distributi
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -4391,13 +4398,13 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_median_imp(const landau_distributi
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.37263644000448182448);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.3726364400044818244844049010588577710);
 }
@@ -4420,7 +4427,7 @@ BOOST_MATH_GPU_ENABLED inline RealType landau_entropy_imp(const landau_distribut
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -4445,12 +4452,13 @@ class landau_distribution
     BOOST_MATH_GPU_ENABLED landau_distribution(RealType l_location = 0, RealType l_scale = 1)
         : mu(l_location), c(l_scale)
     {
+        BOOST_MATH_STD_USING
+        
         constexpr auto function = "boost::math::landau_distribution<%1%>::landau_distribution";
         RealType result = 0;
         detail::check_location(function, l_location, &result, Policy());
         detail::check_scale(function, l_scale, &result, Policy());
 
-        using std::log;
         location_bias = -2 / constants::pi<RealType>() * log(l_scale);
     } // landau_distribution
 

From 9c3f6af1852cb7e7293cd1a4631136e6ce99b78c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 09:59:46 -0400
Subject: [PATCH 332/399] Add landau dist NVRTC testing

---
 test/nvrtc_jamfile                     |   7 +
 test/test_landau_cdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++++
 test/test_landau_cdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++++
 test/test_landau_pdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++++
 test/test_landau_pdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++++
 test/test_landau_quan_nvrtc_double.cpp | 191 +++++++++++++++++++++++++
 test/test_landau_quan_nvrtc_float.cpp  | 191 +++++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_landau_cdf_nvrtc_double.cpp
 create mode 100644 test/test_landau_cdf_nvrtc_float.cpp
 create mode 100644 test/test_landau_pdf_nvrtc_double.cpp
 create mode 100644 test/test_landau_pdf_nvrtc_float.cpp
 create mode 100644 test/test_landau_quan_nvrtc_double.cpp
 create mode 100644 test/test_landau_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 93e6deddd9..0ed1c9de61 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -52,6 +52,13 @@ run test_holtsmark_pdf_nvrtc_float.cpp ;
 run test_holtsmark_quan_nvrtc_double.cpp ;
 run test_holtsmark_quan_nvrtc_float.cpp ;
 
+run test_landau_cdf_nvrtc_double.cpp ;
+run test_landau_cdf_nvrtc_float.cpp ;
+run test_landau_pdf_nvrtc_double.cpp ;
+run test_landau_pdf_nvrtc_float.cpp ;
+run test_landau_quan_nvrtc_double.cpp ;
+run test_landau_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_landau_cdf_nvrtc_double.cpp b/test/test_landau_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f23a758e12
--- /dev/null
+++ b/test/test_landau_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_cdf_nvrtc_float.cpp b/test/test_landau_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..1a339724e8
--- /dev/null
+++ b/test/test_landau_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_pdf_nvrtc_double.cpp b/test/test_landau_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1e8df7d07e
--- /dev/null
+++ b/test/test_landau_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_pdf_nvrtc_float.cpp b/test/test_landau_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..1e8df7d07e
--- /dev/null
+++ b/test/test_landau_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_quan_nvrtc_double.cpp b/test/test_landau_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..f4a5b95534
--- /dev/null
+++ b/test/test_landau_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_quan_nvrtc_float.cpp b/test/test_landau_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..4a10b497cf
--- /dev/null
+++ b/test/test_landau_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/landau.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/landau.hpp>
+extern "C" __global__ 
+void test_landau_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::landau_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_landau_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_landau_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_landau_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::landau_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 97ae9f09b19b945583f5318bbc3e7228b4a5d09d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:15:21 -0400
Subject: [PATCH 333/399] Add NVRTC support to laplace dist

---
 include/boost/math/distributions/laplace.hpp | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/laplace.hpp b/include/boost/math/distributions/laplace.hpp
index 4d1fc46569..81a0abe1ab 100644
--- a/include/boost/math/distributions/laplace.hpp
+++ b/include/boost/math/distributions/laplace.hpp
@@ -25,7 +25,8 @@
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <limits>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost{ namespace math{
 

From 43c80b509c8245770e4e47f1cc32adcea63e46da Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:15:34 -0400
Subject: [PATCH 334/399] Add laplace dist NVRTC testing

---
 test/nvrtc_jamfile                      |   8 +
 test/test_laplace_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++++
 test/test_laplace_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++++
 test/test_laplace_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++++
 test/test_laplace_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++++
 test/test_laplace_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++++++
 test/test_laplace_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++++++
 7 files changed, 1154 insertions(+)
 create mode 100644 test/test_laplace_cdf_nvrtc_double.cpp
 create mode 100644 test/test_laplace_cdf_nvrtc_float.cpp
 create mode 100644 test/test_laplace_pdf_nvrtc_double.cpp
 create mode 100644 test/test_laplace_pdf_nvrtc_float.cpp
 create mode 100644 test/test_laplace_quan_nvrtc_double.cpp
 create mode 100644 test/test_laplace_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 0ed1c9de61..3a9ecb7396 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -59,6 +59,14 @@ run test_landau_pdf_nvrtc_float.cpp ;
 run test_landau_quan_nvrtc_double.cpp ;
 run test_landau_quan_nvrtc_float.cpp ;
 
+run test_laplace_cdf_nvrtc_double.cpp ;
+run test_laplace_cdf_nvrtc_float.cpp ;
+run test_laplace_pdf_nvrtc_double.cpp ;
+run test_laplace_pdf_nvrtc_float.cpp ;
+run test_laplace_quan_nvrtc_double.cpp ;
+run test_laplace_quan_nvrtc_float.cpp ;
+
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_laplace_cdf_nvrtc_double.cpp b/test/test_laplace_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..9d35b5862a
--- /dev/null
+++ b/test/test_laplace_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_laplace_cdf_nvrtc_float.cpp b/test/test_laplace_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..aacf59cb07
--- /dev/null
+++ b/test/test_laplace_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_laplace_pdf_nvrtc_double.cpp b/test/test_laplace_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..49c3864159
--- /dev/null
+++ b/test/test_laplace_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_laplace_pdf_nvrtc_float.cpp b/test/test_laplace_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..2100e2cdcd
--- /dev/null
+++ b/test/test_laplace_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_laplace_quan_nvrtc_double.cpp b/test/test_laplace_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..cf02db5a53
--- /dev/null
+++ b/test/test_laplace_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_laplace_quan_nvrtc_float.cpp b/test/test_laplace_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..36472aaa25
--- /dev/null
+++ b/test/test_laplace_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/laplace.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/laplace.hpp>
+extern "C" __global__ 
+void test_laplace_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::laplace_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_laplace_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_laplace_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_laplace_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::laplace_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 9442866e9d92dabda1a497c2e3ed293d41da32f9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:22:06 -0400
Subject: [PATCH 335/399] Add NVRTC support to logistic dist

---
 include/boost/math/distributions/logistic.hpp | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/distributions/logistic.hpp b/include/boost/math/distributions/logistic.hpp
index 4f94bd8a4f..56dc6e9f2f 100644
--- a/include/boost/math/distributions/logistic.hpp
+++ b/include/boost/math/distributions/logistic.hpp
@@ -11,12 +11,14 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <utility>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost { namespace math { 
 

From 97c8e9efd7a2e32eeb52a680d4f2d97d587a6606 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:22:19 -0400
Subject: [PATCH 336/399] Add logistic dist NVRTC testing

---
 test/nvrtc_jamfile                       |   6 +
 test/test_logistic_cdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++
 test/test_logistic_cdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++
 test/test_logistic_pdf_nvrtc_double.cpp  | 191 +++++++++++++++++++++++
 test/test_logistic_pdf_nvrtc_float.cpp   | 191 +++++++++++++++++++++++
 test/test_logistic_quan_nvrtc_double.cpp | 191 +++++++++++++++++++++++
 test/test_logistic_quan_nvrtc_float.cpp  | 191 +++++++++++++++++++++++
 7 files changed, 1152 insertions(+)
 create mode 100644 test/test_logistic_cdf_nvrtc_double.cpp
 create mode 100644 test/test_logistic_cdf_nvrtc_float.cpp
 create mode 100644 test/test_logistic_pdf_nvrtc_double.cpp
 create mode 100644 test/test_logistic_pdf_nvrtc_float.cpp
 create mode 100644 test/test_logistic_quan_nvrtc_double.cpp
 create mode 100644 test/test_logistic_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 3a9ecb7396..c0af6e7fa1 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -66,6 +66,12 @@ run test_laplace_pdf_nvrtc_float.cpp ;
 run test_laplace_quan_nvrtc_double.cpp ;
 run test_laplace_quan_nvrtc_float.cpp ;
 
+run test_logistic_cdf_nvrtc_double.cpp ;
+run test_logistic_cdf_nvrtc_float.cpp ;
+run test_logistic_pdf_nvrtc_double.cpp ;
+run test_logistic_pdf_nvrtc_float.cpp ;
+run test_logistic_quan_nvrtc_double.cpp ;
+run test_logistic_quan_nvrtc_float.cpp ;
 
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
diff --git a/test/test_logistic_cdf_nvrtc_double.cpp b/test/test_logistic_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..5548dc412d
--- /dev/null
+++ b/test/test_logistic_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_logistic_cdf_nvrtc_float.cpp b/test/test_logistic_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..ea65cc97cb
--- /dev/null
+++ b/test/test_logistic_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_logistic_pdf_nvrtc_double.cpp b/test/test_logistic_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..d287225cf6
--- /dev/null
+++ b/test/test_logistic_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_logistic_pdf_nvrtc_float.cpp b/test/test_logistic_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..9339a6db36
--- /dev/null
+++ b/test/test_logistic_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_logistic_quan_nvrtc_double.cpp b/test/test_logistic_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..f763db82cc
--- /dev/null
+++ b/test/test_logistic_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_logistic_quan_nvrtc_float.cpp b/test/test_logistic_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..b14c3c5daa
--- /dev/null
+++ b/test/test_logistic_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/logistic.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/logistic.hpp>
+extern "C" __global__ 
+void test_logistic_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::logistic_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_logistic_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_logistic_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_logistic_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::logistic_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 4bcfb1ceb22bbf3decf3a968dbb1197c30d81b76 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:40:15 -0400
Subject: [PATCH 337/399] Disable whole file on NVRTC

---
 include/boost/math/tools/big_constant.hpp | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/include/boost/math/tools/big_constant.hpp b/include/boost/math/tools/big_constant.hpp
index 2fdfec7826..0d54976bc4 100644
--- a/include/boost/math/tools/big_constant.hpp
+++ b/include/boost/math/tools/big_constant.hpp
@@ -8,6 +8,12 @@
 #define BOOST_MATH_TOOLS_BIG_CONSTANT_HPP
 
 #include <boost/math/tools/config.hpp>
+
+// On NVRTC we don't need any of this
+// We just have a simple definition of the macro since the largest float
+// type on the platform is a 64-bit double
+#ifndef BOOST_MATH_HAS_NVRTC 
+
 #ifndef BOOST_MATH_STANDALONE
 #include <boost/lexical_cast.hpp>
 #endif
@@ -94,5 +100,7 @@ inline constexpr T make_big_value(largest_float, const char* s, std::false_type
 
 }}} // namespaces
 
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif
 

From d7961fb69a69f25030680ddef1ac68b3d1b53622 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:40:28 -0400
Subject: [PATCH 338/399] Add NVRTC support to mapairy dist

---
 include/boost/math/distributions/mapairy.hpp | 69 +++++++++++---------
 1 file changed, 37 insertions(+), 32 deletions(-)

diff --git a/include/boost/math/distributions/mapairy.hpp b/include/boost/math/distributions/mapairy.hpp
index 542cf6da38..8bf1f990c1 100644
--- a/include/boost/math/distributions/mapairy.hpp
+++ b/include/boost/math/distributions/mapairy.hpp
@@ -15,7 +15,6 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
@@ -23,8 +22,14 @@
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/special_functions/cbrt.hpp>
-#include <utility>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/tools/promotion.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
 #include <cmath>
+#endif
 
 namespace boost { namespace math {
 template <class RealType, class Policy>
@@ -33,7 +38,7 @@ class mapairy_distribution;
 namespace detail {
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -255,7 +260,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType&
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -584,7 +589,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_plus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -757,7 +762,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1048,7 +1053,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_minus_imp_prec(const RealType
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53> &tag) {
     if (x >= 0) {
         return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1061,7 +1066,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, c
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return mapairy_pdf_plus_imp_prec<RealType>(x, tag);
     }
@@ -1100,7 +1105,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp(const mapairy_distributio
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -1116,7 +1121,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_pdf_imp(const mapairy_distributio
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1331,7 +1336,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType&
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1656,7 +1661,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_plus_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1833,7 +1838,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2133,7 +2138,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_minus_imp_prec(const RealType
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
     }
@@ -2146,7 +2151,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, b
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? mapairy_cdf_plus_imp_prec(x, tag) : 1 - mapairy_cdf_plus_imp_prec(x, tag);
     }
@@ -2185,7 +2190,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp(const mapairy_distributio
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -2201,7 +2206,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_cdf_imp(const mapairy_distributio
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2534,7 +2539,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const Rea
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3236,7 +3241,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_lower_imp_prec(const Rea
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3440,7 +3445,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const Rea
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -3838,7 +3843,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_upper_imp_prec(const Rea
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
         return !complement ? mapairy_quantile_upper_imp_prec(1 - p, tag) : mapairy_quantile_lower_imp_prec(1 - p, tag);
@@ -3848,7 +3853,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType&
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
         return !complement ? mapairy_quantile_upper_imp_prec(1 - p, tag) : mapairy_quantile_lower_imp_prec(1 - p, tag);
@@ -3885,7 +3890,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp(const mapairy_distri
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -3899,13 +3904,13 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_quantile_imp(const mapairy_distri
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-1.16158727113597068525);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -1.1615872711359706852500000803029112987);
 }
@@ -3933,7 +3938,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp(const mapairy_distributi
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -3947,13 +3952,13 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_mode_imp(const mapairy_distributi
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(-0.71671068545502205332);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, -0.71671068545502205331700196278067230944440);
 }
@@ -3981,7 +3986,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp(const mapairy_distribu
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -3995,13 +4000,13 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_median_imp(const mapairy_distribu
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(2.00727681841065634600);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 2.0072768184106563460003025875575283708);
 }
@@ -4024,7 +4029,7 @@ BOOST_MATH_GPU_ENABLED inline RealType mapairy_entropy_imp(const mapairy_distrib
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0

From 92a08fdd4d189f3618cd0c0a072322f56e3c7c64 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:40:47 -0400
Subject: [PATCH 339/399] Add mapairy dist NVRTC testing

---
 test/nvrtc_jamfile                      |   7 +
 test/test_mapairy_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++++
 test/test_mapairy_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++++
 test/test_mapairy_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++++
 test/test_mapairy_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++++
 test/test_mapairy_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++++++
 test/test_mapairy_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_mapairy_cdf_nvrtc_double.cpp
 create mode 100644 test/test_mapairy_cdf_nvrtc_float.cpp
 create mode 100644 test/test_mapairy_pdf_nvrtc_double.cpp
 create mode 100644 test/test_mapairy_pdf_nvrtc_float.cpp
 create mode 100644 test/test_mapairy_quan_nvrtc_double.cpp
 create mode 100644 test/test_mapairy_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index c0af6e7fa1..fa25d02261 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -73,6 +73,13 @@ run test_logistic_pdf_nvrtc_float.cpp ;
 run test_logistic_quan_nvrtc_double.cpp ;
 run test_logistic_quan_nvrtc_float.cpp ;
 
+run test_mapairy_cdf_nvrtc_double.cpp ;
+run test_mapairy_cdf_nvrtc_float.cpp ;
+run test_mapairy_pdf_nvrtc_double.cpp ;
+run test_mapairy_pdf_nvrtc_float.cpp ;
+run test_mapairy_quan_nvrtc_double.cpp ;
+run test_mapairy_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_mapairy_cdf_nvrtc_double.cpp b/test/test_mapairy_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..87e7948b72
--- /dev/null
+++ b/test/test_mapairy_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_mapairy_cdf_nvrtc_float.cpp b/test/test_mapairy_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..d84404c5e1
--- /dev/null
+++ b/test/test_mapairy_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_mapairy_pdf_nvrtc_double.cpp b/test/test_mapairy_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..5f461d6d13
--- /dev/null
+++ b/test/test_mapairy_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_mapairy_pdf_nvrtc_float.cpp b/test/test_mapairy_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..39eb4152d0
--- /dev/null
+++ b/test/test_mapairy_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_mapairy_quan_nvrtc_double.cpp b/test/test_mapairy_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..43ac17c848
--- /dev/null
+++ b/test/test_mapairy_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_mapairy_quan_nvrtc_float.cpp b/test/test_mapairy_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..a127843e93
--- /dev/null
+++ b/test/test_mapairy_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/mapairy.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/mapairy.hpp>
+extern "C" __global__ 
+void test_mapairy_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::mapairy_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_mapairy_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_mapairy_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_mapairy_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::mapairy_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From a9cf968292bae7d4b7257c19d77d8fe4bf37e3a4 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:50:38 -0400
Subject: [PATCH 340/399] Add NVRTC support to saspoint5 dist

---
 .../boost/math/distributions/saspoint5.hpp    | 46 +++++++++++--------
 1 file changed, 26 insertions(+), 20 deletions(-)

diff --git a/include/boost/math/distributions/saspoint5.hpp b/include/boost/math/distributions/saspoint5.hpp
index 3e78fca974..7846b99560 100644
--- a/include/boost/math/distributions/saspoint5.hpp
+++ b/include/boost/math/distributions/saspoint5.hpp
@@ -15,15 +15,21 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
-#include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/big_constant.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/detail/derived_accessors.hpp>
 #include <boost/math/tools/rational.hpp>
-#include <utility>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/distributions/fwd.hpp>
 #include <cmath>
+#endif
 
 namespace boost { namespace math {
 template <class RealType, class Policy>
@@ -32,7 +38,7 @@ class saspoint5_distribution;
 namespace detail {
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -337,7 +343,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealTyp
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -849,14 +855,14 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_plus_imp_prec(const RealTyp
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 53> &tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53> &tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>& tag) {
     BOOST_MATH_STD_USING // for ADL of std functions
 
     return saspoint5_pdf_plus_imp_prec<RealType>(abs(x), tag);
@@ -889,7 +895,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp(const saspoint5_distrib
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -905,7 +911,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_pdf_imp(const saspoint5_distrib
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1163,7 +1169,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealTyp
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealType& x, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1642,7 +1648,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_plus_imp_prec(const RealTyp
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 53>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 53>& tag) {
     if (x >= 0) {
         return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
     }
@@ -1655,7 +1661,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x,
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const std::integral_constant<int, 113>& tag) {
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp_prec(const RealType& x, bool complement, const boost::math::integral_constant<int, 113>& tag) {
     if (x >= 0) {
         return complement ? saspoint5_cdf_plus_imp_prec(x, tag) : 1 - saspoint5_cdf_plus_imp_prec(x, tag);
     }
@@ -1694,7 +1700,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp(const saspoint5_distrib
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -1710,7 +1716,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_cdf_imp(const saspoint5_distrib
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 53>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -1994,7 +2000,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const R
 
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const RealType& p, const boost::math::integral_constant<int, 113>&)
 {
     BOOST_MATH_STD_USING
     RealType result;
@@ -2493,7 +2499,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_upper_imp_prec(const R
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 53>& tag)
 {
     if (p > 0.5) {
         return !complement ? saspoint5_quantile_upper_imp_prec(1 - p, tag) : -saspoint5_quantile_upper_imp_prec(1 - p, tag);
@@ -2503,7 +2509,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealTyp
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp_prec(const RealType& p, bool complement, const boost::math::integral_constant<int, 113>& tag)
 {
     if (p > 0.5) {
         return !complement ? saspoint5_quantile_upper_imp_prec(1 - p, tag) : -saspoint5_quantile_upper_imp_prec(1 - p, tag);
@@ -2540,7 +2546,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp(const saspoint5_di
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0
@@ -2554,13 +2560,13 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_quantile_imp(const saspoint5_di
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const boost::math::integral_constant<int, 53>&)
 {
     return static_cast<RealType>(3.63992444568030649573);
 }
 
 template <class RealType>
-BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp_prec(const boost::math::integral_constant<int, 113>&)
 {
     return BOOST_MATH_BIG_CONSTANT(RealType, 113, 3.6399244456803064957308496039071853510);
 }
@@ -2583,7 +2589,7 @@ BOOST_MATH_GPU_ENABLED inline RealType saspoint5_entropy_imp(const saspoint5_dis
 
     typedef typename tools::promote_args<RealType>::type result_type;
     typedef typename policies::precision<result_type, Policy>::type precision_type;
-    typedef std::integral_constant<int,
+    typedef boost::math::integral_constant<int,
         precision_type::value <= 0 ? 0 :
         precision_type::value <= 53 ? 53 :
         precision_type::value <= 113 ? 113 : 0

From 42ccc22fa3c7340a0fb4f40edd7d85ebe58fed83 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 10:50:50 -0400
Subject: [PATCH 341/399] Add saspoint5 NVRTC testing

---
 test/nvrtc_jamfile                        |   7 +
 test/test_saspoint5_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_saspoint5_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_saspoint5_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++++++
 test/test_saspoint5_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++++++
 test/test_saspoint5_quan_nvrtc_double.cpp | 191 ++++++++++++++++++++++
 test/test_saspoint5_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++++++
 7 files changed, 1153 insertions(+)
 create mode 100644 test/test_saspoint5_cdf_nvrtc_double.cpp
 create mode 100644 test/test_saspoint5_cdf_nvrtc_float.cpp
 create mode 100644 test/test_saspoint5_pdf_nvrtc_double.cpp
 create mode 100644 test/test_saspoint5_pdf_nvrtc_float.cpp
 create mode 100644 test/test_saspoint5_quan_nvrtc_double.cpp
 create mode 100644 test/test_saspoint5_quan_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index fa25d02261..8d33eabb55 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -80,6 +80,13 @@ run test_mapairy_pdf_nvrtc_float.cpp ;
 run test_mapairy_quan_nvrtc_double.cpp ;
 run test_mapairy_quan_nvrtc_float.cpp ;
 
+run test_saspoint5_cdf_nvrtc_double.cpp ;
+run test_saspoint5_cdf_nvrtc_float.cpp ;
+run test_saspoint5_pdf_nvrtc_double.cpp ;
+run test_saspoint5_pdf_nvrtc_float.cpp ;
+run test_saspoint5_quan_nvrtc_double.cpp ;
+run test_saspoint5_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
diff --git a/test/test_saspoint5_cdf_nvrtc_double.cpp b/test/test_saspoint5_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..ff2067fa0c
--- /dev/null
+++ b/test/test_saspoint5_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_saspoint5_cdf_nvrtc_float.cpp b/test/test_saspoint5_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..11c816da1c
--- /dev/null
+++ b/test/test_saspoint5_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_saspoint5_pdf_nvrtc_double.cpp b/test/test_saspoint5_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4c74443836
--- /dev/null
+++ b/test/test_saspoint5_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_saspoint5_pdf_nvrtc_float.cpp b/test/test_saspoint5_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..8cd93aaa94
--- /dev/null
+++ b/test/test_saspoint5_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_saspoint5_quan_nvrtc_double.cpp b/test/test_saspoint5_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..631ac4b243
--- /dev/null
+++ b/test/test_saspoint5_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_saspoint5_quan_nvrtc_float.cpp b/test/test_saspoint5_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..fa152622e6
--- /dev/null
+++ b/test/test_saspoint5_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/saspoint5.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/saspoint5.hpp>
+extern "C" __global__ 
+void test_saspoint5_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::saspoint5_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_saspoint5_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_saspoint5_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_saspoint5_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::saspoint5_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 889d0e20e109b8e983bc1abb36f94f62ee4de7e9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 11:37:14 -0400
Subject: [PATCH 342/399] Add NVRTC support to  modf

---
 include/boost/math/special_functions/modf.hpp | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/special_functions/modf.hpp b/include/boost/math/special_functions/modf.hpp
index e08945dca5..6e372ec9a3 100644
--- a/include/boost/math/special_functions/modf.hpp
+++ b/include/boost/math/special_functions/modf.hpp
@@ -11,9 +11,13 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/policies/policy.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
+#endif
 
 namespace boost{ namespace math{
 

From 4822f21fb6df8a3b33cdc396b91dd1d04ab3eff2 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 11:37:25 -0400
Subject: [PATCH 343/399] Add modf NVRTC testing

---
 test/nvrtc_jamfile              |   4 +
 test/test_modf_nvrtc_double.cpp | 200 ++++++++++++++++++++++++++++++++
 test/test_modf_nvrtc_float.cpp  | 200 ++++++++++++++++++++++++++++++++
 3 files changed, 404 insertions(+)
 create mode 100644 test/test_modf_nvrtc_double.cpp
 create mode 100644 test/test_modf_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 8d33eabb55..e2fdaba52c 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -88,6 +88,7 @@ run test_saspoint5_quan_nvrtc_double.cpp ;
 run test_saspoint5_quan_nvrtc_float.cpp ;
 
 # Special Functions
+# Beta
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
 run test_cos_pi_nvrtc_double.cpp ;
@@ -110,10 +111,13 @@ run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
 run test_log1p_nvrtc_double.cpp ;
 run test_log1p_nvrtc_float.cpp ;
+run test_modf_nvrtc_double.cpp ;
+run test_modf_nvrtc_float.cpp ;
 run test_round_nvrtc_double.cpp ;
 run test_round_nvrtc_float.cpp ;
 run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
 run test_sin_pi_nvrtc_double.cpp ;
 run test_sin_pi_nvrtc_float.cpp ;
+# Trigamma
 run test_trunc_nvrtc_double.cpp ;
diff --git a/test/test_modf_nvrtc_double.cpp b/test/test_modf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f172dd52c1
--- /dev/null
+++ b/test/test_modf_nvrtc_double.cpp
@@ -0,0 +1,200 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/modf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/modf.hpp>
+extern "C" __global__ 
+void test_modf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    float_type fract;
+    int i_part;
+    long l_part;
+    long long ll_part;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::modf(in1[i], &fract) + 
+                 boost::math::modf(in1[i], &i_part) + 
+                 boost::math::modf(in1[i], &l_part) + 
+                 boost::math::modf(in1[i], &ll_part);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_modf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_modf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_modf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            float_type fract;
+            const auto res = 4 * boost::math::modf(h_in1[i], &fract);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_modf_nvrtc_float.cpp b/test/test_modf_nvrtc_float.cpp
new file mode 100644
index 0000000000..1dcd3c0810
--- /dev/null
+++ b/test/test_modf_nvrtc_float.cpp
@@ -0,0 +1,200 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/modf.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/modf.hpp>
+extern "C" __global__ 
+void test_modf_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    float_type fract;
+    int i_part;
+    long l_part;
+    long long ll_part;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::modf(in1[i], &fract) + 
+                 boost::math::modf(in1[i], &i_part) + 
+                 boost::math::modf(in1[i], &l_part) + 
+                 boost::math::modf(in1[i], &ll_part);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_modf_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_modf_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_modf_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            float_type fract;
+            const auto res = 4 * boost::math::modf(h_in1[i], &fract);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From dcac57124e744a12f6b5541a9dc18894af744f98 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:17:13 -0400
Subject: [PATCH 344/399] Fix including header

---
 include/boost/math/tools/type_traits.hpp | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/tools/type_traits.hpp b/include/boost/math/tools/type_traits.hpp
index a37e8e7ebb..a13332797b 100644
--- a/include/boost/math/tools/type_traits.hpp
+++ b/include/boost/math/tools/type_traits.hpp
@@ -12,13 +12,13 @@
 
 #include <boost/math/tools/config.hpp>
 
-namespace boost {
-namespace math {
-
 #ifdef BOOST_MATH_ENABLE_CUDA
 
 #include <cuda/std/type_traits>
 
+namespace boost {
+namespace math {
+
 // Helper classes
 using cuda::std::integral_constant;
 using cuda::std::true_type;
@@ -163,6 +163,9 @@ using cuda::std::underlying_type_t;
 
 #include <type_traits>
 
+namespace boost {
+namespace math {
+
 // Helper classes
 using std::integral_constant;
 using std::true_type;

From 67e246e089a8c6af5a82211a43421ad91cb0cb85 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:35:30 -0400
Subject: [PATCH 345/399] Implement CUDA friendly cstdint

---
 include/boost/math/tools/cstdint.hpp | 105 +++++++++++++++++++++++++++
 1 file changed, 105 insertions(+)
 create mode 100644 include/boost/math/tools/cstdint.hpp

diff --git a/include/boost/math/tools/cstdint.hpp b/include/boost/math/tools/cstdint.hpp
new file mode 100644
index 0000000000..f96e85c879
--- /dev/null
+++ b/include/boost/math/tools/cstdint.hpp
@@ -0,0 +1,105 @@
+//  Copyright (c) 2024 Matt Borland
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_MATH_TOOLS_CSTDINT
+#define BOOST_MATH_TOOLS_CSTDINT
+
+#include <boost/math/tools/config.hpp>
+
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+#include <cuda/std/cstdint>
+
+namespace boost {
+namespace math {
+
+using cuda::std::int8_t;
+using cuda::std::int16_t;
+using cuda::std::int32_t;
+using cuda::std::int64_t;
+
+using cuda::std::int_fast8_t;
+using cuda::std::int_fast16_t;
+using cuda::std::int_fast32_t;
+using cuda::std::int_fast64_t;
+
+using cuda::std::int_least8_t;
+using cuda::std::int_least16_t;
+using cuda::std::int_least32_t;
+using cuda::std::int_least64_t;
+
+using cuda::std::intmax_t;
+using cuda::std::intptr_t;
+
+using cuda::std::uint8_t;
+using cuda::std::uint16_t;
+using cuda::std::uint32_t;
+using cuda::std::uint64_t;
+
+using cuda::std::uint_fast8_t;
+using cuda::std::uint_fast16_t;
+using cuda::std::uint_fast32_t;
+using cuda::std::uint_fast64_t;
+
+using cuda::std::uint_least8_t;
+using cuda::std::uint_least16_t;
+using cuda::std::uint_least32_t;
+using cuda::std::uint_least64_t;
+
+using cuda::std::uintmax_t;
+using cuda::std::uintptr_t;
+
+using size_t = unsigned long;
+
+#else
+
+namespace boost {
+namespace math {
+
+using std::int8_t;
+using std::int16_t;
+using std::int32_t;
+using std::int64_t;
+
+using std::int_fast8_t;
+using std::int_fast16_t;
+using std::int_fast32_t;
+using std::int_fast64_t;
+
+using std::int_least8_t;
+using std::int_least16_t;
+using std::int_least32_t;
+using std::int_least64_t;
+
+using std::intmax_t;
+using std::intptr_t;
+
+using std::uint8_t;
+using std::uint16_t;
+using std::uint32_t;
+using std::uint64_t;
+
+using std::uint_fast8_t;
+using std::uint_fast16_t;
+using std::uint_fast32_t;
+using std::uint_fast64_t;
+
+using std::uint_least8_t;
+using std::uint_least16_t;
+using std::uint_least32_t;
+using std::uint_least64_t;
+
+using std::uintmax_t;
+using std::uintptr_t;
+
+using std::size_t;
+
+#endif
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_TOOLS_CSTDINT

From e8bc5ced0087764dcf6f7698375e5046c9237fc5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:35:45 -0400
Subject: [PATCH 346/399] Add cuda header to ensure proper include order

---
 include/boost/math/tools/config.hpp | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 364aa8f548..e97ceaa742 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -675,6 +675,7 @@ namespace boost{ namespace math{
 #include <cuda_runtime.h>
 #include <cuda/std/type_traits>
 #include <cuda/std/utility>
+#include <cuda/std/cstdint>
 
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
@@ -827,6 +828,8 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_SIZE_T unsigned long
 #define BOOST_MATH_UINTMAX_T unsigned long
 
+#define BOOST_MATH_INT_VALUE_SUFFIX(RV, SUF) RV##SUF
+
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr
 #else

From 4f6b1644207a62ff79dbc25de5d28a04b4c64f71 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:42:44 -0400
Subject: [PATCH 347/399] Fix style for consistency

---
 include/boost/math/special_functions/gamma.hpp | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 0d5e5f0b23..afb8e97282 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -14,9 +14,10 @@
 #pragma once
 #endif
 
-#ifndef __CUDACC_RTC__
-
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/fraction.hpp>
 #include <boost/math/tools/precision.hpp>

From 32b563f60d56cd7fd19650204f6e4c10f18c269d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:43:03 -0400
Subject: [PATCH 348/399] Add CUDA support for complex num detection

---
 include/boost/math/tools/complex.hpp | 19 ++++++++++++++++++-
 1 file changed, 18 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/complex.hpp b/include/boost/math/tools/complex.hpp
index d462ca8092..f93d2958d1 100644
--- a/include/boost/math/tools/complex.hpp
+++ b/include/boost/math/tools/complex.hpp
@@ -10,9 +10,17 @@
 #ifndef BOOST_MATH_TOOLS_COMPLEX_HPP
 #define BOOST_MATH_TOOLS_COMPLEX_HPP
 
-#include <utility>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/is_detected.hpp>
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+#include <cuda/std/utility>
+#endif
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <utility>
+#endif
+
 namespace boost {
    namespace math {
       namespace tools {
@@ -24,12 +32,21 @@ namespace boost {
             static constexpr bool value = false;
          };
 
+         #ifndef BOOST_MATH_ENABLE_CUDA
          template <typename T>
          struct is_complex_type_impl<T, void_t<decltype(std::declval<T>().real()), 
                                                decltype(std::declval<T>().imag())>>
          {
             static constexpr bool value = true;
          };
+         #else
+         template <typename T>
+         struct is_complex_type_impl<T, void_t<decltype(cuda::std::declval<T>().real()), 
+                                               decltype(cuda::std::declval<T>().imag())>>
+         {
+            static constexpr bool value = true;
+         };
+         #endif
          } // Namespace detail
 
          template <typename T>

From 2bea2bb572f99698f98e304fecf21def7eec13df Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:43:13 -0400
Subject: [PATCH 349/399] Convert to our types

---
 include/boost/math/tools/is_detected.hpp | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/include/boost/math/tools/is_detected.hpp b/include/boost/math/tools/is_detected.hpp
index 8dfe86b740..93fa96f60b 100644
--- a/include/boost/math/tools/is_detected.hpp
+++ b/include/boost/math/tools/is_detected.hpp
@@ -8,7 +8,7 @@
 #ifndef BOOST_MATH_TOOLS_IS_DETECTED_HPP
 #define BOOST_MATH_TOOLS_IS_DETECTED_HPP
 
-#include <type_traits>
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost { namespace math { namespace tools {
 
@@ -20,14 +20,14 @@ namespace detail {
 template <typename Default, typename AlwaysVoid, template<typename...> class Op, typename... Args>
 struct detector
 {
-    using value_t = std::false_type;
+    using value_t = boost::math::false_type;
     using type = Default;
 };
 
 template <typename Default, template<typename...> class Op, typename... Args>
 struct detector<Default, void_t<Op<Args...>>, Op, Args...>
 {
-    using value_t = std::true_type;
+    using value_t = boost::math::true_type;
     using type = Op<Args...>;
 };
 

From f519e4e3da224acfb6884ec0e3a1f5f5660957b5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:43:29 -0400
Subject: [PATCH 350/399] Disable on NVRTC for now

---
 include/boost/math/tools/fraction.hpp | 30 ++++++++++++++-------------
 include/boost/math/tools/roots.hpp    |  8 ++++++-
 2 files changed, 23 insertions(+), 15 deletions(-)

diff --git a/include/boost/math/tools/fraction.hpp b/include/boost/math/tools/fraction.hpp
index 1970e5ca3f..c201a91b6c 100644
--- a/include/boost/math/tools/fraction.hpp
+++ b/include/boost/math/tools/fraction.hpp
@@ -12,6 +12,8 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/complex.hpp>
@@ -25,10 +27,10 @@ namespace detail
 {
 
    template <typename T>
-   struct is_pair : public std::false_type{};
+   struct is_pair : public boost::math::false_type{};
 
    template <typename T, typename U>
-   struct is_pair<boost::math::pair<T,U>> : public std::true_type{};
+   struct is_pair<boost::math::pair<T,U>> : public boost::math::true_type{};
 
    template <typename Gen>
    struct fraction_traits_simple
@@ -110,7 +112,7 @@ namespace detail {
 //
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
       noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
       #ifndef BOOST_MATH_ENABLE_SYCL
       // SYCL can not handle this condition so we only check float on that platform
@@ -140,7 +142,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    C = f;
    D = 0;
 
-   std::uintmax_t counter(max_terms);
+   BOOST_MATH_UINTMAX_T counter(max_terms);
    do{
       v = g();
       D = traits::b(v) + traits::a(v) * D;
@@ -162,7 +164,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 } // namespace detail
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
          #ifndef BOOST_MATH_ENABLE_SYCL
          && noexcept(std::declval<Gen>()())
@@ -180,7 +182,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    #endif
    )
 {
-   std::uintmax_t max_terms = (std::numeric_limits<std::uintmax_t>::max)();
+   BOOST_MATH_UINTMAX_T max_terms = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
@@ -198,12 +200,12 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    using result_type = typename traits::result_type;
 
    result_type factor = ldexp(1.0f, 1 - bits); // 1 / pow(result_type(2), bits);
-   std::uintmax_t max_terms = (std::numeric_limits<std::uintmax_t>::max)();
+   BOOST_MATH_UINTMAX_T max_terms = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, BOOST_MATH_UINTMAX_T& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -236,7 +238,7 @@ namespace detail {
 // Note that the first a1 and b1 returned by generator Gen are both used.
 //
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -266,7 +268,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    C = f;
    D = 0;
 
-   std::uintmax_t counter(max_terms);
+   BOOST_MATH_UINTMAX_T counter(max_terms);
 
    do{
       v = g();
@@ -289,7 +291,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 } // namespace detail
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -307,7 +309,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    #endif
    )
 {
-   std::uintmax_t max_iter = (std::numeric_limits<std::uintmax_t>::max)();
+   BOOST_MATH_UINTMAX_T max_iter = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
@@ -325,13 +327,13 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    typedef typename traits::result_type result_type;
 
    result_type factor = ldexp(1.0f, 1-bits); // 1 / pow(result_type(2), bits);
-   std::uintmax_t max_iter = (std::numeric_limits<std::uintmax_t>::max)();
+   BOOST_MATH_UINTMAX_T max_iter = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
 
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
 template <typename Gen>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, std::uintmax_t& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, BOOST_MATH_UINTMAX_T& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
diff --git a/include/boost/math/tools/roots.hpp b/include/boost/math/tools/roots.hpp
index 97e67fae95..8f36aa22df 100644
--- a/include/boost/math/tools/roots.hpp
+++ b/include/boost/math/tools/roots.hpp
@@ -9,6 +9,11 @@
 #ifdef _MSC_VER
 #pragma once
 #endif
+
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC // Disabled for now
+
 #include <boost/math/tools/complex.hpp> // test for multiprecision types in complex Newton
 
 #include <utility>
@@ -16,7 +21,6 @@
 #include <tuple>
 #include <cstdint>
 
-#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/cxx03_warn.hpp>
 
 #include <boost/math/special_functions/sign.hpp>
@@ -1025,4 +1029,6 @@ inline std::pair<typename tools::promote_args<T1, T2, T3>::type, typename tools:
 } // namespace math
 } // namespace boost
 
+#endif // BOOST_MATH_HAS_NVRTC
+
 #endif // BOOST_MATH_TOOLS_NEWTON_SOLVER_HPP

From 3273f31c675043e5c31f3959627520cda8a5c73b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:43:44 -0400
Subject: [PATCH 351/399] Add CUDA support to lanczos

---
 .../boost/math/special_functions/lanczos.hpp  | 346 +++++++++---------
 1 file changed, 175 insertions(+), 171 deletions(-)

diff --git a/include/boost/math/special_functions/lanczos.hpp b/include/boost/math/special_functions/lanczos.hpp
index b804bf8294..0ec24bddbf 100644
--- a/include/boost/math/special_functions/lanczos.hpp
+++ b/include/boost/math/special_functions/lanczos.hpp
@@ -11,12 +11,16 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-#include <boost/math/tools/big_constant.hpp>
 #include <boost/math/tools/rational.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/policies/policy.hpp>
-#include <limits>
-#include <type_traits>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/tools/big_constant.hpp>
 #include <cstdint>
+#endif
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -59,7 +63,7 @@ BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const L&)
 // Max experimental error (with arbitrary precision arithmetic) 9.516e-12
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos6 : public std::integral_constant<int, 35>
+struct lanczos6 : public boost::math::integral_constant<int, 35>
 {
    //
    // Produces slightly better than float precision when evaluated at
@@ -77,13 +81,13 @@ struct lanczos6 : public std::integral_constant<int, 35>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 63.99951844938187085666201263218840287667)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 2.506628274631006311133031631822390264407))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
-         static_cast<std::uint16_t>(0u),
-         static_cast<std::uint16_t>(24u),
-         static_cast<std::uint16_t>(50u),
-         static_cast<std::uint16_t>(35u),
-         static_cast<std::uint16_t>(10u),
-         static_cast<std::uint16_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint16_t) denom[6] = {
+         static_cast<boost::math::uint16_t>(0u),
+         static_cast<boost::math::uint16_t>(24u),
+         static_cast<boost::math::uint16_t>(50u),
+         static_cast<boost::math::uint16_t>(35u),
+         static_cast<boost::math::uint16_t>(10u),
+         static_cast<boost::math::uint16_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -101,13 +105,13 @@ struct lanczos6 : public std::integral_constant<int, 35>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 0.2412010548258800231126240760264822486599)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 35, 0.009446967704539249494420221613134244048319))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
-         static_cast<std::uint16_t>(0u),
-         static_cast<std::uint16_t>(24u),
-         static_cast<std::uint16_t>(50u),
-         static_cast<std::uint16_t>(35u),
-         static_cast<std::uint16_t>(10u),
-         static_cast<std::uint16_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint16_t) denom[6] = {
+         static_cast<boost::math::uint16_t>(0u),
+         static_cast<boost::math::uint16_t>(24u),
+         static_cast<boost::math::uint16_t>(50u),
+         static_cast<boost::math::uint16_t>(35u),
+         static_cast<boost::math::uint16_t>(10u),
+         static_cast<boost::math::uint16_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -163,7 +167,7 @@ struct lanczos6 : public std::integral_constant<int, 35>
 // Max experimental error (with arbitrary precision arithmetic) 2.16676e-19
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos11 : public std::integral_constant<int, 60>
+struct lanczos11 : public boost::math::integral_constant<int, 60>
 {
    //
    // Produces slightly better than double precision when evaluated at
@@ -186,18 +190,18 @@ struct lanczos11 : public std::integral_constant<int, 60>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 261.6140441641668190791708576058805625502)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 2.506628274631000502415573855452633787834))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(362880u),
-         static_cast<std::uint32_t>(1026576u),
-         static_cast<std::uint32_t>(1172700u),
-         static_cast<std::uint32_t>(723680u),
-         static_cast<std::uint32_t>(269325u),
-         static_cast<std::uint32_t>(63273u),
-         static_cast<std::uint32_t>(9450u),
-         static_cast<std::uint32_t>(870u),
-         static_cast<std::uint32_t>(45u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[11] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(362880u),
+         static_cast<boost::math::uint32_t>(1026576u),
+         static_cast<boost::math::uint32_t>(1172700u),
+         static_cast<boost::math::uint32_t>(723680u),
+         static_cast<boost::math::uint32_t>(269325u),
+         static_cast<boost::math::uint32_t>(63273u),
+         static_cast<boost::math::uint32_t>(9450u),
+         static_cast<boost::math::uint32_t>(870u),
+         static_cast<boost::math::uint32_t>(45u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -220,18 +224,18 @@ struct lanczos11 : public std::integral_constant<int, 60>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 0.004826466289237661857584712046231435101741)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 60, 0.4624429436045378766270459638520555557321e-4))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[11] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(362880u),
-         static_cast<std::uint32_t>(1026576u),
-         static_cast<std::uint32_t>(1172700u),
-         static_cast<std::uint32_t>(723680u),
-         static_cast<std::uint32_t>(269325u),
-         static_cast<std::uint32_t>(63273u),
-         static_cast<std::uint32_t>(9450u),
-         static_cast<std::uint32_t>(870u),
-         static_cast<std::uint32_t>(45u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[11] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(362880u),
+         static_cast<boost::math::uint32_t>(1026576u),
+         static_cast<boost::math::uint32_t>(1172700u),
+         static_cast<boost::math::uint32_t>(723680u),
+         static_cast<boost::math::uint32_t>(269325u),
+         static_cast<boost::math::uint32_t>(63273u),
+         static_cast<boost::math::uint32_t>(9450u),
+         static_cast<boost::math::uint32_t>(870u),
+         static_cast<boost::math::uint32_t>(45u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -297,7 +301,7 @@ struct lanczos11 : public std::integral_constant<int, 60>
 // Max experimental error (with arbitrary precision arithmetic) 9.2213e-23
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos13 : public std::integral_constant<int, 72>
+struct lanczos13 : public boost::math::integral_constant<int, 72>
 {
    //
    // Produces slightly better than extended-double precision when evaluated at
@@ -322,20 +326,20 @@ struct lanczos13 : public std::integral_constant<int, 72>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 381.8801248632926870394389468349331394196)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 2.506628274631000502415763426076722427007))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(39916800u),
-         static_cast<std::uint32_t>(120543840u),
-         static_cast<std::uint32_t>(150917976u),
-         static_cast<std::uint32_t>(105258076u),
-         static_cast<std::uint32_t>(45995730u),
-         static_cast<std::uint32_t>(13339535u),
-         static_cast<std::uint32_t>(2637558u),
-         static_cast<std::uint32_t>(357423u),
-         static_cast<std::uint32_t>(32670u),
-         static_cast<std::uint32_t>(1925u),
-         static_cast<std::uint32_t>(66u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[13] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(39916800u),
+         static_cast<boost::math::uint32_t>(120543840u),
+         static_cast<boost::math::uint32_t>(150917976u),
+         static_cast<boost::math::uint32_t>(105258076u),
+         static_cast<boost::math::uint32_t>(45995730u),
+         static_cast<boost::math::uint32_t>(13339535u),
+         static_cast<boost::math::uint32_t>(2637558u),
+         static_cast<boost::math::uint32_t>(357423u),
+         static_cast<boost::math::uint32_t>(32670u),
+         static_cast<boost::math::uint32_t>(1925u),
+         static_cast<boost::math::uint32_t>(66u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -360,20 +364,20 @@ struct lanczos13 : public std::integral_constant<int, 72>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 0.0007469903808915448316510079585999893674101)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 72, 0.4903180573459871862552197089738373164184e-5))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(39916800u),
-         static_cast<std::uint32_t>(120543840u),
-         static_cast<std::uint32_t>(150917976u),
-         static_cast<std::uint32_t>(105258076u),
-         static_cast<std::uint32_t>(45995730u),
-         static_cast<std::uint32_t>(13339535u),
-         static_cast<std::uint32_t>(2637558u),
-         static_cast<std::uint32_t>(357423u),
-         static_cast<std::uint32_t>(32670u),
-         static_cast<std::uint32_t>(1925u),
-         static_cast<std::uint32_t>(66u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[13] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(39916800u),
+         static_cast<boost::math::uint32_t>(120543840u),
+         static_cast<boost::math::uint32_t>(150917976u),
+         static_cast<boost::math::uint32_t>(105258076u),
+         static_cast<boost::math::uint32_t>(45995730u),
+         static_cast<boost::math::uint32_t>(13339535u),
+         static_cast<boost::math::uint32_t>(2637558u),
+         static_cast<boost::math::uint32_t>(357423u),
+         static_cast<boost::math::uint32_t>(32670u),
+         static_cast<boost::math::uint32_t>(1925u),
+         static_cast<boost::math::uint32_t>(66u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -443,7 +447,7 @@ struct lanczos13 : public std::integral_constant<int, 72>
 // Max experimental error (with arbitrary precision arithmetic) 8.111667e-8
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos6m24 : public std::integral_constant<int, 24>
+struct lanczos6m24 : public boost::math::integral_constant<int, 24>
 {
    //
    // Use for float precision, when evaluated as a float:
@@ -460,13 +464,13 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
          static_cast<T>(27.5192015197455403062503721613097825345L),
          static_cast<T>(2.50662858515256974113978724717473206342L)
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
-         static_cast<std::uint16_t>(0u),
-         static_cast<std::uint16_t>(24u),
-         static_cast<std::uint16_t>(50u),
-         static_cast<std::uint16_t>(35u),
-         static_cast<std::uint16_t>(10u),
-         static_cast<std::uint16_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint16_t) denom[6] = {
+         static_cast<boost::math::uint16_t>(0u),
+         static_cast<boost::math::uint16_t>(24u),
+         static_cast<boost::math::uint16_t>(50u),
+         static_cast<boost::math::uint16_t>(35u),
+         static_cast<boost::math::uint16_t>(10u),
+         static_cast<boost::math::uint16_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -484,13 +488,13 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
          static_cast<T>(6.595765571169314946316366571954421695196L),
          static_cast<T>(0.6007854010515290065101128585795542383721L)
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint16_t) denom[6] = {
-         static_cast<std::uint16_t>(0u),
-         static_cast<std::uint16_t>(24u),
-         static_cast<std::uint16_t>(50u),
-         static_cast<std::uint16_t>(35u),
-         static_cast<std::uint16_t>(10u),
-         static_cast<std::uint16_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint16_t) denom[6] = {
+         static_cast<boost::math::uint16_t>(0u),
+         static_cast<boost::math::uint16_t>(24u),
+         static_cast<boost::math::uint16_t>(50u),
+         static_cast<boost::math::uint16_t>(35u),
+         static_cast<boost::math::uint16_t>(10u),
+         static_cast<boost::math::uint16_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -546,7 +550,7 @@ struct lanczos6m24 : public std::integral_constant<int, 24>
 // Max experimental error (with arbitrary precision arithmetic) 1.196214e-17
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos13m53 : public std::integral_constant<int, 53>
+struct lanczos13m53 : public boost::math::integral_constant<int, 53>
 {
    //
    // Use for double precision, when evaluated as a double:
@@ -570,20 +574,20 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
          static_cast<T>(210.8242777515793458725097339207133627117L),
          static_cast<T>(2.506628274631000270164908177133837338626L)
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(39916800u),
-         static_cast<std::uint32_t>(120543840u),
-         static_cast<std::uint32_t>(150917976u),
-         static_cast<std::uint32_t>(105258076u),
-         static_cast<std::uint32_t>(45995730u),
-         static_cast<std::uint32_t>(13339535u),
-         static_cast<std::uint32_t>(2637558u),
-         static_cast<std::uint32_t>(357423u),
-         static_cast<std::uint32_t>(32670u),
-         static_cast<std::uint32_t>(1925u),
-         static_cast<std::uint32_t>(66u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[13] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(39916800u),
+         static_cast<boost::math::uint32_t>(120543840u),
+         static_cast<boost::math::uint32_t>(150917976u),
+         static_cast<boost::math::uint32_t>(105258076u),
+         static_cast<boost::math::uint32_t>(45995730u),
+         static_cast<boost::math::uint32_t>(13339535u),
+         static_cast<boost::math::uint32_t>(2637558u),
+         static_cast<boost::math::uint32_t>(357423u),
+         static_cast<boost::math::uint32_t>(32670u),
+         static_cast<boost::math::uint32_t>(1925u),
+         static_cast<boost::math::uint32_t>(66u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -608,20 +612,20 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
          static_cast<T>(0.5098416655656676188125178644804694509993L),
          static_cast<T>(0.006061842346248906525783753964555936883222L)
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint32_t) denom[13] = {
-         static_cast<std::uint32_t>(0u),
-         static_cast<std::uint32_t>(39916800u),
-         static_cast<std::uint32_t>(120543840u),
-         static_cast<std::uint32_t>(150917976u),
-         static_cast<std::uint32_t>(105258076u),
-         static_cast<std::uint32_t>(45995730u),
-         static_cast<std::uint32_t>(13339535u),
-         static_cast<std::uint32_t>(2637558u),
-         static_cast<std::uint32_t>(357423u),
-         static_cast<std::uint32_t>(32670u),
-         static_cast<std::uint32_t>(1925u),
-         static_cast<std::uint32_t>(66u),
-         static_cast<std::uint32_t>(1u)
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint32_t) denom[13] = {
+         static_cast<boost::math::uint32_t>(0u),
+         static_cast<boost::math::uint32_t>(39916800u),
+         static_cast<boost::math::uint32_t>(120543840u),
+         static_cast<boost::math::uint32_t>(150917976u),
+         static_cast<boost::math::uint32_t>(105258076u),
+         static_cast<boost::math::uint32_t>(45995730u),
+         static_cast<boost::math::uint32_t>(13339535u),
+         static_cast<boost::math::uint32_t>(2637558u),
+         static_cast<boost::math::uint32_t>(357423u),
+         static_cast<boost::math::uint32_t>(32670u),
+         static_cast<boost::math::uint32_t>(1925u),
+         static_cast<boost::math::uint32_t>(66u),
+         static_cast<boost::math::uint32_t>(1u)
       };
       // LCOV_EXCL_STOP
       return boost::math::tools::evaluate_rational(num, denom, z);
@@ -691,7 +695,7 @@ struct lanczos13m53 : public std::integral_constant<int, 53>
 // Max experimental error (with arbitrary precision arithmetic) 2.7699e-26
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos17m64 : public std::integral_constant<int, 64>
+struct lanczos17m64 : public boost::math::integral_constant<int, 64>
 {
    //
    // Use for extended-double precision, when evaluated as an extended-double:
@@ -719,7 +723,7 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 488.0063567520005730476791712814838113252)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.50662827463100050241576877135758834683))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint64_t) denom[17] = {
          BOOST_MATH_INT_VALUE_SUFFIX(0, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(1307674368000, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(4339163001600, uLL),
@@ -765,7 +769,7 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.002393749522058449186690627996063983095463)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.1229541408909435212800785616808830746135e-4))
       };
-      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, std::uint64_t) denom[17] = {
+      BOOST_MATH_STATIC const BOOST_MATH_INT_TABLE_TYPE(T, boost::math::uint64_t) denom[17] = {
          BOOST_MATH_INT_VALUE_SUFFIX(0, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(1307674368000, uLL),
          BOOST_MATH_INT_VALUE_SUFFIX(4339163001600, uLL),
@@ -860,13 +864,13 @@ struct lanczos17m64 : public std::integral_constant<int, 64>
 // Max experimental error (with arbitrary precision arithmetic) 1.0541e-38
 // Generated with compiler: Microsoft Visual C++ version 8.0 on Win32 at Mar 23 2006
 //
-struct lanczos24m113 : public std::integral_constant<int, 113>
+struct lanczos24m113 : public boost::math::integral_constant<int, 113>
 {
    //
    // Use for long-double precision, when evaluated as an long-double:
    //
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[24] = {
@@ -926,7 +930,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[24] = {
@@ -987,7 +991,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[23] = {
@@ -1025,7 +1029,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[23] = {
@@ -1063,7 +1067,7 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
       return result;
    }
 
-   static double g(){ return 20.3209821879863739013671875; }
+   BOOST_MATH_GPU_ENABLED static double g(){ return 20.3209821879863739013671875; }
 };
 
 //
@@ -1072,10 +1076,10 @@ struct lanczos24m113 : public std::integral_constant<int, 113>
 // Generated with compiler: Microsoft Visual C++ version 14.2 on Win32 at May 23 2021
 // Type precision was 134 bits or 42 max_digits10
 //
-struct lanczos27MP : public std::integral_constant<int, 134>
+struct lanczos27MP : public boost::math::integral_constant<int, 134>
 {
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[27] = {
@@ -1141,7 +1145,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[27] = {
@@ -1208,7 +1212,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[34] = {
@@ -1257,7 +1261,7 @@ struct lanczos27MP : public std::integral_constant<int, 134>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[34] = {
@@ -1306,10 +1310,10 @@ struct lanczos27MP : public std::integral_constant<int, 134>
       return result;
    }
 
-   static double g() { return 2.472513680905104038743047567550092935562134e+01; }
+   BOOST_MATH_GPU_ENABLED static double g() { return 2.472513680905104038743047567550092935562134e+01; }
 };
 
-inline double lanczos_g_near_1_and_2(const lanczos27MP&)
+BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const lanczos27MP&)
 {
    return 17.03623256087303;
 }
@@ -1320,10 +1324,10 @@ inline double lanczos_g_near_1_and_2(const lanczos27MP&)
 // Generated with compiler: Microsoft Visual C++ version 14.2 on Win32 at Oct 14 2019
 // Type precision was 168 bits or 53 max_digits10
 //
-struct lanczos35MP : public std::integral_constant<int, 168>
+struct lanczos35MP : public boost::math::integral_constant<int, 168>
 {
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[35] = {
@@ -1405,7 +1409,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[35] = {
@@ -1488,7 +1492,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[42] = {
@@ -1545,7 +1549,7 @@ struct lanczos35MP : public std::integral_constant<int, 168>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[42] = {
@@ -1602,10 +1606,10 @@ struct lanczos35MP : public std::integral_constant<int, 168>
       return result;
    }
 
-   static double g() { return 2.96640371531248092651367187500000000000000000000000000e+01; }
+   BOOST_MATH_GPU_ENABLED static double g() { return 2.96640371531248092651367187500000000000000000000000000e+01; }
 };
 
-inline double lanczos_g_near_1_and_2(const lanczos35MP&)
+BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const lanczos35MP&)
 {
    return 22.36563469469547;
 }
@@ -1615,10 +1619,10 @@ inline double lanczos_g_near_1_and_2(const lanczos35MP&)
 // Generated with compiler: Microsoft Visual C++ version 14.2 on Win32 at Oct 14 2019
 // Type precision was 201 bits or 63 max_digits10
 //
-struct lanczos48MP : public std::integral_constant<int, 201>
+struct lanczos48MP : public boost::math::integral_constant<int, 201>
 {
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[48] = {
@@ -1726,7 +1730,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[48] = {
@@ -1835,7 +1839,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[47] = {
@@ -1897,7 +1901,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[47] = {
@@ -1959,7 +1963,7 @@ struct lanczos48MP : public std::integral_constant<int, 201>
       return result;
    }
 
-   static double g() { return 2.880805098265409469604492187500000000000000000000000000000000000e+01; }
+   BOOST_MATH_GPU_ENABLED static double g() { return 2.880805098265409469604492187500000000000000000000000000000000000e+01; }
 };
 //
 // Lanczos Coefficients for N=49 G=3.531905273437499914734871708787977695465087890625000000000000000000000000e+01
@@ -1967,10 +1971,10 @@ struct lanczos48MP : public std::integral_constant<int, 201>
 // Generated with compiler: Microsoft Visual C++ version 14.2 on Win32 at May 23 2021
 // Type precision was 234 bits or 72 max_digits10
 //
-struct lanczos49MP : public std::integral_constant<int, 234>
+struct lanczos49MP : public boost::math::integral_constant<int, 234>
 {
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[49] = {
@@ -2080,7 +2084,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[49] = {
@@ -2191,7 +2195,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[48] = {
@@ -2254,7 +2258,7 @@ struct lanczos49MP : public std::integral_constant<int, 234>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[48] = {
@@ -2317,10 +2321,10 @@ struct lanczos49MP : public std::integral_constant<int, 234>
       return result;
    }
 
-   static double g() { return 3.531905273437499914734871708787977695465087890625000000000000000000000000e+01; }
+   BOOST_MATH_GPU_ENABLED static double g() { return 3.531905273437499914734871708787977695465087890625000000000000000000000000e+01; }
 };
 
-inline double lanczos_g_near_1_and_2(const lanczos49MP&)
+BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const lanczos49MP&)
 {
    return 33.54638671875000;
 }
@@ -2331,10 +2335,10 @@ inline double lanczos_g_near_1_and_2(const lanczos49MP&)
 // Generated with compiler: Microsoft Visual C++ version 14.2 on Win32 at May 22 2021
 // Type precision was 267 bits or 82 max_digits10
 //
-struct lanczos52MP : public std::integral_constant<int, 267>
+struct lanczos52MP : public boost::math::integral_constant<int, 267>
 {
    template <class T>
-   static T lanczos_sum(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[52] = {
@@ -2450,7 +2454,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    }
 
    template <class T>
-   static T lanczos_sum_expG_scaled(const T& z)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_expG_scaled(const T& z)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T num[52] = {
@@ -2567,7 +2571,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
 
 
    template<class T>
-   static T lanczos_sum_near_1(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_1(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[56] = {
@@ -2638,7 +2642,7 @@ struct lanczos52MP : public std::integral_constant<int, 267>
    }
 
    template<class T>
-   static T lanczos_sum_near_2(const T& dz)
+   BOOST_MATH_GPU_ENABLED static T lanczos_sum_near_2(const T& dz)
    {
       // LCOV_EXCL_START
       BOOST_MATH_STATIC const T d[56] = {
@@ -2709,10 +2713,10 @@ struct lanczos52MP : public std::integral_constant<int, 267>
       return result;
    }
 
-   static double g() { return 4.9921416015624998863131622783839702606201171875000000000000000000000000000000000000e+01; }
+   BOOST_MATH_GPU_ENABLED static double g() { return 4.9921416015624998863131622783839702606201171875000000000000000000000000000000000000e+01; }
 };
 
-inline double lanczos_g_near_1_and_2(const lanczos52MP&)
+BOOST_MATH_GPU_ENABLED inline double lanczos_g_near_1_and_2(const lanczos52MP&)
 {
    return 38.73733398437500;
 }
@@ -2721,24 +2725,24 @@ inline double lanczos_g_near_1_and_2(const lanczos52MP&)
 //
 // placeholder for no lanczos info available:
 //
-struct undefined_lanczos : public std::integral_constant<int, (std::numeric_limits<int>::max)() - 1> { };
+struct undefined_lanczos : public boost::math::integral_constant<int, (boost::math::numeric_limits<int>::max)() - 1> { };
 
 template <class Real, class Policy>
 struct lanczos
 {
-   BOOST_MATH_STATIC constexpr auto target_precision = policies::precision<Real, Policy>::type::value <= 0 ? (std::numeric_limits<int>::max)()-2 : 
+   BOOST_MATH_STATIC constexpr auto target_precision = policies::precision<Real, Policy>::type::value <= 0 ? (boost::math::numeric_limits<int>::max)()-2 : 
                                                                                                    policies::precision<Real, Policy>::type::value;
 
-   using type = typename std::conditional<(target_precision <= lanczos6m24::value), lanczos6m24, 
-                typename std::conditional<(target_precision <= lanczos13m53::value), lanczos13m53,
-                typename std::conditional<(target_precision <= lanczos11::value), lanczos11,
-                typename std::conditional<(target_precision <= lanczos17m64::value), lanczos17m64,
-                typename std::conditional<(target_precision <= lanczos24m113::value), lanczos24m113,
-                typename std::conditional<(target_precision <= lanczos27MP::value), lanczos27MP,
-                typename std::conditional<(target_precision <= lanczos35MP::value), lanczos35MP,
-                typename std::conditional<(target_precision <= lanczos48MP::value), lanczos48MP,
-                typename std::conditional<(target_precision <= lanczos49MP::value), lanczos49MP,
-                typename std::conditional<(target_precision <= lanczos52MP::value), lanczos52MP, undefined_lanczos>::type
+   using type = typename boost::math::conditional<(target_precision <= lanczos6m24::value), lanczos6m24, 
+                typename boost::math::conditional<(target_precision <= lanczos13m53::value), lanczos13m53,
+                typename boost::math::conditional<(target_precision <= lanczos11::value), lanczos11,
+                typename boost::math::conditional<(target_precision <= lanczos17m64::value), lanczos17m64,
+                typename boost::math::conditional<(target_precision <= lanczos24m113::value), lanczos24m113,
+                typename boost::math::conditional<(target_precision <= lanczos27MP::value), lanczos27MP,
+                typename boost::math::conditional<(target_precision <= lanczos35MP::value), lanczos35MP,
+                typename boost::math::conditional<(target_precision <= lanczos48MP::value), lanczos48MP,
+                typename boost::math::conditional<(target_precision <= lanczos49MP::value), lanczos49MP,
+                typename boost::math::conditional<(target_precision <= lanczos52MP::value), lanczos52MP, undefined_lanczos>::type
                 >::type>::type>::type>::type>::type>::type>::type>::type
                 >::type;
 };

From 460f9976d6ac14d3806b8fa8c109279700bd6fcb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:43:54 -0400
Subject: [PATCH 352/399] Add missing macro specialization

---
 include/boost/math/tools/config.hpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index e97ceaa742..a383b10f73 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -829,6 +829,7 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_UINTMAX_T unsigned long
 
 #define BOOST_MATH_INT_VALUE_SUFFIX(RV, SUF) RV##SUF
+#define BOOST_MATH_INT_TABLE_TYPE(RT, IT) IT
 
 #if defined(__cpp_inline_variables) && __cpp_inline_variables >= 201606L
 #  define BOOST_MATH_INLINE_CONSTEXPR inline constexpr

From c0201c3d37ba97465e35d7865eada849ac3f720c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:44:32 -0400
Subject: [PATCH 353/399] Add NVRTC support to beta

---
 include/boost/math/special_functions/beta.hpp | 67 +++++++++++++------
 1 file changed, 47 insertions(+), 20 deletions(-)

diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 75968f3ebe..0f6f0deb8d 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -11,19 +11,30 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/special_functions/gamma.hpp>
-#include <boost/math/special_functions/binomial.hpp>
-#include <boost/math/special_functions/factorials.hpp>
 #include <boost/math/special_functions/erf.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/expm1.hpp>
 #include <boost/math/special_functions/trunc.hpp>
+#include <boost/math/special_functions/lanczos.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/constants/constants.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/binomial.hpp>
+#include <boost/math/special_functions/factorials.hpp>
 #include <boost/math/tools/roots.hpp>
-#include <boost/math/tools/assert.hpp>
 #include <cmath>
+#endif
 
 namespace boost{ namespace math{
 
@@ -124,6 +135,7 @@ BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
 // Generic implementation of Beta(a,b) without Lanczos approximation support
 // (Caution this is slow!!!):
 //
+#ifndef BOOST_MATH_HAS_NVRTC
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const lanczos::undefined_lanczos& l, const Policy& pol)
 {
@@ -194,7 +206,7 @@ BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const lanczos::undefined_lanczos& l,
    }
 
 } // template <class T>T beta_imp(T a, T b, const lanczos::undefined_lanczos& l)
-
+#endif
 
 //
 // Compute the leading power terms in the incomplete Beta:
@@ -246,11 +258,11 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
    // l1 and l2 are the base of the exponents minus one:
    T l1 = (x * b - y * agh) / agh;
    T l2 = (y * a - x * bgh) / bgh;
-   if(((std::min)(fabs(l1), fabs(l2)) < 0.2))
+   if((BOOST_MATH_GPU_SAFE_MIN(fabs(l1), fabs(l2)) < 0.2))
    {
       // when the base of the exponent is very near 1 we get really
       // gross errors unless extra care is taken:
-      if((l1 * l2 > 0) || ((std::min)(a, b) < 1))
+      if((l1 * l2 > 0) || (BOOST_MATH_GPU_SAFE_MIN(a, b) < 1))
       {
          //
          // This first branch handles the simple cases where either:
@@ -286,7 +298,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
             BOOST_MATH_INSTRUMENT_VARIABLE(result);
          }
       }
-      else if((std::max)(fabs(l1), fabs(l2)) < 0.5)
+      else if(BOOST_MATH_GPU_SAFE_MAX(fabs(l1), fabs(l2)) < 0.5)
       {
          //
          // Both exponents are near one and both the exponents are
@@ -448,6 +460,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
 //
 // This version is generic, slow, and does not use the Lanczos approximation.
 //
+#ifndef BOOST_MATH_HAS_NVRTC
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
                         T b,
@@ -484,7 +497,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
       bool need_logs = false;
       if (a < b)
       {
-         BOOST_MATH_IF_CONSTEXPR(std::numeric_limits<T>::has_infinity)
+         BOOST_MATH_IF_CONSTEXPR(boost::math::numeric_limits<T>::has_infinity)
          {
             power1 = pow((x * y * c * c) / (a * b), a);
             power2 = pow((y * c) / b, b - a);
@@ -507,7 +520,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
       }
       else
       {
-         BOOST_MATH_IF_CONSTEXPR(std::numeric_limits<T>::has_infinity)
+         BOOST_MATH_IF_CONSTEXPR(boost::math::numeric_limits<T>::has_infinity)
          {
             power1 = pow((x * y * c * c) / (a * b), b);
             power2 = pow((x * c) / a, a - b);
@@ -526,7 +539,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
                need_logs = true;
          }
       }
-      BOOST_MATH_IF_CONSTEXPR(std::numeric_limits<T>::has_infinity)
+      BOOST_MATH_IF_CONSTEXPR(boost::math::numeric_limits<T>::has_infinity)
       {
          if (!(boost::math::isnormal)(power1) || !(boost::math::isnormal)(power2))
          {
@@ -625,6 +638,8 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
    }
    return prefix * power1 * (power2 / bet);
 }
+
+#endif
 //
 // Series approximation to the incomplete beta:
 //
@@ -717,7 +732,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool
    if(result < tools::min_value<T>())
       return s0; // Safeguard: series can't cope with denorms.
    ibeta_series_t<T> s(a, b, x, result);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   BOOST_MATH_UINTMAX_T max_iter = policies::get_max_series_iterations<Policy>();
    result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter, s0);
    policies::check_series_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%) in ibeta_series (with lanczos)", max_iter, pol);
    return result;
@@ -725,6 +740,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool
 //
 // Incomplete Beta series again, this time without Lanczos support:
 //
+#ifndef BOOST_MATH_HAS_NVRTC
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::lanczos::undefined_lanczos& l, bool normalised, T* p_derivative, T y, const Policy& pol)
 {
@@ -778,7 +794,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::la
    if(result < tools::min_value<T>())
       return s0; // Safeguard: series can't cope with denorms.
    ibeta_series_t<T> s(a, b, x, result);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   BOOST_MATH_UINTMAX_T max_iter = policies::get_max_series_iterations<Policy>();
    result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter, s0);
    policies::check_series_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%) in ibeta_series (without lanczos)", max_iter, pol);
    return result;
@@ -790,7 +806,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::la
 template <class T>
 struct ibeta_fraction2_t
 {
-   typedef std::pair<T, T> result_type;
+   typedef boost::math::pair<T, T> result_type;
 
    BOOST_MATH_GPU_ENABLED ibeta_fraction2_t(T a_, T b_, T x_, T y_) : a(a_), b(b_), x(x_), y(y_), m(0) {}
 
@@ -806,7 +822,7 @@ struct ibeta_fraction2_t
 
       ++m;
 
-      return std::make_pair(aN, bN);
+      return boost::math::make_pair(aN, bN);
    }
 
 private:
@@ -867,6 +883,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_a_step(T a, T b, T x, T y, int k, const Policy& p
 
    return prefix;
 }
+#endif
 //
 // This function is only needed for the non-regular incomplete beta,
 // it computes the delta in:
@@ -905,11 +922,15 @@ struct Pn_size
 {
    // This is likely to be enough for ~35-50 digit accuracy
    // but it's hard to quantify exactly:
+   #ifndef BOOST_MATH_HAS_NVRTC
    static constexpr unsigned value =
       ::boost::math::max_factorial<T>::value >= 100 ? 50
    : ::boost::math::max_factorial<T>::value >= ::boost::math::max_factorial<double>::value ? 30
    : ::boost::math::max_factorial<T>::value >= ::boost::math::max_factorial<float>::value ? 15 : 1;
    static_assert(::boost::math::max_factorial<T>::value >= ::boost::math::max_factorial<float>::value, "Type does not provide for 35-50 digits of accuracy.");
+   #else
+   static constexpr unsigned value = 0; // Will never be called
+   #endif
 };
 template <>
 struct Pn_size<float>
@@ -936,6 +957,7 @@ struct Pn_size<long double>
 #endif
 };
 
+#ifndef BOOST_MATH_HAS_NVRTC
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& pol, bool normalised)
 {
@@ -1037,7 +1059,7 @@ BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T
    }
    return sum;
 } // template <class T, class Lanczos>T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Lanczos& l, bool normalised)
-
+#endif
 //
 // For integer arguments we can relate the incomplete beta to the
 // complement of the binomial distribution cdf and use this finite sum.
@@ -1224,7 +1246,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, b
       return p;
    }
 
-   if((std::min)(a, b) <= 1)
+   if(BOOST_MATH_GPU_SAFE_MIN(a, b) <= 1)
    {
       if(x > 0.5)
       {
@@ -1233,10 +1255,10 @@ BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, b
          invert = !invert;
          BOOST_MATH_INSTRUMENT_VARIABLE(invert);
       }
-      if((std::max)(a, b) <= 1)
+      if(BOOST_MATH_GPU_SAFE_MAX(a, b) <= 1)
       {
          // Both a,b < 1:
-         if((a >= (std::min)(T(0.2), b)) || (pow(x, a) <= 0.9))
+         if((a >= BOOST_MATH_GPU_SAFE_MIN(T(0.2), b)) || (pow(x, a) <= 0.9))
          {
             if(!invert)
             {
@@ -1405,7 +1427,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, b
 
       if(b < 40)
       {
-         if((floor(a) == a) && (floor(b) == b) && (a < static_cast<T>((std::numeric_limits<int>::max)() - 100)) && (y != 1))
+         if((floor(a) == a) && (floor(b) == b) && (a < static_cast<T>((boost::math::numeric_limits<int>::max)() - 100)) && (y != 1))
          {
             // relate to the binomial distribution and use a finite sum:
             T k = a - 1;
@@ -1726,7 +1748,12 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
 } // namespace math
 } // namespace boost
 
+// TODO(mborland): Get the ibeta_inv working on NVRTC
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/special_functions/detail/ibeta_inverse.hpp>
 #include <boost/math/special_functions/detail/ibeta_inv_ab.hpp>
 
+#endif
+
 #endif // BOOST_MATH_SPECIAL_BETA_HPP

From 993eee29afa6876c81674357df0c44dfae9a976f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 16:46:02 -0400
Subject: [PATCH 354/399] Add beta NVRTC testing

---
 test/nvrtc_jamfile              |   3 +-
 test/test_beta_nvrtc_double.cpp | 190 ++++++++++++++++++++++++++++++++
 test/test_beta_nvrtc_float.cpp  | 190 ++++++++++++++++++++++++++++++++
 3 files changed, 382 insertions(+), 1 deletion(-)
 create mode 100644 test/test_beta_nvrtc_double.cpp
 create mode 100644 test/test_beta_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index e2fdaba52c..d4ff8977bb 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -88,7 +88,8 @@ run test_saspoint5_quan_nvrtc_double.cpp ;
 run test_saspoint5_quan_nvrtc_float.cpp ;
 
 # Special Functions
-# Beta
+run test_beta_nvrtc_double.cpp ;
+run test_beta_nvrtc_float.cpp ;
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
 run test_cos_pi_nvrtc_double.cpp ;
diff --git a/test/test_beta_nvrtc_double.cpp b/test/test_beta_nvrtc_double.cpp
new file mode 100644
index 0000000000..fdc502a195
--- /dev/null
+++ b/test/test_beta_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_beta_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::beta(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_nvrtc_float.cpp b/test/test_beta_nvrtc_float.cpp
new file mode 100644
index 0000000000..d403d33155
--- /dev/null
+++ b/test/test_beta_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_beta_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::beta(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::beta(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 937cc01e2bfa1649f03f040e176d86f5901f6df3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 17:27:03 -0400
Subject: [PATCH 355/399] Add NVRTC support to pow

---
 include/boost/math/special_functions/pow.hpp | 20 +++++++++++---------
 1 file changed, 11 insertions(+), 9 deletions(-)

diff --git a/include/boost/math/special_functions/pow.hpp b/include/boost/math/special_functions/pow.hpp
index a056f6daf3..7a1bb14eba 100644
--- a/include/boost/math/special_functions/pow.hpp
+++ b/include/boost/math/special_functions/pow.hpp
@@ -14,11 +14,13 @@
 #define BOOST_MATH_POW_HPP
 
 #include <boost/math/tools/config.hpp>
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/policies/policy.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/tools/promotion.hpp>
 
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
+#endif
 
 namespace boost {
 namespace math {
@@ -35,7 +37,7 @@ template <int N, int M = N%2>
 struct positive_power
 {
     template <typename T>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base)
     {
         T power = positive_power<N/2>::result(base);
         return power * power;
@@ -46,7 +48,7 @@ template <int N>
 struct positive_power<N, 1>
 {
     template <typename T>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base)
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base)
     {
         T power = positive_power<N/2>::result(base);
         return base * power * power;
@@ -57,7 +59,7 @@ template <>
 struct positive_power<1, 1>
 {
     template <typename T>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base){ return base; }
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base){ return base; }
 };
 
 
@@ -65,7 +67,7 @@ template <int N, bool>
 struct power_if_positive
 {
     template <typename T, class Policy>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy&)
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base, const Policy&)
     { return positive_power<N>::result(base); }
 };
 
@@ -73,7 +75,7 @@ template <int N>
 struct power_if_positive<N, false>
 {
     template <typename T, class Policy>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base, const Policy& policy)
     {
         if (base == 0)
         {
@@ -92,7 +94,7 @@ template <>
 struct power_if_positive<0, true>
 {
     template <typename T, class Policy>
-    BOOST_MATH_GPU_ENABLED static BOOST_MATH_CXX14_CONSTEXPR T result(T base, const Policy& policy)
+    BOOST_MATH_GPU_ENABLED static constexpr T result(T base, const Policy& policy)
     {
         if (base == 0)
         {
@@ -121,14 +123,14 @@ struct select_power_if_positive
 
 
 template <int N, typename T, class Policy>
-BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base, const Policy& policy)
+BOOST_MATH_GPU_ENABLED constexpr inline typename tools::promote_args<T>::type pow(T base, const Policy& policy)
 { 
    using result_type = typename tools::promote_args<T>::type;
    return detail::select_power_if_positive<N>::type::result(static_cast<result_type>(base), policy); 
 }
 
 template <int N, typename T>
-BOOST_MATH_GPU_ENABLED BOOST_MATH_CXX14_CONSTEXPR inline typename tools::promote_args<T>::type pow(T base)
+BOOST_MATH_GPU_ENABLED constexpr inline typename tools::promote_args<T>::type pow(T base)
 { return pow<N>(base, policies::policy<>()); }
 
 #ifdef _MSC_VER

From 87c320f6eaf279d927434d01d5d16118573ec426 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 17:27:14 -0400
Subject: [PATCH 356/399] Add NVRTC support to trigamma

---
 .../boost/math/special_functions/trigamma.hpp | 33 ++++++++++++-------
 1 file changed, 21 insertions(+), 12 deletions(-)

diff --git a/include/boost/math/special_functions/trigamma.hpp b/include/boost/math/special_functions/trigamma.hpp
index 2ec6c52562..61a60b502f 100644
--- a/include/boost/math/special_functions/trigamma.hpp
+++ b/include/boost/math/special_functions/trigamma.hpp
@@ -11,16 +11,22 @@
 #pragma once
 #endif
 
-#include <type_traits>
 #include <boost/math/tools/config.hpp>
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/rational.hpp>
-#include <boost/math/tools/series.hpp>
 #include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/big_constant.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/policies/policy.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <boost/math/tools/big_constant.hpp>
+#include <boost/math/special_functions/sin_pi.hpp>
+#include <boost/math/special_functions/pow.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/polygamma.hpp>
+#include <boost/math/tools/series.hpp>
+#endif
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -36,17 +42,20 @@ namespace boost{
 namespace math{
 namespace detail{
 
+// TODO(mborland): Temporary for NVRTC
+#ifndef BOOST_MATH_HAS_NVRTC
 template<class T, class Policy>
 T polygamma_imp(const int n, T x, const Policy &pol);
 
 template <class T, class Policy>
-T trigamma_prec(T x, const Policy& pol, const std::integral_constant<int, 0>&)
+T trigamma_prec(T x, const Policy& pol, const boost::math::integral_constant<int, 0>&)
 {
    return polygamma_imp(1, x, pol);
 }
+#endif
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const boost::math::integral_constant<int, 53>&)
 {
    // Max error in interpolated form: 3.736e-017
    BOOST_MATH_STATIC const T offset = BOOST_MATH_BIG_CONSTANT(T, 53, 2.1093254089355469);
@@ -119,7 +128,7 @@ BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_c
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const boost::math::integral_constant<int, 64>&)
 {
    // Max error in interpolated form: 1.178e-020
    BOOST_MATH_STATIC const T offset_1_2 = BOOST_MATH_BIG_CONSTANT(T, 64, 2.109325408935546875);
@@ -197,7 +206,7 @@ BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const std::integral_c
 }
 
 template <class T, class Policy>
-T trigamma_prec(T x, const Policy&, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T trigamma_prec(T x, const Policy&, const boost::math::integral_constant<int, 113>&)
 {
    // Max error in interpolated form: 1.916e-035
 
@@ -416,13 +425,13 @@ struct trigamma_initializer
       BOOST_MATH_GPU_ENABLED init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
-         do_init(std::integral_constant<bool, precision_type::value && (precision_type::value <= 113)>());
+         do_init(boost::math::integral_constant<bool, precision_type::value && (precision_type::value <= 113)>());
       }
-      BOOST_MATH_GPU_ENABLED void do_init(const std::true_type&)
+      BOOST_MATH_GPU_ENABLED void do_init(const boost::math::true_type&)
       {
          boost::math::trigamma(T(2.5), Policy());
       }
-      BOOST_MATH_GPU_ENABLED void do_init(const std::false_type&){}
+      BOOST_MATH_GPU_ENABLED void do_init(const boost::math::false_type&){}
       BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
    static const init initializer;
@@ -446,7 +455,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    typedef typename policies::precision<T, Policy>::type precision_type;
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 53 ? 53 :
       precision_type::value <= 64 ? 64 :

From b57dfe4e70ceb766f616b2ec9c65646bd04834c6 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 15 Aug 2024 17:28:51 -0400
Subject: [PATCH 357/399] Add trigamma NVRTC testing

---
 test/nvrtc_jamfile                  |   3 +-
 test/test_trigamma_nvrtc_double.cpp | 190 ++++++++++++++++++++++++++++
 test/test_trigamma_nvrtc_float.cpp  | 190 ++++++++++++++++++++++++++++
 3 files changed, 382 insertions(+), 1 deletion(-)
 create mode 100644 test/test_trigamma_nvrtc_double.cpp
 create mode 100644 test/test_trigamma_nvrtc_float.cpp

diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index d4ff8977bb..7e57f93ce6 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -120,5 +120,6 @@ run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
 run test_sin_pi_nvrtc_double.cpp ;
 run test_sin_pi_nvrtc_float.cpp ;
-# Trigamma
+run test_trigamma_nvrtc_double.cpp ;
+run test_trigamma_nvrtc_float.cpp ;
 run test_trunc_nvrtc_double.cpp ;
diff --git a/test/test_trigamma_nvrtc_double.cpp b/test/test_trigamma_nvrtc_double.cpp
new file mode 100644
index 0000000000..46877acce1
--- /dev/null
+++ b/test/test_trigamma_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/trigamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/trigamma.hpp>
+extern "C" __global__ 
+void test_trigamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::trigamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_trigamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_trigamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_trigamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::trigamma(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_trigamma_nvrtc_float.cpp b/test/test_trigamma_nvrtc_float.cpp
new file mode 100644
index 0000000000..083c7d8767
--- /dev/null
+++ b/test/test_trigamma_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/trigamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/trigamma.hpp>
+extern "C" __global__ 
+void test_trigamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::trigamma(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_trigamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_trigamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_trigamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::trigamma(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From d0acb067dcb8636e2d5411607b8dba16c383981d Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 16 Aug 2024 09:08:10 -0400
Subject: [PATCH 358/399] Replace workaround cstdint macros

---
 .../boost/math/policies/error_handling.hpp    |  5 ++--
 include/boost/math/policies/policy.hpp        | 11 +++----
 include/boost/math/special_functions/beta.hpp |  5 ++--
 include/boost/math/tools/config.hpp           |  8 -----
 include/boost/math/tools/fraction.hpp         | 25 ++++++++--------
 include/boost/math/tools/mp.hpp               | 21 +++++++-------
 include/boost/math/tools/rational.hpp         | 29 ++++++++++---------
 7 files changed, 51 insertions(+), 53 deletions(-)

diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 07e1127218..ce3f1e7ccd 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -11,6 +11,7 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 #ifndef BOOST_MATH_HAS_NVRTC
 
@@ -1017,7 +1018,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE R checked_narrowing_cast(T val, co
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline void check_series_iterations(const char* function, BOOST_MATH_UINTMAX_T max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
+BOOST_MATH_GPU_ENABLED inline void check_series_iterations(const char* function, boost::math::uintmax_t max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
 {
    if(max_iter >= policies::get_max_series_iterations<Policy>())
       raise_evaluation_error<T>(
@@ -1026,7 +1027,7 @@ BOOST_MATH_GPU_ENABLED inline void check_series_iterations(const char* function,
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, BOOST_MATH_UINTMAX_T max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
+BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, boost::math::uintmax_t max_iter, const Policy& pol) noexcept(boost::math::is_floating_point_v<T>)
 {
    if(max_iter >= policies::get_max_root_iterations<Policy>())
       raise_evaluation_error<T>(
diff --git a/include/boost/math/policies/policy.hpp b/include/boost/math/policies/policy.hpp
index 432191362e..ec7b36f2d5 100644
--- a/include/boost/math/policies/policy.hpp
+++ b/include/boost/math/policies/policy.hpp
@@ -11,6 +11,7 @@
 #include <boost/math/tools/mp.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 namespace boost{ namespace math{
 
@@ -313,7 +314,7 @@ class is_default_policy
    };
 };
 
-template <class Seq, class T, BOOST_MATH_SIZE_T N>
+template <class Seq, class T, boost::math::size_t N>
 struct append_N
 {
    using type = typename append_N<mp::mp_push_back<Seq, T>, T, N-1>::type;
@@ -402,7 +403,7 @@ class policy
    // Typelist of the arguments:
    //
    using arg_list = mp::mp_list<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11,A12,A13>;
-   static constexpr BOOST_MATH_SIZE_T arg_list_size = mp::mp_size<arg_list>::value;
+   static constexpr boost::math::size_t arg_list_size = mp::mp_size<arg_list>::value;
 
    template<typename A, typename B, bool b>
    struct pick_arg
@@ -533,7 +534,7 @@ class normalise
 {
 private:
    using arg_list = mp::mp_list<A1,A2,A3,A4,A5,A6,A7,A8,A9,A10,A11,A12,A13>;
-   static constexpr BOOST_MATH_SIZE_T arg_list_size = mp::mp_size<arg_list>::value;
+   static constexpr boost::math::size_t arg_list_size = mp::mp_size<arg_list>::value;
 
    template<typename A, typename B, bool b>
    struct pick_arg
@@ -882,7 +883,7 @@ struct series_factor_calc<T, Digits, boost::math::true_type, boost::math::false_
 {
    BOOST_MATH_GPU_ENABLED static constexpr T get() noexcept(boost::math::is_floating_point<T>::value)
    {
-      return 1 / static_cast<T>(static_cast<BOOST_MATH_UINTMAX_T>(1u) << (Digits::value - 1));
+      return 1 / static_cast<T>(static_cast<boost::math::uintmax_t>(1u) << (Digits::value - 1));
    }
 };
 template <class T, class Digits>
@@ -901,7 +902,7 @@ BOOST_MATH_GPU_ENABLED constexpr T get_epsilon_imp(boost::math::true_type const&
    static_assert(boost::math::numeric_limits<T>::radix == 2, "boost::math::numeric_limits<T>::radix == 2");
 
    typedef typename boost::math::policies::precision<T, Policy>::type p_t;
-   typedef boost::math::integral_constant<bool, p_t::value <= boost::math::numeric_limits<BOOST_MATH_UINTMAX_T>::digits> is_small_int;
+   typedef boost::math::integral_constant<bool, p_t::value <= boost::math::numeric_limits<boost::math::uintmax_t>::digits> is_small_int;
    typedef boost::math::integral_constant<bool, p_t::value >= boost::math::numeric_limits<T>::digits> is_default_value;
    return series_factor_calc<T, p_t, is_small_int, is_default_value>::get();
 }
diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 0f6f0deb8d..f0ac6318b5 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -18,6 +18,7 @@
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/erf.hpp>
 #include <boost/math/special_functions/log1p.hpp>
@@ -732,7 +733,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool
    if(result < tools::min_value<T>())
       return s0; // Safeguard: series can't cope with denorms.
    ibeta_series_t<T> s(a, b, x, result);
-   BOOST_MATH_UINTMAX_T max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter, s0);
    policies::check_series_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%) in ibeta_series (with lanczos)", max_iter, pol);
    return result;
@@ -794,7 +795,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::la
    if(result < tools::min_value<T>())
       return s0; // Safeguard: series can't cope with denorms.
    ibeta_series_t<T> s(a, b, x, result);
-   BOOST_MATH_UINTMAX_T max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter, s0);
    policies::check_series_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%) in ibeta_series (without lanczos)", max_iter, pol);
    return result;
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index a383b10f73..2736d660fe 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -776,11 +776,6 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_FP_SUBNORMAL FP_SUBNORMAL
 #define BOOST_MATH_FP_NORMAL FP_NORMAL
 
-// Missing type from NVRTC
-#include <cstdint>
-#define BOOST_MATH_SIZE_T std::size_t
-#define BOOST_MATH_UINTMAX_T std::uintmax_t
-
 #else // Special section for CUDA NVRTC to ensure we consume no STL headers
 
 #ifndef BOOST_MATH_STANDALONE
@@ -825,9 +820,6 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #define BOOST_MATH_FP_SUBNORMAL 3
 #define BOOST_MATH_FP_NORMAL 4
 
-#define BOOST_MATH_SIZE_T unsigned long
-#define BOOST_MATH_UINTMAX_T unsigned long
-
 #define BOOST_MATH_INT_VALUE_SUFFIX(RV, SUF) RV##SUF
 #define BOOST_MATH_INT_TABLE_TYPE(RT, IT) IT
 
diff --git a/include/boost/math/tools/fraction.hpp b/include/boost/math/tools/fraction.hpp
index c201a91b6c..e5a31edf65 100644
--- a/include/boost/math/tools/fraction.hpp
+++ b/include/boost/math/tools/fraction.hpp
@@ -17,6 +17,7 @@
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/complex.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <type_traits>
 #include <cstdint>
 #include <cmath>
@@ -112,7 +113,7 @@ namespace detail {
 //
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
       noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
       #ifndef BOOST_MATH_ENABLE_SYCL
       // SYCL can not handle this condition so we only check float on that platform
@@ -142,7 +143,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    C = f;
    D = 0;
 
-   BOOST_MATH_UINTMAX_T counter(max_terms);
+   boost::math::uintmax_t counter(max_terms);
    do{
       v = g();
       D = traits::b(v) + traits::a(v) * D;
@@ -164,7 +165,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 } // namespace detail
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
          #ifndef BOOST_MATH_ENABLE_SYCL
          && noexcept(std::declval<Gen>()())
@@ -182,7 +183,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    #endif
    )
 {
-   BOOST_MATH_UINTMAX_T max_terms = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
+   boost::math::uintmax_t max_terms = (std::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
@@ -200,12 +201,12 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    using result_type = typename traits::result_type;
 
    result_type factor = ldexp(1.0f, 1 - bits); // 1 / pow(result_type(2), bits);
-   BOOST_MATH_UINTMAX_T max_terms = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
+   boost::math::uintmax_t max_terms = (std::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -238,7 +239,7 @@ namespace detail {
 // Note that the first a1 and b1 returned by generator Gen are both used.
 //
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -268,7 +269,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    C = f;
    D = 0;
 
-   BOOST_MATH_UINTMAX_T counter(max_terms);
+   boost::math::uintmax_t counter(max_terms);
 
    do{
       v = g();
@@ -291,7 +292,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 } // namespace detail
 
 template <typename Gen, typename U>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
@@ -309,7 +310,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    #endif
    )
 {
-   BOOST_MATH_UINTMAX_T max_iter = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
+   boost::math::uintmax_t max_iter = (std::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
@@ -327,13 +328,13 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    typedef typename traits::result_type result_type;
 
    result_type factor = ldexp(1.0f, 1-bits); // 1 / pow(result_type(2), bits);
-   BOOST_MATH_UINTMAX_T max_iter = (std::numeric_limits<BOOST_MATH_UINTMAX_T>::max)();
+   boost::math::uintmax_t max_iter = (std::numeric_limits<boost::math::uintmax_t>::max)();
 
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
 template <typename Gen>
-BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, BOOST_MATH_UINTMAX_T& max_terms)
+BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
    #ifndef BOOST_MATH_ENABLE_SYCL
    && noexcept(std::declval<Gen>()())
diff --git a/include/boost/math/tools/mp.hpp b/include/boost/math/tools/mp.hpp
index 66fcbdbaf1..560ae8b500 100644
--- a/include/boost/math/tools/mp.hpp
+++ b/include/boost/math/tools/mp.hpp
@@ -13,6 +13,7 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 namespace boost { namespace math { namespace tools { namespace meta_programming {
 
@@ -22,8 +23,8 @@ template<typename... T>
 struct mp_list {};
 
 // Size_t
-template<BOOST_MATH_SIZE_T N> 
-using mp_size_t = boost::math::integral_constant<BOOST_MATH_SIZE_T, N>;
+template<boost::math::size_t N> 
+using mp_size_t = boost::math::integral_constant<boost::math::size_t, N>;
 
 // Boolean
 template<bool B>
@@ -52,7 +53,7 @@ struct mp_size_impl {};
 template<template<typename...> class L, typename... T> // Template template parameter must use class
 struct mp_size_impl<L<T...>>
 {
-    using type = boost::math::integral_constant<BOOST_MATH_SIZE_T, sizeof...(T)>;
+    using type = boost::math::integral_constant<boost::math::size_t, sizeof...(T)>;
 };
 }
 
@@ -78,7 +79,7 @@ namespace detail {
 // At
 // TODO - Use tree based lookup for larger typelists
 // http://odinthenerd.blogspot.com/2017/04/tree-based-lookup-why-kvasirmpl-is.html
-template<typename L, BOOST_MATH_SIZE_T>
+template<typename L, boost::math::size_t>
 struct mp_at_c {};
 
 template<template<typename...> class L, typename T0, typename... T>
@@ -167,7 +168,7 @@ struct mp_at_c<L<T0, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T...>, 1
 };
 }
 
-template<typename L, BOOST_MATH_SIZE_T Index>
+template<typename L, boost::math::size_t Index>
 using mp_at_c = typename detail::mp_at_c<L, Index>::type;
 
 template<typename L, typename Index>
@@ -338,8 +339,8 @@ using mp_remove_if_q = mp_remove_if<L, Q::template fn>;
 template<typename T, T... Index>
 struct integer_sequence {};
 
-template<BOOST_MATH_SIZE_T... Index>
-using index_sequence = integer_sequence<BOOST_MATH_SIZE_T, Index...>;
+template<boost::math::size_t... Index>
+using index_sequence = integer_sequence<boost::math::size_t, Index...>;
 
 namespace detail {
 
@@ -411,11 +412,11 @@ struct make_integer_sequence_impl
 template<typename T, T N>
 using make_integer_sequence = typename detail::make_integer_sequence_impl<T, N>::type;
 
-template<BOOST_MATH_SIZE_T N>
-using make_index_sequence = make_integer_sequence<BOOST_MATH_SIZE_T, N>;
+template<boost::math::size_t N>
+using make_index_sequence = make_integer_sequence<boost::math::size_t, N>;
 
 template<typename... T>
-using index_sequence_for = make_integer_sequence<BOOST_MATH_SIZE_T, sizeof...(T)>;
+using index_sequence_for = make_integer_sequence<boost::math::size_t, sizeof...(T)>;
 
 }}}} // namespaces
 
diff --git a/include/boost/math/tools/rational.hpp b/include/boost/math/tools/rational.hpp
index e3c3e7e338..a535abcdc5 100644
--- a/include/boost/math/tools/rational.hpp
+++ b/include/boost/math/tools/rational.hpp
@@ -13,6 +13,7 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/assert.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 #ifndef BOOST_MATH_HAS_NVRTC
 #include <array>
@@ -172,7 +173,7 @@ namespace boost{ namespace math{ namespace tools{
 // Forward declaration to keep two phase lookup happy:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED U evaluate_polynomial(const T* poly, U const& z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U);
+BOOST_MATH_GPU_ENABLED U evaluate_polynomial(const T* poly, U const& z, boost::math::size_t count) BOOST_MATH_NOEXCEPT(U);
 
 namespace detail{
 
@@ -190,7 +191,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial_c_imp
 // the loop expanded versions above:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, boost::math::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    BOOST_MATH_ASSERT(count > 0);
    U sum = static_cast<U>(poly[count - 1]);
@@ -205,7 +206,7 @@ BOOST_MATH_GPU_ENABLED inline U evaluate_polynomial(const T* poly, U const& z, B
 // Compile time sized polynomials, just inline forwarders to the
 // implementations above:
 //
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const T(&a)[N], const V& val) BOOST_MATH_NOEXCEPT(V)
 {
    typedef boost::math::integral_constant<int, N> tag_type;
@@ -213,7 +214,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const
 }
 
 #ifndef BOOST_MATH_HAS_NVRTC
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const std::array<T,N>& a, const V& val) BOOST_MATH_NOEXCEPT(V)
 {
    typedef boost::math::integral_constant<int, N> tag_type;
@@ -224,19 +225,19 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_polynomial(const
 // Even polynomials are trivial: just square the argument!
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_even_polynomial(const T* poly, U z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_even_polynomial(const T* poly, U z, boost::math::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    return evaluate_polynomial(poly, U(z*z), count);
 }
 
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
 }
 
 #ifndef BOOST_MATH_HAS_NVRTC
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return evaluate_polynomial(a, V(z*z));
@@ -246,12 +247,12 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_even_polynomial(
 // Odd polynomials come next:
 //
 template <class T, class U>
-BOOST_MATH_GPU_ENABLED inline U evaluate_odd_polynomial(const T* poly, U z, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(U)
+BOOST_MATH_GPU_ENABLED inline U evaluate_odd_polynomial(const T* poly, U z, boost::math::size_t count) BOOST_MATH_NOEXCEPT(U)
 {
    return poly[0] + z * evaluate_polynomial(poly+1, U(z*z), count-1);
 }
 
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const T(&a)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    typedef boost::math::integral_constant<int, N-1> tag_type;
@@ -259,7 +260,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(c
 }
 
 #ifndef BOOST_MATH_HAS_NVRTC
-template <BOOST_MATH_SIZE_T N, class T, class V>
+template <boost::math::size_t N, class T, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(const std::array<T,N>& a, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    typedef boost::math::integral_constant<int, N-1> tag_type;
@@ -268,7 +269,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_odd_polynomial(c
 #endif
 
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(V);
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, boost::math::size_t count) BOOST_MATH_NOEXCEPT(V);
 
 namespace detail{
 
@@ -288,7 +289,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational_c_imp(c
 // in our Lanczos code for example.
 //
 template <class T, class U, class V>
-BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, BOOST_MATH_SIZE_T count) BOOST_MATH_NOEXCEPT(V)
+BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V& z_, boost::math::size_t count) BOOST_MATH_NOEXCEPT(V)
 {
    V z(z_);
    V s1, s2;
@@ -320,14 +321,14 @@ BOOST_MATH_GPU_ENABLED V evaluate_rational(const T* num, const U* denom, const V
    return s1 / s2;
 }
 
-template <BOOST_MATH_SIZE_T N, class T, class U, class V>
+template <boost::math::size_t N, class T, class U, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const T(&a)[N], const U(&b)[N], const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return detail::evaluate_rational_c_imp(a, b, z, static_cast<const boost::math::integral_constant<int, N>*>(nullptr));
 }
 
 #ifndef BOOST_MATH_HAS_NVRTC
-template <BOOST_MATH_SIZE_T N, class T, class U, class V>
+template <boost::math::size_t N, class T, class U, class V>
 BOOST_MATH_GPU_ENABLED BOOST_MATH_GPU_ENABLED inline V evaluate_rational(const std::array<T,N>& a, const std::array<U,N>& b, const V& z) BOOST_MATH_NOEXCEPT(V)
 {
    return detail::evaluate_rational_c_imp(a.data(), b.data(), z, static_cast<boost::math::integral_constant<int, N>*>(nullptr));

From 1add05ba5ec36ac006f96dc16d822119885851bd Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 16 Aug 2024 09:12:38 -0400
Subject: [PATCH 359/399] Add missing header

---
 include/boost/math/tools/cstdint.hpp | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/include/boost/math/tools/cstdint.hpp b/include/boost/math/tools/cstdint.hpp
index f96e85c879..ce2c913b5c 100644
--- a/include/boost/math/tools/cstdint.hpp
+++ b/include/boost/math/tools/cstdint.hpp
@@ -56,6 +56,8 @@ using size_t = unsigned long;
 
 #else
 
+#include <cstdint>
+
 namespace boost {
 namespace math {
 

From 047c206c3028331d353e20a13855f8fafb0ccd5e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 20 Aug 2024 16:40:47 -0400
Subject: [PATCH 360/399] Add bessel GPU support

Add GPU support to bessel_i0

Add CUDA and NVRTC testing

Add GPU support to bessel_i1

Add CUDA and NVRTC testing of bessel_i1

Add tgamma1pm1 NVRTC impl

Add GPU support to iconv

Add GPU test to bessel_ik

Add SYCL testing of complete bessel_i

Add GPU support to bessel_j0

Ignore BOOST_MATH_INSTRUMENT_VARIABLE on NVRTC

Add bessel J0 CUDA and NVRTC testing

Add GPU support to bessel_j1

Add bessel j1 CUDA and NVRTC testing

Add GPU support to bessel jn and jy

Add SYCL bessel j testing

Add bessel_k0 GPU support

Add bessel_k0 CUDA and NVRTC testing

Add GPU support to bessel_k1

Add bessel_k1 CUDA and NVRTC testing

Add GPU support to bessel_kn

Add bessel_kn CUDA and NVRTC testing

Add SYCL testing of complete bessel_k

Make newton-rhapson GPU compatible

Make the completed bessel functions GPU compatible

Add SYCL bessel y testing

Apply changes for non-empty policy on CUDA

Add NVCC cyl_bessel_i testing

Add GPU support to sinc

Add GPU support to series functions

Add GPU support to bessel_jy_zero

Add array helper type

Make hypot GPU safe

Make bessel_yX GPU capable

Add bessel_y0 and bessel_y1 CUDA testing

Add nvrtc testing of bessel_y0 and bessel_y1

Fix macros

Add missing header

Add missing header

Markup iconv

Add iround for NVRTC

Add tgamma1pm1 with policy overload for NVRTC

Disable header

Fix factorial support for CUDA platforms

Add definition of bessel traits

Add cyl_bessel_i NVRTC testing

Fix cyl_bessel_jy warnings

Fix CUDA forward declarations

Fix maybe-unused variable warning

Add CUDA cyl_bessel_j testing

Add sign overload for lgamma

Fix warnings

Add NVRTC cyl_bessel_j testing

Add NVCC sph_bessel testing

Add NVRTC testing of sph_bessel

Add NVRTC testing of cyl_bessel_k

Add NVCC testing of cyl_bessel_k

Add NVCC testing of cyl_neumann

Add NVRTC cyl_neumann testing

Add NVRTC sph_neumann testing

Add NVCC sph_neumann testing
---
 .../boost/math/special_functions/bessel.hpp   | 257 ++++++++++++------
 .../detail/airy_ai_bi_zero.hpp                |  48 +++-
 .../special_functions/detail/bessel_i0.hpp    |  78 +++---
 .../special_functions/detail/bessel_i1.hpp    |  73 ++---
 .../special_functions/detail/bessel_ik.hpp    |  32 ++-
 .../special_functions/detail/bessel_j0.hpp    |  34 +--
 .../special_functions/detail/bessel_j1.hpp    |  46 ++--
 .../special_functions/detail/bessel_jn.hpp    |   6 +-
 .../special_functions/detail/bessel_jy.hpp    |  44 +--
 .../detail/bessel_jy_asym.hpp                 |  21 +-
 .../detail/bessel_jy_series.hpp               |  27 +-
 .../detail/bessel_jy_zero.hpp                 |  86 +++---
 .../special_functions/detail/bessel_k0.hpp    | 114 ++++----
 .../special_functions/detail/bessel_k1.hpp    | 126 +++++----
 .../special_functions/detail/bessel_kn.hpp    |   8 +-
 .../special_functions/detail/bessel_y0.hpp    |  27 +-
 .../special_functions/detail/bessel_y1.hpp    |  23 +-
 .../special_functions/detail/bessel_yn.hpp    |   6 +-
 .../math/special_functions/detail/iconv.hpp   |  11 +-
 .../detail/unchecked_factorial.hpp            |  96 ++++---
 .../boost/math/special_functions/expm1.hpp    |  54 ++--
 .../math/special_functions/factorials.hpp     |  31 ++-
 .../boost/math/special_functions/gamma.hpp    |  43 ++-
 .../boost/math/special_functions/hypot.hpp    |  20 +-
 .../boost/math/special_functions/math_fwd.hpp | 118 ++++----
 include/boost/math/special_functions/next.hpp |   7 +
 .../boost/math/special_functions/round.hpp    |  24 ++
 include/boost/math/special_functions/sinc.hpp |  29 +-
 include/boost/math/special_functions/ulp.hpp  |   1 +
 include/boost/math/tools/array.hpp            |  41 +++
 include/boost/math/tools/config.hpp           |   9 +-
 include/boost/math/tools/roots.hpp            |  94 ++++---
 include/boost/math/tools/series.hpp           |  70 +++--
 test/cuda_jamfile                             |  59 +++-
 test/nvrtc_jamfile                            |  45 +++
 test/sycl_jamfile                             |   4 +
 test/test_bessel_i.cpp                        |  14 +
 test/test_bessel_i.hpp                        |   6 +
 test/test_bessel_i0_double.cu                 | 100 +++++++
 test/test_bessel_i0_float.cu                  | 100 +++++++
 test/test_bessel_i0_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_i0_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_i1_double.cu                 | 100 +++++++
 test/test_bessel_i1_float.cu                  | 100 +++++++
 test/test_bessel_i1_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_i1_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_j.cpp                        |   5 +
 test/test_bessel_j.hpp                        |   3 +
 test/test_bessel_j0_double.cu                 | 100 +++++++
 test/test_bessel_j0_float.cu                  | 100 +++++++
 test/test_bessel_j0_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_j0_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_j1_double.cu                 | 100 +++++++
 test/test_bessel_j1_float.cu                  | 100 +++++++
 test/test_bessel_j1_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_j1_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_k.cpp                        |   5 +
 test/test_bessel_k.hpp                        |   3 +
 test/test_bessel_k0_double.cu                 | 100 +++++++
 test/test_bessel_k0_float.cu                  | 100 +++++++
 test/test_bessel_k0_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_k0_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_k1_double.cu                 | 100 +++++++
 test/test_bessel_k1_float.cu                  | 100 +++++++
 test/test_bessel_k1_nvrtc_double.cpp          | 190 +++++++++++++
 test/test_bessel_k1_nvrtc_float.cpp           | 190 +++++++++++++
 test/test_bessel_kn_double.cu                 | 105 +++++++
 test/test_bessel_kn_float.cu                  | 105 +++++++
 test/test_bessel_kn_nvrtc_double.cpp          | 192 +++++++++++++
 test/test_bessel_kn_nvrtc_float.cpp           | 192 +++++++++++++
 test/test_bessel_y.cpp                        |   9 +
 test/test_bessel_y.hpp                        |   3 +
 test/test_bessel_y0_double.cu                 | 106 ++++++++
 test/test_bessel_y0_float.cu                  | 106 ++++++++
 test/test_bessel_y0_nvrtc_double.cpp          | 194 +++++++++++++
 test/test_bessel_y0_nvrtc_float.cpp           | 194 +++++++++++++
 test/test_bessel_y1_double.cu                 | 106 ++++++++
 test/test_bessel_y1_float.cu                  | 106 ++++++++
 test/test_bessel_y1_nvrtc_double.cpp          | 194 +++++++++++++
 test/test_bessel_y1_nvrtc_float.cpp           | 194 +++++++++++++
 test/test_cyl_bessel_i_double.cu              | 104 +++++++
 test/test_cyl_bessel_i_float.cu               | 104 +++++++
 test/test_cyl_bessel_i_nvrtc_double.cpp       | 190 +++++++++++++
 test/test_cyl_bessel_i_nvrtc_float.cpp        | 190 +++++++++++++
 test/test_cyl_bessel_j_double.cu              | 104 +++++++
 test/test_cyl_bessel_j_float.cu               | 104 +++++++
 test/test_cyl_bessel_j_nvrtc_double.cpp       | 190 +++++++++++++
 test/test_cyl_bessel_j_nvrtc_float.cpp        | 190 +++++++++++++
 test/test_cyl_bessel_k_double.cu              | 104 +++++++
 test/test_cyl_bessel_k_float.cu               | 104 +++++++
 test/test_cyl_bessel_k_nvrtc_double.cpp       | 190 +++++++++++++
 test/test_cyl_bessel_k_nvrtc_float.cpp        | 190 +++++++++++++
 test/test_cyl_neumann_double.cu               | 116 ++++++++
 test/test_cyl_neumann_float.cu                | 104 +++++++
 test/test_cyl_neumann_nvrtc_double.cpp        | 190 +++++++++++++
 test/test_cyl_neumann_nvrtc_float.cpp         | 190 +++++++++++++
 test/test_sph_bessel_double.cu                | 119 ++++++++
 test/test_sph_bessel_float.cu                 | 119 ++++++++
 test/test_sph_bessel_nvrtc_double.cpp         | 199 ++++++++++++++
 test/test_sph_bessel_nvrtc_float.cpp          | 199 ++++++++++++++
 test/test_sph_neumann_double.cu               | 116 ++++++++
 test/test_sph_neumann_float.cu                | 116 ++++++++
 test/test_sph_neumann_nvrtc_double.cpp        | 190 +++++++++++++
 test/test_sph_neumann_nvrtc_float.cpp         | 190 +++++++++++++
 104 files changed, 10075 insertions(+), 671 deletions(-)
 create mode 100644 include/boost/math/tools/array.hpp
 create mode 100644 test/test_bessel_i0_double.cu
 create mode 100644 test/test_bessel_i0_float.cu
 create mode 100644 test/test_bessel_i0_nvrtc_double.cpp
 create mode 100644 test/test_bessel_i0_nvrtc_float.cpp
 create mode 100644 test/test_bessel_i1_double.cu
 create mode 100644 test/test_bessel_i1_float.cu
 create mode 100644 test/test_bessel_i1_nvrtc_double.cpp
 create mode 100644 test/test_bessel_i1_nvrtc_float.cpp
 create mode 100644 test/test_bessel_j0_double.cu
 create mode 100644 test/test_bessel_j0_float.cu
 create mode 100644 test/test_bessel_j0_nvrtc_double.cpp
 create mode 100644 test/test_bessel_j0_nvrtc_float.cpp
 create mode 100644 test/test_bessel_j1_double.cu
 create mode 100644 test/test_bessel_j1_float.cu
 create mode 100644 test/test_bessel_j1_nvrtc_double.cpp
 create mode 100644 test/test_bessel_j1_nvrtc_float.cpp
 create mode 100644 test/test_bessel_k0_double.cu
 create mode 100644 test/test_bessel_k0_float.cu
 create mode 100644 test/test_bessel_k0_nvrtc_double.cpp
 create mode 100644 test/test_bessel_k0_nvrtc_float.cpp
 create mode 100644 test/test_bessel_k1_double.cu
 create mode 100644 test/test_bessel_k1_float.cu
 create mode 100644 test/test_bessel_k1_nvrtc_double.cpp
 create mode 100644 test/test_bessel_k1_nvrtc_float.cpp
 create mode 100644 test/test_bessel_kn_double.cu
 create mode 100644 test/test_bessel_kn_float.cu
 create mode 100644 test/test_bessel_kn_nvrtc_double.cpp
 create mode 100644 test/test_bessel_kn_nvrtc_float.cpp
 create mode 100644 test/test_bessel_y0_double.cu
 create mode 100644 test/test_bessel_y0_float.cu
 create mode 100644 test/test_bessel_y0_nvrtc_double.cpp
 create mode 100644 test/test_bessel_y0_nvrtc_float.cpp
 create mode 100644 test/test_bessel_y1_double.cu
 create mode 100644 test/test_bessel_y1_float.cu
 create mode 100644 test/test_bessel_y1_nvrtc_double.cpp
 create mode 100644 test/test_bessel_y1_nvrtc_float.cpp
 create mode 100644 test/test_cyl_bessel_i_double.cu
 create mode 100644 test/test_cyl_bessel_i_float.cu
 create mode 100644 test/test_cyl_bessel_i_nvrtc_double.cpp
 create mode 100644 test/test_cyl_bessel_i_nvrtc_float.cpp
 create mode 100644 test/test_cyl_bessel_j_double.cu
 create mode 100644 test/test_cyl_bessel_j_float.cu
 create mode 100644 test/test_cyl_bessel_j_nvrtc_double.cpp
 create mode 100644 test/test_cyl_bessel_j_nvrtc_float.cpp
 create mode 100644 test/test_cyl_bessel_k_double.cu
 create mode 100644 test/test_cyl_bessel_k_float.cu
 create mode 100644 test/test_cyl_bessel_k_nvrtc_double.cpp
 create mode 100644 test/test_cyl_bessel_k_nvrtc_float.cpp
 create mode 100644 test/test_cyl_neumann_double.cu
 create mode 100644 test/test_cyl_neumann_float.cu
 create mode 100644 test/test_cyl_neumann_nvrtc_double.cpp
 create mode 100644 test/test_cyl_neumann_nvrtc_float.cpp
 create mode 100644 test/test_sph_bessel_double.cu
 create mode 100644 test/test_sph_bessel_float.cu
 create mode 100644 test/test_sph_bessel_nvrtc_double.cpp
 create mode 100644 test/test_sph_bessel_nvrtc_float.cpp
 create mode 100644 test/test_sph_neumann_double.cu
 create mode 100644 test/test_sph_neumann_float.cu
 create mode 100644 test/test_sph_neumann_nvrtc_double.cpp
 create mode 100644 test/test_sph_neumann_nvrtc_float.cpp

diff --git a/include/boost/math/special_functions/bessel.hpp b/include/boost/math/special_functions/bessel.hpp
index e9677d3c79..0814734428 100644
--- a/include/boost/math/special_functions/bessel.hpp
+++ b/include/boost/math/special_functions/bessel.hpp
@@ -15,8 +15,14 @@
 #  pragma once
 #endif
 
-#include <limits>
-#include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/rational.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/series.hpp>
+#include <boost/math/tools/roots.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/special_functions/detail/bessel_jy.hpp>
 #include <boost/math/special_functions/detail/bessel_jn.hpp>
 #include <boost/math/special_functions/detail/bessel_yn.hpp>
@@ -31,10 +37,8 @@
 #include <boost/math/special_functions/sinc.hpp>
 #include <boost/math/special_functions/trunc.hpp>
 #include <boost/math/special_functions/round.hpp>
-#include <boost/math/tools/rational.hpp>
-#include <boost/math/tools/promotion.hpp>
-#include <boost/math/tools/series.hpp>
-#include <boost/math/tools/roots.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -43,6 +47,50 @@
 
 namespace boost{ namespace math{
 
+// Since we cannot pull this in from math fwd we need a copy
+#ifdef BOOST_MATH_HAS_NVRTC
+
+namespace detail{
+
+      typedef boost::math::integral_constant<int, 0> bessel_no_int_tag;      // No integer optimisation possible.
+      typedef boost::math::integral_constant<int, 1> bessel_maybe_int_tag;   // Maybe integer optimisation.
+      typedef boost::math::integral_constant<int, 2> bessel_int_tag;         // Definite integer optimisation.
+
+      template <class T1, class T2, class Policy>
+      struct bessel_traits
+      {
+         using result_type = typename boost::math::conditional<
+            boost::math::is_integral<T1>::value,
+            typename tools::promote_args<T2>::type,
+            tools::promote_args_t<T1, T2>
+         >::type;
+
+         typedef typename policies::precision<result_type, Policy>::type precision_type;
+
+         using optimisation_tag = typename boost::math::conditional<
+            (precision_type::value <= 0 || precision_type::value > 64),
+            bessel_no_int_tag,
+            typename boost::math::conditional<
+               boost::math::is_integral<T1>::value,
+               bessel_int_tag,
+               bessel_maybe_int_tag
+            >::type
+         >::type;
+
+         using optimisation_tag128 = typename boost::math::conditional<
+            (precision_type::value <= 0 || precision_type::value > 113),
+            bessel_no_int_tag,
+            typename boost::math::conditional<
+               boost::math::is_integral<T1>::value,
+               bessel_int_tag,
+               bessel_maybe_int_tag
+            >::type
+         >::type;
+      };
+   } // detail
+
+#endif
+
 namespace detail{
 
 template <class T, class Policy>
@@ -50,7 +98,7 @@ struct sph_bessel_j_small_z_series_term
 {
    typedef T result_type;
 
-   sph_bessel_j_small_z_series_term(unsigned v_, T x)
+   BOOST_MATH_GPU_ENABLED sph_bessel_j_small_z_series_term(unsigned v_, T x)
       : N(0), v(v_)
    {
       BOOST_MATH_STD_USING
@@ -64,7 +112,7 @@ struct sph_bessel_j_small_z_series_term
          term = pow(mult, T(v)) / boost::math::tgamma(v+1+T(0.5f), Policy());
       mult *= -mult;
    }
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = term;
       ++N;
@@ -79,11 +127,11 @@ struct sph_bessel_j_small_z_series_term
 };
 
 template <class T, class Policy>
-inline T sph_bessel_j_small_z_series(unsigned v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sph_bessel_j_small_z_series(unsigned v, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
    sph_bessel_j_small_z_series_term<T, Policy> s(v, x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
 
@@ -92,10 +140,21 @@ inline T sph_bessel_j_small_z_series(unsigned v, T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T cyl_bessel_j_imp(T v, T x, const bessel_no_int_tag& t, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T cyl_bessel_j_imp_final(T v, T x, const bessel_no_int_tag& t, const Policy& pol)
+{
+   BOOST_MATH_STD_USING
+
+   T result_J, y; // LCOV_EXCL_LINE
+   bessel_jy(v, x, &result_J, &y, need_j, pol);
+   return result_J;
+}
+
+// Dispatch funtion to avoid recursion
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED T cyl_bessel_j_imp(T v, T x, const bessel_no_int_tag& t, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::bessel_j<%1%>(%1%,%1%)";
+
    if(x < 0)
    {
       // better have integer v:
@@ -105,23 +164,27 @@ T cyl_bessel_j_imp(T v, T x, const bessel_no_int_tag& t, const Policy& pol)
          // This branch is hit by multiprecision types only, and is
          // tested by our real_concept tests, but thee are excluded from coverage
          // due to time constraints.
-         T r = cyl_bessel_j_imp(v, T(-x), t, pol);
+         T r = cyl_bessel_j_imp_final(T(v), T(-x), t, pol);
          if (iround(v, pol) & 1)
+         {
             r = -r;
+         }
+
          return r;
          // LCOV_EXCL_STOP
       }
       else
+      {
+         constexpr auto function = "boost::math::bessel_j<%1%>(%1%,%1%)";
          return policies::raise_domain_error<T>(function, "Got x = %1%, but we need x >= 0", x, pol);
+      }
    }
 
-   T result_J, y; // LCOV_EXCL_LINE
-   bessel_jy(v, x, &result_J, &y, need_j, pol);
-   return result_J;
+   return cyl_bessel_j_imp_final(T(v), T(x), t, pol);
 }
 
 template <class T, class Policy>
-inline T cyl_bessel_j_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_j_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // ADL of std names.
    int ival = detail::iconv(v, pol);
@@ -135,14 +198,14 @@ inline T cyl_bessel_j_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& p
 }
 
 template <class T, class Policy>
-inline T cyl_bessel_j_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_j_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    return bessel_jn(v, x, pol);
 }
 
 template <class T, class Policy>
-inline T sph_bessel_j_imp(unsigned n, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sph_bessel_j_imp(unsigned n, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
    if(x < 0)
@@ -171,7 +234,7 @@ inline T sph_bessel_j_imp(unsigned n, T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T cyl_bessel_i_imp(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T cyl_bessel_i_imp_final(T v, T x, const Policy& pol)
 {
    //
    // This handles all the bessel I functions, note that we don't optimise
@@ -180,20 +243,7 @@ T cyl_bessel_i_imp(T v, T x, const Policy& pol)
    // case has better error handling too).
    //
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::cyl_bessel_i<%1%>(%1%,%1%)";
-   if(x < 0)
-   {
-      // better have integer v:
-      if(floor(v) == v)
-      {
-         T r = cyl_bessel_i_imp(v, T(-x), pol);
-         if(iround(v, pol) & 1)
-            r = -r;
-         return r;
-      }
-      else
-         return policies::raise_domain_error<T>(function, "Got x = %1%, but we need x >= 0", x, pol);
-   }
+   constexpr auto function = "boost::math::cyl_bessel_i<%1%>(%1%,%1%)";
    if(x == 0)
    {
       if(v < 0) 
@@ -210,7 +260,7 @@ T cyl_bessel_i_imp(T v, T x, const Policy& pol)
       }
       return sqrt(2 / (x * constants::pi<T>())) * sinh(x);
    }
-   if((policies::digits<T, Policy>() <= 113) && (std::numeric_limits<T>::digits <= 113) && (std::numeric_limits<T>::radix == 2))
+   if((policies::digits<T, Policy>() <= 113) && (boost::math::numeric_limits<T>::digits <= 113) && (boost::math::numeric_limits<T>::radix == 2))
    {
       if(v == 0)
       {
@@ -228,10 +278,39 @@ T cyl_bessel_i_imp(T v, T x, const Policy& pol)
    return result_I;
 }
 
+// Additional dispatch function to get the GPU impls happy
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED T cyl_bessel_i_imp(T v, T x, const Policy& pol)
+{
+   BOOST_MATH_STD_USING
+   constexpr auto function = "boost::math::cyl_bessel_i<%1%>(%1%,%1%)";
+
+   if(x < 0)
+   {
+      // better have integer v:
+      if(floor(v) == v)
+      {
+         T r = cyl_bessel_i_imp_final(T(v), T(-x), pol);
+         if(iround(v, pol) & 1)
+         {
+            r = -r;
+         }
+         
+         return r;
+      }
+      else
+      {
+         return policies::raise_domain_error<T>(function, "Got x = %1%, but we need x >= 0", x, pol);
+      }
+   }
+   
+   return cyl_bessel_i_imp_final(T(v), T(x), pol);
+}
+
 template <class T, class Policy>
-inline T cyl_bessel_k_imp(T v, T x, const bessel_no_int_tag& /* t */, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_k_imp(T v, T x, const bessel_no_int_tag& /* t */, const Policy& pol)
 {
-   static const char* function = "boost::math::cyl_bessel_k<%1%>(%1%,%1%)";
+   constexpr auto function = "boost::math::cyl_bessel_k<%1%>(%1%,%1%)";
    BOOST_MATH_STD_USING
    if(x < 0)
    {
@@ -248,7 +327,7 @@ inline T cyl_bessel_k_imp(T v, T x, const bessel_no_int_tag& /* t */, const Poli
 }
 
 template <class T, class Policy>
-inline T cyl_bessel_k_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_k_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    if((floor(v) == v))
@@ -259,15 +338,15 @@ inline T cyl_bessel_k_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& p
 }
 
 template <class T, class Policy>
-inline T cyl_bessel_k_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_k_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
 {
    return bessel_kn(v, x, pol);
 }
 
 template <class T, class Policy>
-inline T cyl_neumann_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_neumann_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol)
 {
-   static const char* function = "boost::math::cyl_neumann<%1%>(%1%,%1%)";
+   constexpr auto function = "boost::math::cyl_neumann<%1%>(%1%,%1%)";
 
    BOOST_MATH_INSTRUMENT_VARIABLE(v);
    BOOST_MATH_INSTRUMENT_VARIABLE(x);
@@ -291,7 +370,7 @@ inline T cyl_neumann_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline T cyl_neumann_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_neumann_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -310,16 +389,16 @@ inline T cyl_neumann_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& po
 }
 
 template <class T, class Policy>
-inline T cyl_neumann_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_neumann_imp(int v, T x, const bessel_int_tag&, const Policy& pol)
 {
    return bessel_yn(v, x, pol);
 }
 
 template <class T, class Policy>
-inline T sph_neumann_imp(unsigned v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T sph_neumann_imp(unsigned v, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
-   static const char* function = "boost::math::sph_neumann<%1%>(%1%,%1%)";
+   constexpr auto function = "boost::math::sph_neumann<%1%>(%1%,%1%)";
    //
    // Nothing much to do here but check for errors, and
    // evaluate the function's definition directly:
@@ -340,11 +419,11 @@ inline T sph_neumann_imp(unsigned v, T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline T cyl_bessel_j_zero_imp(T v, int m, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_bessel_j_zero_imp(T v, int m, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names, needed for floor.
 
-   static const char* function = "boost::math::cyl_bessel_j_zero<%1%>(%1%, int)";
+   constexpr auto function = "boost::math::cyl_bessel_j_zero<%1%>(%1%, int)";
 
    const T half_epsilon(boost::math::tools::epsilon<T>() / 2U);
 
@@ -395,7 +474,7 @@ inline T cyl_bessel_j_zero_imp(T v, int m, const Policy& pol)
    const T guess_root = boost::math::detail::bessel_zero::cyl_bessel_j_zero_detail::initial_guess<T, Policy>((order_is_integer ? vv : v), m, pol);
 
    // Select the maximum allowed iterations from the policy.
-   std::uintmax_t number_of_iterations = policies::get_max_root_iterations<Policy>();
+   boost::math::uintmax_t number_of_iterations = policies::get_max_root_iterations<Policy>();
 
    const T delta_lo = ((guess_root > 0.2F) ? T(0.2) : T(guess_root / 2U));
 
@@ -418,11 +497,11 @@ inline T cyl_bessel_j_zero_imp(T v, int m, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline T cyl_neumann_zero_imp(T v, int m, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T cyl_neumann_zero_imp(T v, int m, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names, needed for floor.
 
-   static const char* function = "boost::math::cyl_neumann_zero<%1%>(%1%, int)";
+   constexpr auto function = "boost::math::cyl_neumann_zero<%1%>(%1%, int)";
 
    // Handle non-finite order.
    if (!(boost::math::isfinite)(v) )
@@ -473,7 +552,7 @@ inline T cyl_neumann_zero_imp(T v, int m, const Policy& pol)
    const T guess_root = boost::math::detail::bessel_zero::cyl_neumann_zero_detail::initial_guess<T, Policy>(v, m, pol);
 
    // Select the maximum allowed iterations from the policy.
-   std::uintmax_t number_of_iterations = policies::get_max_root_iterations<Policy>();
+   boost::math::uintmax_t number_of_iterations = policies::get_max_root_iterations<Policy>();
 
    const T delta_lo = ((guess_root > 0.2F) ? T(0.2) : T(guess_root / 2U));
 
@@ -498,7 +577,7 @@ inline T cyl_neumann_zero_imp(T v, int m, const Policy& pol)
 } // namespace detail
 
 template <class T1, class T2, class Policy>
-inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j(T1 v, T2 x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j(T1 v, T2 x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -514,13 +593,13 @@ inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j(
 }
 
 template <class T1, class T2>
-inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j(T1 v, T2 x)
 {
    return cyl_bessel_j(v, x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel(unsigned v, T x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel(unsigned v, T x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T, T, Policy>::result_type result_type;
@@ -535,13 +614,13 @@ inline typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel(unsi
 }
 
 template <class T>
-inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel(unsigned v, T x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel(unsigned v, T x)
 {
    return sph_bessel(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i(T1 v, T2 x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i(T1 v, T2 x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -556,13 +635,13 @@ inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i(
 }
 
 template <class T1, class T2>
-inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i(T1 v, T2 x)
 {
    return cyl_bessel_i(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k(T1 v, T2 x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k(T1 v, T2 x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -578,13 +657,13 @@ inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k(
 }
 
 template <class T1, class T2>
-inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k(T1 v, T2 x)
 {
    return cyl_bessel_k(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann(T1 v, T2 x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann(T1 v, T2 x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -600,13 +679,13 @@ inline typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann(T
 }
 
 template <class T1, class T2>
-inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann(T1 v, T2 x)
 {
    return cyl_neumann(v, x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann(unsigned v, T x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann(unsigned v, T x, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T, T, Policy>::result_type result_type;
@@ -621,13 +700,13 @@ inline typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann(uns
 }
 
 template <class T>
-inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann(unsigned v, T x)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann(unsigned v, T x)
 {
    return sph_neumann(v, x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_bessel_j_zero(T v, int m, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_bessel_j_zero(T v, int m, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T, T, Policy>::result_type result_type;
@@ -639,35 +718,35 @@ inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_bessel_j_ze
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    return policies::checked_narrowing_cast<result_type, Policy>(detail::cyl_bessel_j_zero_imp<value_type>(v, m, forwarding_policy()), "boost::math::cyl_bessel_j_zero<%1%>(%1%,%1%)");
 }
 
 template <class T>
-inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_bessel_j_zero(T v, int m)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_bessel_j_zero(T v, int m)
 {
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    return cyl_bessel_j_zero<T, policies::policy<> >(v, m, policies::policy<>());
 }
 
 template <class T, class OutputIterator, class Policy>
-inline OutputIterator cyl_bessel_j_zero(T v,
+BOOST_MATH_GPU_ENABLED inline OutputIterator cyl_bessel_j_zero(T v,
                               int start_index,
                               unsigned number_of_zeros,
                               OutputIterator out_it,
                               const Policy& pol)
 {
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    for(int i = 0; i < static_cast<int>(number_of_zeros); ++i)
@@ -679,7 +758,7 @@ inline OutputIterator cyl_bessel_j_zero(T v,
 }
 
 template <class T, class OutputIterator>
-inline OutputIterator cyl_bessel_j_zero(T v,
+BOOST_MATH_GPU_ENABLED inline OutputIterator cyl_bessel_j_zero(T v,
                               int start_index,
                               unsigned number_of_zeros,
                               OutputIterator out_it)
@@ -688,7 +767,7 @@ inline OutputIterator cyl_bessel_j_zero(T v,
 }
 
 template <class T, class Policy>
-inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_neumann_zero(T v, int m, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_neumann_zero(T v, int m, const Policy& /* pol */)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T, T, Policy>::result_type result_type;
@@ -700,35 +779,35 @@ inline typename detail::bessel_traits<T, T, Policy>::result_type cyl_neumann_zer
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    return policies::checked_narrowing_cast<result_type, Policy>(detail::cyl_neumann_zero_imp<value_type>(v, m, forwarding_policy()), "boost::math::cyl_neumann_zero<%1%>(%1%,%1%)");
 }
 
 template <class T>
-inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_neumann_zero(T v, int m)
+BOOST_MATH_GPU_ENABLED inline typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_neumann_zero(T v, int m)
 {
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    return cyl_neumann_zero<T, policies::policy<> >(v, m, policies::policy<>());
 }
 
 template <class T, class OutputIterator, class Policy>
-inline OutputIterator cyl_neumann_zero(T v,
+BOOST_MATH_GPU_ENABLED inline OutputIterator cyl_neumann_zero(T v,
                              int start_index,
                              unsigned number_of_zeros,
                              OutputIterator out_it,
                              const Policy& pol)
 {
-   static_assert(    false == std::numeric_limits<T>::is_specialized
-                           || (   true  == std::numeric_limits<T>::is_specialized
-                               && false == std::numeric_limits<T>::is_integer),
+   static_assert(    false == boost::math::numeric_limits<T>::is_specialized
+                           || (   true  == boost::math::numeric_limits<T>::is_specialized
+                               && false == boost::math::numeric_limits<T>::is_integer),
                            "Order must be a floating-point type.");
 
    for(int i = 0; i < static_cast<int>(number_of_zeros); ++i)
@@ -740,7 +819,7 @@ inline OutputIterator cyl_neumann_zero(T v,
 }
 
 template <class T, class OutputIterator>
-inline OutputIterator cyl_neumann_zero(T v,
+BOOST_MATH_GPU_ENABLED inline OutputIterator cyl_neumann_zero(T v,
                              int start_index,
                              unsigned number_of_zeros,
                              OutputIterator out_it)
diff --git a/include/boost/math/special_functions/detail/airy_ai_bi_zero.hpp b/include/boost/math/special_functions/detail/airy_ai_bi_zero.hpp
index 7735eb8589..e518422f17 100644
--- a/include/boost/math/special_functions/detail/airy_ai_bi_zero.hpp
+++ b/include/boost/math/special_functions/detail/airy_ai_bi_zero.hpp
@@ -13,6 +13,8 @@
 #ifndef BOOST_MATH_AIRY_AI_BI_ZERO_2013_01_20_HPP_
   #define BOOST_MATH_AIRY_AI_BI_ZERO_2013_01_20_HPP_
 
+  #include <boost/math/tools/config.hpp>
+  #include <boost/math/tools/tuple.hpp>
   #include <boost/math/constants/constants.hpp>
   #include <boost/math/special_functions/cbrt.hpp>
 
@@ -21,18 +23,18 @@
   {
     // Forward declarations of the needed Airy function implementations.
     template <class T, class Policy>
-    T airy_ai_imp(T x, const Policy& pol);
+    BOOST_MATH_GPU_ENABLED T airy_ai_imp(T x, const Policy& pol);
     template <class T, class Policy>
-    T airy_bi_imp(T x, const Policy& pol);
+    BOOST_MATH_GPU_ENABLED T airy_bi_imp(T x, const Policy& pol);
     template <class T, class Policy>
-    T airy_ai_prime_imp(T x, const Policy& pol);
+    BOOST_MATH_GPU_ENABLED T airy_ai_prime_imp(T x, const Policy& pol);
     template <class T, class Policy>
-    T airy_bi_prime_imp(T x, const Policy& pol);
+    BOOST_MATH_GPU_ENABLED T airy_bi_prime_imp(T x, const Policy& pol);
 
     namespace airy_zero
     {
       template<class T, class Policy>
-      T equation_as_10_4_105(const T& z, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED T equation_as_10_4_105(const T& z, const Policy& pol)
       {
         const T one_over_z        (T(1) / z);
         const T one_over_z_squared(one_over_z * one_over_z);
@@ -54,7 +56,7 @@
       namespace airy_ai_zero_detail
       {
         template<class T, class Policy>
-        T initial_guess(const int m, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T initial_guess(const int m, const Policy& pol)
         {
           T guess;
 
@@ -106,11 +108,19 @@
         class function_object_ai_and_ai_prime
         {
         public:
-          explicit function_object_ai_and_ai_prime(const Policy& pol) : my_pol(pol) { }
+          BOOST_MATH_GPU_ENABLED explicit function_object_ai_and_ai_prime(const Policy& pol) : my_pol(pol) { }
 
-          function_object_ai_and_ai_prime(const function_object_ai_and_ai_prime&) = default;
+          #ifdef BOOST_MATH_ENABLE_CUDA
+          #  pragma nv_diag_suppress 20012
+          #endif
 
-          boost::math::tuple<T, T> operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED function_object_ai_and_ai_prime(const function_object_ai_and_ai_prime&) = default;
+
+          #ifdef BOOST_MATH_ENABLE_CUDA
+          #  pragma nv_diag_default 20012
+          #endif
+
+          BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(const T& x) const
           {
             // Return a tuple containing both Ai(x) and Ai'(x).
             return boost::math::make_tuple(
@@ -127,7 +137,7 @@
       namespace airy_bi_zero_detail
       {
         template<class T, class Policy>
-        T initial_guess(const int m, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T initial_guess(const int m, const Policy& pol)
         {
           T guess;
 
@@ -179,11 +189,19 @@
         class function_object_bi_and_bi_prime
         {
         public:
-          explicit function_object_bi_and_bi_prime(const Policy& pol) : my_pol(pol) { }
-
-          function_object_bi_and_bi_prime(const function_object_bi_and_bi_prime&) = default;
-
-          boost::math::tuple<T, T> operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED explicit function_object_bi_and_bi_prime(const Policy& pol) : my_pol(pol) { }
+
+          #ifdef BOOST_MATH_ENABLE_CUDA
+          #  pragma nv_diag_suppress 20012
+          #endif
+          
+          BOOST_MATH_GPU_ENABLED function_object_bi_and_bi_prime(const function_object_bi_and_bi_prime&) = default;
+          
+          #ifdef BOOST_MATH_ENABLE_CUDA
+          #  pragma nv_diag_default 20012
+          #endif
+
+          BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(const T& x) const
           {
             // Return a tuple containing both Bi(x) and Bi'(x).
             return boost::math::make_tuple(
diff --git a/include/boost/math/special_functions/detail/bessel_i0.hpp b/include/boost/math/special_functions/detail/bessel_i0.hpp
index af6e8c3794..f2219cc940 100644
--- a/include/boost/math/special_functions/detail/bessel_i0.hpp
+++ b/include/boost/math/special_functions/detail/bessel_i0.hpp
@@ -1,5 +1,6 @@
 //  Copyright (c) 2006 Xiaogang Zhang
 //  Copyright (c) 2017 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -14,6 +15,9 @@
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/precision.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -35,24 +39,24 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T>
-T bessel_i0(const T& x);
+BOOST_MATH_GPU_ENABLED T bessel_i0(const T& x);
 
 template <typename T, int N>
-T bessel_i0_imp(const T&, const std::integral_constant<int, N>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T&, const boost::math::integral_constant<int, N>&)
 {
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-T bessel_i0_imp(const T& x, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T& x, const boost::math::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
    {
       // Max error in interpolated form: 3.929e-08
       // Max Error found at float precision = Poly: 1.991226e-07
-      static const float P[] = {
+      BOOST_MATH_STATIC const float P[] = {
          1.00000003928615375e+00f,
          2.49999576572179639e-01f,
          2.77785268558399407e-02f,
@@ -70,7 +74,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 24>&)
    {
       // Max error in interpolated form: 5.195e-08
       // Max Error found at float precision = Poly: 8.502534e-08
-      static const float P[] = {
+      BOOST_MATH_STATIC const float P[] = {
          3.98942651588301770e-01f,
          4.98327234176892844e-02f,
          2.91866904423115499e-02f,
@@ -83,7 +87,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 24>&)
    {
       // Max error in interpolated form: 1.782e-09
       // Max Error found at float precision = Poly: 6.473568e-08
-      static const float P[] = {
+      BOOST_MATH_STATIC const float P[] = {
          3.98942391532752700e-01f,
          4.98455950638200020e-02f,
          2.94835666900682535e-02f
@@ -96,7 +100,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 24>&)
 }
 
 template <typename T>
-T bessel_i0_imp(const T& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T& x, const boost::math::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
@@ -104,7 +108,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 53>&)
       // Bessel I0 over[10 ^ -16, 7.75]
       // Max error in interpolated form : 3.042e-18
       // Max Error found at double precision = Poly : 5.106609e-16 Cheb : 5.239199e-16
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          1.00000000000000000e+00,
          2.49999999999999909e-01,
          2.77777777777782257e-02,
@@ -128,7 +132,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 53>&)
    {
       // Max error in interpolated form : 1.685e-16
       // Max Error found at double precision = Poly : 2.575063e-16 Cheb : 2.247615e+00
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          3.98942280401425088e-01,
          4.98677850604961985e-02,
          2.80506233928312623e-02,
@@ -158,7 +162,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 53>&)
    {
       // Max error in interpolated form : 2.437e-18
       // Max Error found at double precision = Poly : 1.216719e-16
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          3.98942280401432905e-01,
          4.98677850491434560e-02,
          2.80506308916506102e-02,
@@ -173,7 +177,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 53>&)
 }
 
 template <typename T>
-T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T& x, const boost::math::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
@@ -182,7 +186,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
       // Max error in interpolated form : 3.899e-20
       // Max Error found at float80 precision = Poly : 1.770840e-19
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, 9.99999999999999999961011629e-01),
          BOOST_MATH_BIG_CONSTANT(T, 64, 2.50000000000000001321873912e-01),
          BOOST_MATH_BIG_CONSTANT(T, 64, 2.77777777777777703400424216e-02),
@@ -211,8 +215,8 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
       // Maximum Relative Change in Control Points : 1.631e-04
       // Max Error found at float80 precision = Poly : 7.811948e-21
       // LCOV_EXCL_START
-      static const T Y = 4.051098823547363281250e-01f;
-      static const T P[] = {
+      BOOST_MATH_STATIC const T Y = 4.051098823547363281250e-01f;
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, -6.158081780620616479492e-03),
          BOOST_MATH_BIG_CONSTANT(T, 64, 4.883635969834048766148e-02),
          BOOST_MATH_BIG_CONSTANT(T, 64, 7.892782002476195771920e-02),
@@ -237,8 +241,8 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
       // Maximum Relative Change in Control Points : 1.304e-03
       // Max Error found at float80 precision = Poly : 2.303527e-20
       // LCOV_EXCL_START
-      static const T Y = 4.033188819885253906250e-01f;
-      static const T P[] = {
+      BOOST_MATH_STATIC const T Y = 4.033188819885253906250e-01f;
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, -4.376373876116109401062e-03),
          BOOST_MATH_BIG_CONSTANT(T, 64, 4.982899138682911273321e-02),
          BOOST_MATH_BIG_CONSTANT(T, 64, 3.109477529533515397644e-02),
@@ -262,8 +266,8 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
       // Max error in interpolated form: 1.035e-21
       // Max Error found at float80 precision = Poly: 1.885872e-21
       // LCOV_EXCL_START
-      static const T Y = 4.011702537536621093750e-01f;
-      static const T P[] = {
+      BOOST_MATH_STATIC const T Y = 4.011702537536621093750e-01f;
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, -2.227973351806078464328e-03),
          BOOST_MATH_BIG_CONSTANT(T, 64, 4.986778486088017419036e-02),
          BOOST_MATH_BIG_CONSTANT(T, 64, 2.805066823812285310011e-02),
@@ -291,7 +295,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
       // Max error in interpolated form : 5.587e-20
       // Max Error found at float80 precision = Poly : 8.776852e-20
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 64, 3.98942280401432677955074061e-01),
          BOOST_MATH_BIG_CONSTANT(T, 64, 4.98677850501789875615574058e-02),
          BOOST_MATH_BIG_CONSTANT(T, 64, 2.80506290908675604202206833e-02),
@@ -320,7 +324,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 64>&)
 }
 
 template <typename T>
-T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T& x, const boost::math::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
@@ -329,7 +333,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form : 1.274e-34
       // Max Error found at float128 precision = Poly : 3.096091e-34
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 1.0000000000000000000000000000000001273856e+00),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.4999999999999999999999999999999107477496e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.7777777777777777777777777777881795230918e-02),
@@ -364,7 +368,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form : 7.534e-35
       // Max Error found at float128 precision = Poly : 6.123912e-34
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 9.9999999999999999992388573069504617493518e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.5000000000000000007304739268173096975340e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.7777777777777777744261405400543564492074e-02),
@@ -403,7 +407,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form : 1.808e-34
       // Max Error found at float128 precision = Poly : 2.399403e-34
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.9894228040870793650581242239624530714032e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 4.9867780576714783790784348982178607842250e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.8051948347934462928487999569249907599510e-02),
@@ -445,7 +449,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form : 1.487e-34
       // Max Error found at float128 precision = Poly : 1.929924e-34
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.9894228040143267793996798658172135362278e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 4.9867785050179084714910130342157246539820e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.8050629090725751585266360464766768437048e-02),
@@ -480,7 +484,7 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form : 5.459e-35
       // Max Error found at float128 precision = Poly : 1.472240e-34
       // LCOV_EXCL_START
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.9894228040143267793994605993438166526772e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, 4.9867785050179084742493257495245185241487e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 2.8050629090725735167652437695397756897920e-02),
@@ -507,33 +511,33 @@ T bessel_i0_imp(const T& x, const std::integral_constant<int, 113>&)
 }
 
 template <typename T>
-T bessel_i0_imp(const T& x, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED T bessel_i0_imp(const T& x, const boost::math::integral_constant<int, 0>&)
 {
    if(boost::math::tools::digits<T>() <= 24)
-      return bessel_i0_imp(x, std::integral_constant<int, 24>());
+      return bessel_i0_imp(x, boost::math::integral_constant<int, 24>());
    else if(boost::math::tools::digits<T>() <= 53)
-      return bessel_i0_imp(x, std::integral_constant<int, 53>());
+      return bessel_i0_imp(x, boost::math::integral_constant<int, 53>());
    else if(boost::math::tools::digits<T>() <= 64)
-      return bessel_i0_imp(x, std::integral_constant<int, 64>());
+      return bessel_i0_imp(x, boost::math::integral_constant<int, 64>());
    else if(boost::math::tools::digits<T>() <= 113)
-      return bessel_i0_imp(x, std::integral_constant<int, 113>());
+      return bessel_i0_imp(x, boost::math::integral_constant<int, 113>());
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-inline T bessel_i0(const T& x)
+BOOST_MATH_GPU_ENABLED inline T bessel_i0(const T& x)
 {
-   typedef std::integral_constant<int,
-      ((std::numeric_limits<T>::digits == 0) || (std::numeric_limits<T>::radix != 2)) ?
+   typedef boost::math::integral_constant<int,
+      ((boost::math::numeric_limits<T>::digits == 0) || (boost::math::numeric_limits<T>::radix != 2)) ?
       0 :
-      std::numeric_limits<T>::digits <= 24 ?
+      boost::math::numeric_limits<T>::digits <= 24 ?
       24 :
-      std::numeric_limits<T>::digits <= 53 ?
+      boost::math::numeric_limits<T>::digits <= 53 ?
       53 :
-      std::numeric_limits<T>::digits <= 64 ?
+      boost::math::numeric_limits<T>::digits <= 64 ?
       64 :
-      std::numeric_limits<T>::digits <= 113 ?
+      boost::math::numeric_limits<T>::digits <= 113 ?
       113 : -1
    > tag_type;
 
diff --git a/include/boost/math/special_functions/detail/bessel_i1.hpp b/include/boost/math/special_functions/detail/bessel_i1.hpp
index badc35de0b..d2c750df06 100644
--- a/include/boost/math/special_functions/detail/bessel_i1.hpp
+++ b/include/boost/math/special_functions/detail/bessel_i1.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2017 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -17,9 +18,13 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/precision.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -38,24 +43,24 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T>
-T bessel_i1(const T& x);
+BOOST_MATH_GPU_ENABLED T bessel_i1(const T& x);
 
 template <typename T, int N>
-T bessel_i1_imp(const T&, const std::integral_constant<int, N>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T&, const boost::math::integral_constant<int, N>&)
 {
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-T bessel_i1_imp(const T& x, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T& x, const boost::math::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING
       if(x < 7.75)
       {
          //Max error in interpolated form : 1.348e-08
          // Max Error found at float precision = Poly : 1.469121e-07
-         static const float P[] = {
+         BOOST_MATH_STATIC const float P[] = {
             8.333333221e-02f,
             6.944453712e-03f,
             3.472097211e-04f,
@@ -74,7 +79,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 24>&)
          // Max error in interpolated form: 9.000e-08
          // Max Error found at float precision = Poly: 1.044345e-07
 
-         static const float P[] = {
+         BOOST_MATH_STATIC const float P[] = {
             3.98942115977513013e-01f,
             -1.49581264836620262e-01f,
             -4.76475741878486795e-02f,
@@ -89,7 +94,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 24>&)
 }
 
 template <typename T>
-T bessel_i1_imp(const T& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T& x, const boost::math::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
@@ -98,7 +103,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 53>&)
       // Max error in interpolated form: 5.639e-17
       // Max Error found at double precision = Poly: 1.795559e-16
 
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          8.333333333333333803e-02,
          6.944444444444341983e-03,
          3.472222222225921045e-04,
@@ -122,7 +127,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 53>&)
       // Max error in interpolated form: 1.796e-16
       // Max Error found at double precision = Poly: 2.898731e-16
 
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          3.989422804014406054e-01,
          -1.496033551613111533e-01,
          -4.675104253598537322e-02,
@@ -152,7 +157,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 53>&)
    {
       // Max error in interpolated form: 1.320e-19
       // Max Error found at double precision = Poly: 7.065357e-17
-      static const double P[] = {
+      BOOST_MATH_STATIC const double P[] = {
          3.989422804014314820e-01,
          -1.496033551467584157e-01,
          -4.675105322571775911e-02,
@@ -167,7 +172,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 53>&)
 }
 
 template <typename T>
-T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T& x, const boost::math::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING
       if(x < 7.75)
@@ -175,7 +180,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
          // Bessel I0 over[10 ^ -16, 7.75]
          // Max error in interpolated form: 8.086e-21
          // Max Error found at float80 precision = Poly: 7.225090e-20
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 8.33333333333333333340071817e-02),
             BOOST_MATH_BIG_CONSTANT(T, 64, 6.94444444444444442462728070e-03),
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.47222222222222318886683883e-04),
@@ -203,7 +208,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
          // Maximum Deviation Found : 3.887e-20
          // Expected Error Term : 3.887e-20
          // Maximum Relative Change in Control Points : 1.681e-04
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.98942260530218897338680e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.49599542849073670179540e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.70492865454119188276875e-02),
@@ -236,7 +241,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
          // Maximum Relative Change in Control Points : 2.101e-03
          // Max Error found at float80 precision = Poly : 6.029974e-20
 
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.98942280401431675205845e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.49603355149968887210170e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.67510486284376330257260e-02),
@@ -258,7 +263,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
          // Bessel I0 over[100, INF]
          // Max error in interpolated form: 2.456e-20
          // Max Error found at float80 precision = Poly: 5.446356e-20
-         static const T P[] = {
+         BOOST_MATH_STATIC const T P[] = {
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.98942280401432677958445e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.49603355150537411254359e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.67510484842456251368526e-02),
@@ -276,7 +281,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 64>&)
 }
 
 template <typename T>
-T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T& x, const boost::math::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING
    if(x < 7.75)
@@ -285,7 +290,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form: 1.835e-35
       // Max Error found at float128 precision = Poly: 1.645036e-34
 
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 8.3333333333333333333333333333333331804098e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 6.9444444444444444444444444444445418303082e-03),
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.4722222222222222222222222222119082346591e-04),
@@ -321,7 +326,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Maximum Relative Change in Control Points : 5.204e-03
       // Max Error found at float128 precision = Poly : 2.882561e-34
 
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 8.333333333333333326889717360850080939e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 6.944444444444444511272790848815114507e-03),
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.472222222222221892451965054394153443e-04),
@@ -355,7 +360,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Maximum Deviation Found : 1.766e-35
       // Expected Error Term : 1.021e-35
       // Maximum Relative Change in Control Points : 6.228e-03
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 8.333333333333255774414858563409941233e-02),
          BOOST_MATH_BIG_CONSTANT(T, 113, 6.944444444444897867884955912228700291e-03),
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.472222222220954970397343617150959467e-04),
@@ -389,7 +394,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
    {
       // Max error in interpolated form: 8.864e-36
       // Max Error found at float128 precision = Poly: 8.522841e-35
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.989422793693152031514179994954750043e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -1.496029423752889591425633234009799670e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -4.682975926820553021482820043377990241e-02),
@@ -421,7 +426,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form: 6.028e-35
       // Max Error found at float128 precision = Poly: 1.368313e-34
 
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.989422804012941975429616956496046931e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -1.496033550576049830976679315420681402e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -4.675107835141866009896710750800622147e-02),
@@ -456,7 +461,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Max error in interpolated form: 5.494e-35
       // Max Error found at float128 precision = Poly: 1.214651e-34
 
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.989422804014326779399307367861631577e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -1.496033551505372542086590873271571919e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -4.675104848454290286276466276677172664e-02),
@@ -486,7 +491,7 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
       // Bessel I0 over[100, INF]
       // Max error in interpolated form: 6.081e-35
       // Max Error found at float128 precision = Poly: 1.407151e-34
-      static const T P[] = {
+      BOOST_MATH_STATIC const T P[] = {
          BOOST_MATH_BIG_CONSTANT(T, 113, 3.9894228040143267793994605993438200208417e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -1.4960335515053725422747977247811372936584e-01),
          BOOST_MATH_BIG_CONSTANT(T, 113, -4.6751048484542891946087411826356811991039e-02),
@@ -512,33 +517,33 @@ T bessel_i1_imp(const T& x, const std::integral_constant<int, 113>&)
 }
 
 template <typename T>
-T bessel_i1_imp(const T& x, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED T bessel_i1_imp(const T& x, const boost::math::integral_constant<int, 0>&)
 {
    if(boost::math::tools::digits<T>() <= 24)
-      return bessel_i1_imp(x, std::integral_constant<int, 24>());
+      return bessel_i1_imp(x, boost::math::integral_constant<int, 24>());
    else if(boost::math::tools::digits<T>() <= 53)
-      return bessel_i1_imp(x, std::integral_constant<int, 53>());
+      return bessel_i1_imp(x, boost::math::integral_constant<int, 53>());
    else if(boost::math::tools::digits<T>() <= 64)
-      return bessel_i1_imp(x, std::integral_constant<int, 64>());
+      return bessel_i1_imp(x, boost::math::integral_constant<int, 64>());
    else if(boost::math::tools::digits<T>() <= 113)
-      return bessel_i1_imp(x, std::integral_constant<int, 113>());
+      return bessel_i1_imp(x, boost::math::integral_constant<int, 113>());
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-inline T bessel_i1(const T& x)
+inline BOOST_MATH_GPU_ENABLED T bessel_i1(const T& x)
 {
-   typedef std::integral_constant<int,
-      ((std::numeric_limits<T>::digits == 0) || (std::numeric_limits<T>::radix != 2)) ?
+   typedef boost::math::integral_constant<int,
+      ((boost::math::numeric_limits<T>::digits == 0) || (boost::math::numeric_limits<T>::radix != 2)) ?
       0 :
-      std::numeric_limits<T>::digits <= 24 ?
+      boost::math::numeric_limits<T>::digits <= 24 ?
       24 :
-      std::numeric_limits<T>::digits <= 53 ?
+      boost::math::numeric_limits<T>::digits <= 53 ?
       53 :
-      std::numeric_limits<T>::digits <= 64 ?
+      boost::math::numeric_limits<T>::digits <= 64 ?
       64 :
-      std::numeric_limits<T>::digits <= 113 ?
+      boost::math::numeric_limits<T>::digits <= 113 ?
       113 : -1
    > tag_type;
 
diff --git a/include/boost/math/special_functions/detail/bessel_ik.hpp b/include/boost/math/special_functions/detail/bessel_ik.hpp
index 0c653b4753..b3e7378fd4 100644
--- a/include/boost/math/special_functions/detail/bessel_ik.hpp
+++ b/include/boost/math/special_functions/detail/bessel_ik.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2006 Xiaogang Zhang
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,14 +11,17 @@
 #pragma once
 #endif
 
-#include <cmath>
-#include <cstdint>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/series.hpp>
+#include <boost/math/special_functions/sign.hpp>
 #include <boost/math/special_functions/round.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/sin_pi.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/policies/error_handling.hpp>
-#include <boost/math/tools/config.hpp>
 
 // Modified Bessel functions of the first and second kind of fractional order
 
@@ -30,13 +34,13 @@ struct cyl_bessel_i_small_z
 {
    typedef T result_type;
 
-   cyl_bessel_i_small_z(T v_, T z_) : k(0), v(v_), mult(z_*z_/4)
+   BOOST_MATH_GPU_ENABLED cyl_bessel_i_small_z(T v_, T z_) : k(0), v(v_), mult(z_*z_/4)
    {
       BOOST_MATH_STD_USING
       term = 1;
    }
 
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T result = term;
       ++k;
@@ -52,7 +56,7 @@ struct cyl_bessel_i_small_z
 };
 
 template <class T, class Policy>
-inline T bessel_i_small_z_series(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T bessel_i_small_z_series(T v, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    T prefix;
@@ -69,7 +73,7 @@ inline T bessel_i_small_z_series(T v, T x, const Policy& pol)
       return prefix;
 
    cyl_bessel_i_small_z<T, Policy> s(v, x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
 
@@ -80,7 +84,7 @@ inline T bessel_i_small_z_series(T v, T x, const Policy& pol)
 // Calculate K(v, x) and K(v+1, x) by method analogous to
 // Temme, Journal of Computational Physics, vol 21, 343 (1976)
 template <typename T, typename Policy>
-int temme_ik(T v, T x, T* result_K, T* K1, const Policy& pol)
+BOOST_MATH_GPU_ENABLED int temme_ik(T v, T x, T* result_K, T* K1, const Policy& pol)
 {
     T f, h, p, q, coef, sum, sum1, tolerance;
     T a, b, c, d, sigma, gamma1, gamma2;
@@ -157,7 +161,7 @@ int temme_ik(T v, T x, T* result_K, T* K1, const Policy& pol)
 // Evaluate continued fraction fv = I_(v+1) / I_v, derived from
 // Abramowitz and Stegun, Handbook of Mathematical Functions, 1972, 9.1.73
 template <typename T, typename Policy>
-int CF1_ik(T v, T x, T* fv, const Policy& pol)
+BOOST_MATH_GPU_ENABLED int CF1_ik(T v, T x, T* fv, const Policy& pol)
 {
     T C, D, f, a, b, delta, tiny, tolerance;
     unsigned long k;
@@ -204,7 +208,7 @@ int CF1_ik(T v, T x, T* fv, const Policy& pol)
 // z1 / z0 = U(v+1.5, 2v+1, 2x) / U(v+0.5, 2v+1, 2x), see
 // Thompson and Barnett, Computer Physics Communications, vol 47, 245 (1987)
 template <typename T, typename Policy>
-int CF2_ik(T v, T x, T* Kv, T* Kv1, const Policy& pol)
+BOOST_MATH_GPU_ENABLED int CF2_ik(T v, T x, T* Kv, T* Kv1, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::constants;
@@ -297,7 +301,7 @@ enum{
 // Compute I(v, x) and K(v, x) simultaneously by Temme's method, see
 // Temme, Journal of Computational Physics, vol 19, 324 (1975)
 template <typename T, typename Policy>
-int bessel_ik(T v, T x, T* result_I, T* result_K, int kind, const Policy& pol)
+BOOST_MATH_GPU_ENABLED int bessel_ik(T v, T x, T* result_I, T* result_K, int kind, const Policy& pol)
 {
     // Kv1 = K_(v+1), fv = I_(v+1) / I_v
     // Ku1 = K_(u+1), fu = I_(u+1) / I_u
@@ -314,7 +318,7 @@ int bessel_ik(T v, T x, T* result_I, T* result_K, int kind, const Policy& pol)
     using namespace boost::math::tools;
     using namespace boost::math::constants;
 
-    static const char* function = "boost::math::bessel_ik<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::bessel_ik<%1%>(%1%,%1%)";
 
     if (v < 0)
     {
@@ -329,7 +333,7 @@ int bessel_ik(T v, T x, T* result_I, T* result_K, int kind, const Policy& pol)
     if (((kind & need_i) == 0) && (fabs(4 * v * v - 25) / (8 * x) < tools::forth_root_epsilon<T>()))
     {
        // A&S 9.7.2
-       Iv = std::numeric_limits<T>::quiet_NaN(); // any value will do
+       Iv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do
        T mu = 4 * v * v;
        T eight_z = 8 * x;
        Kv = 1 + (mu - 1) / eight_z + (mu - 1) * (mu - 9) / (2 * eight_z * eight_z) + (mu - 1) * (mu - 9) * (mu - 25) / (6 * eight_z * eight_z * eight_z);
@@ -410,7 +414,7 @@ int bessel_ik(T v, T x, T* result_I, T* result_K, int kind, const Policy& pol)
           }
        }
        else
-          Iv = std::numeric_limits<T>::quiet_NaN(); // any value will do
+          Iv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do
     }
     if (reflect)
     {
diff --git a/include/boost/math/special_functions/detail/bessel_j0.hpp b/include/boost/math/special_functions/detail/bessel_j0.hpp
index 9a0b26fe6b..2df027b21d 100644
--- a/include/boost/math/special_functions/detail/bessel_j0.hpp
+++ b/include/boost/math/special_functions/detail/bessel_j0.hpp
@@ -10,6 +10,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -32,10 +33,10 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T>
-T bessel_j0(T x);
+BOOST_MATH_GPU_ENABLED T bessel_j0(T x);
 
 template <typename T>
-T bessel_j0(T x)
+BOOST_MATH_GPU_ENABLED T bessel_j0(T x)
 {
 #ifdef BOOST_MATH_INSTRUMENT
     static bool b = false;
@@ -48,7 +49,7 @@ T bessel_j0(T x)
     }
 #endif
 
-    static const T P1[] = {
+    BOOST_MATH_STATIC const T P1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -4.1298668500990866786e+11)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.7282507878605942706e+10)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -6.2140700423540120665e+08)),
@@ -57,7 +58,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0344222815443188943e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2117036164593528341e-01))
     };
-    static const T Q1[] = {
+    BOOST_MATH_STATIC const T Q1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.3883787996332290397e+12)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.6328198300859648632e+10)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.3985097372263433271e+08)),
@@ -66,7 +67,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0))
     };
-    static const T P2[] = {
+    BOOST_MATH_STATIC const T P2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.8319397969392084011e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2254078161378989535e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -7.2879702464464618998e+03)),
@@ -76,7 +77,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.4321196680624245801e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.8591703355916499363e+01))
     };
-    static const T Q2[] = {
+    BOOST_MATH_STATIC const T Q2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.5783478026152301072e+05)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.4599102262586308984e+05)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.4055062591169562211e+04)),
@@ -86,7 +87,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -2.5258076240801555057e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T PC[] = {
+    BOOST_MATH_STATIC const T PC[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2779090197304684302e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1345386639580765797e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1170523380864944322e+04)),
@@ -94,7 +95,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.5376201909008354296e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.8961548424210455236e-01))
     };
-    static const T QC[] = {
+    BOOST_MATH_STATIC const T QC[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2779090197304684318e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1370412495510416640e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1215350561880115730e+04)),
@@ -102,7 +103,7 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.5711159858080893649e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T PS[] = {
+    BOOST_MATH_STATIC const T PS[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.9226600200800094098e+01)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.8591953644342993800e+02)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.1183429920482737611e+02)),
@@ -110,7 +111,7 @@ T bessel_j0(T x)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2441026745835638459e+00)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.8033303048680751817e-03))
     };
-    static const T QS[] = {
+    BOOST_MATH_STATIC const T QS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.7105024128512061905e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.1951131543434613647e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.2642780169211018836e+03)),
@@ -118,12 +119,13 @@ T bessel_j0(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 9.0593769594993125859e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.4048255576957727686e+00)),
-                   x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.5200781102863106496e+00)),
-                   x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.160e+02)),
-                   x12 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.42444230422723137837e-03)),
-                   x21 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.4130e+03)),
-                   x22 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.46860286310649596604e-04));
+
+    BOOST_MATH_STATIC const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.4048255576957727686e+00));
+    BOOST_MATH_STATIC const T x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.5200781102863106496e+00));
+    BOOST_MATH_STATIC const T x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.160e+02));
+    BOOST_MATH_STATIC const T x12 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.42444230422723137837e-03));
+    BOOST_MATH_STATIC const T x21 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.4130e+03));
+    BOOST_MATH_STATIC const T x22 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.46860286310649596604e-04));
 
     T value, factor, r, rc, rs;
 
diff --git a/include/boost/math/special_functions/detail/bessel_j1.hpp b/include/boost/math/special_functions/detail/bessel_j1.hpp
index 6d354dcce7..43df9fa0c1 100644
--- a/include/boost/math/special_functions/detail/bessel_j1.hpp
+++ b/include/boost/math/special_functions/detail/bessel_j1.hpp
@@ -10,6 +10,7 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -32,27 +33,29 @@
 namespace boost { namespace math{  namespace detail{
 
 template <typename T>
-T bessel_j1(T x);
+BOOST_MATH_GPU_ENABLED T bessel_j1(T x);
 
 template <class T>
 struct bessel_j1_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init();
       }
-      static void do_init()
+      BOOST_MATH_GPU_ENABLED static void do_init()
       {
          bessel_j1(T(1));
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -60,11 +63,11 @@ template <class T>
 const typename bessel_j1_initializer<T>::init bessel_j1_initializer<T>::initializer;
 
 template <typename T>
-T bessel_j1(T x)
+BOOST_MATH_GPU_ENABLED T bessel_j1(T x)
 {
     bessel_j1_initializer<T>::force_instantiate();
 
-    static const T P1[] = {
+    BOOST_MATH_STATIC const T P1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.4258509801366645672e+11)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.6781041261492395835e+09)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.1548696764841276794e+08)),
@@ -73,7 +76,7 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0650724020080236441e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.0767857011487300348e-02))
     };
-    static const T Q1[] = {
+    BOOST_MATH_STATIC const T Q1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1868604460820175290e+12)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.2091902282580133541e+10)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.0228375140097033958e+08)),
@@ -82,7 +85,7 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0))
     };
-    static const T P2[] = {
+    BOOST_MATH_STATIC const T P2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.7527881995806511112e+16)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.6608531731299018674e+15)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.6658018905416665164e+13)),
@@ -92,7 +95,7 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -7.5023342220781607561e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.6179191852758252278e+00))
     };
-    static const T Q2[] = {
+    BOOST_MATH_STATIC const T Q2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.7253905888447681194e+18)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.7128800897135812012e+16)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.4899346165481429307e+13)),
@@ -102,7 +105,7 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.3886978985861357615e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T PC[] = {
+    BOOST_MATH_STATIC const T PC[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -4.4357578167941278571e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -9.9422465050776411957e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -6.6033732483649391093e+06)),
@@ -111,7 +114,7 @@ T bessel_j1(T x)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.6116166443246101165e+03)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0))
     };
-    static const T QC[] = {
+    BOOST_MATH_STATIC const T QC[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -4.4357578167941278568e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -9.9341243899345856590e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -6.5853394797230870728e+06)),
@@ -120,7 +123,7 @@ T bessel_j1(T x)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.4550094401904961825e+03)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T PS[] = {
+    BOOST_MATH_STATIC const T PS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.3220913409857223519e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.5145160675335701966e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.6178836581270835179e+04)),
@@ -129,7 +132,7 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.5265133846636032186e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0))
     };
-    static const T QS[] = {
+    BOOST_MATH_STATIC const T QS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.0871281941028743574e+05)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.8194580422439972989e+06)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.4194606696037208929e+06)),
@@ -138,12 +141,13 @@ T bessel_j1(T x)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.6383677696049909675e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0))
     };
-    static const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.8317059702075123156e+00)),
-                   x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.0155866698156187535e+00)),
-                   x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 9.810e+02)),
-                   x12 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.2527979248768438556e-04)),
-                   x21 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.7960e+03)),
-                   x22 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.8330184381246462950e-05));
+
+    BOOST_MATH_STATIC const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.8317059702075123156e+00));
+    BOOST_MATH_STATIC const T x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.0155866698156187535e+00));
+    BOOST_MATH_STATIC const T x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 9.810e+02));
+    BOOST_MATH_STATIC const T x12 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.2527979248768438556e-04));
+    BOOST_MATH_STATIC const T x21 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.7960e+03));
+    BOOST_MATH_STATIC const T x22 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.8330184381246462950e-05));
 
     T value, factor, r, rc, rs, w;
 
diff --git a/include/boost/math/special_functions/detail/bessel_jn.hpp b/include/boost/math/special_functions/detail/bessel_jn.hpp
index a08af05485..73bc0c5621 100644
--- a/include/boost/math/special_functions/detail/bessel_jn.hpp
+++ b/include/boost/math/special_functions/detail/bessel_jn.hpp
@@ -10,6 +10,10 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/assert.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/detail/bessel_j0.hpp>
 #include <boost/math/special_functions/detail/bessel_j1.hpp>
 #include <boost/math/special_functions/detail/bessel_jy.hpp>
@@ -24,7 +28,7 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T bessel_jn(int n, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T bessel_jn(int n, T x, const Policy& pol)
 {
     T value(0), factor, current, prev, next;
 
diff --git a/include/boost/math/special_functions/detail/bessel_jy.hpp b/include/boost/math/special_functions/detail/bessel_jy.hpp
index 90e099eb77..143dce872c 100644
--- a/include/boost/math/special_functions/detail/bessel_jy.hpp
+++ b/include/boost/math/special_functions/detail/bessel_jy.hpp
@@ -11,16 +11,18 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/sign.hpp>
 #include <boost/math/special_functions/hypot.hpp>
 #include <boost/math/special_functions/sin_pi.hpp>
 #include <boost/math/special_functions/cos_pi.hpp>
+#include <boost/math/special_functions/round.hpp>
 #include <boost/math/special_functions/detail/bessel_jy_asym.hpp>
 #include <boost/math/special_functions/detail/bessel_jy_series.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/policies/error_handling.hpp>
-#include <complex>
 
 // Bessel functions of the first and second kind of fractional order
 
@@ -38,7 +40,7 @@ namespace boost { namespace math {
       // try it and see...
       //
       template <class T, class Policy>
-      bool hankel_PQ(T v, T x, T* p, T* q, const Policy& )
+      BOOST_MATH_GPU_ENABLED bool hankel_PQ(T v, T x, T* p, T* q, const Policy& )
       {
          BOOST_MATH_STD_USING
             T tolerance = 2 * policies::get_epsilon<T, Policy>();
@@ -70,7 +72,7 @@ namespace boost { namespace math {
       // Calculate Y(v, x) and Y(v+1, x) by Temme's method, see
       // Temme, Journal of Computational Physics, vol 21, 343 (1976)
       template <typename T, typename Policy>
-      int temme_jy(T v, T x, T* Y, T* Y1, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED int temme_jy(T v, T x, T* Y, T* Y1, const Policy& pol)
       {
          T g, h, p, q, f, coef, sum, sum1, tolerance;
          T a, d, e, sigma;
@@ -139,7 +141,7 @@ namespace boost { namespace math {
       // Evaluate continued fraction fv = J_(v+1) / J_v, see
       // Abramowitz and Stegun, Handbook of Mathematical Functions, 1972, 9.1.73
       template <typename T, typename Policy>
-      int CF1_jy(T v, T x, T* fv, int* sign, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED int CF1_jy(T v, T x, T* fv, int* sign, const Policy& pol)
       {
          T C, D, f, a, b, delta, tiny, tolerance;
          unsigned long k;
@@ -185,7 +187,7 @@ namespace boost { namespace math {
       // real values only.
       //
       template <typename T, typename Policy>
-      int CF2_jy(T v, T x, T* p, T* q, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED int CF2_jy(T v, T x, T* p, T* q, const Policy& pol)
       {
          BOOST_MATH_STD_USING
 
@@ -254,13 +256,13 @@ namespace boost { namespace math {
          return 0;
       }
 
-      static const int need_j = 1;
-      static const int need_y = 2;
+      BOOST_MATH_STATIC const int need_j = 1;
+      BOOST_MATH_STATIC const int need_y = 2;
 
       // Compute J(v, x) and Y(v, x) simultaneously by Steed's method, see
       // Barnett et al, Computer Physics Communications, vol 8, 377 (1974)
       template <typename T, typename Policy>
-      int bessel_jy(T v, T x, T* J, T* Y, int kind, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED int bessel_jy(T v, T x, T* J, T* Y, int kind, const Policy& pol)
       {
          BOOST_MATH_ASSERT(x >= 0);
 
@@ -273,7 +275,7 @@ namespace boost { namespace math {
          T cp = 0;
          T sp = 0;
 
-         static const char* function = "boost::math::bessel_jy<%1%>(%1%,%1%)";
+         constexpr auto function = "boost::math::bessel_jy<%1%>(%1%,%1%)";
 
          BOOST_MATH_STD_USING
             using namespace boost::math::tools;
@@ -284,7 +286,7 @@ namespace boost { namespace math {
             reflect = true;
             v = -v;                             // v is non-negative from here
          }
-         if (v > static_cast<T>((std::numeric_limits<int>::max)()))
+         if (v > static_cast<T>((boost::math::numeric_limits<int>::max)()))
          {
             *J = *Y = policies::raise_evaluation_error<T>(function, "Order of Bessel function is too large to evaluate: got %1%", v, pol);
             return 1;  // LCOV_EXCL_LINE previous line will throw.
@@ -310,10 +312,10 @@ namespace boost { namespace math {
             else if(kind & need_j)
                *J = policies::raise_domain_error<T>(function, "Value of Bessel J_v(x) is complex-infinity at %1%", x, pol); // complex infinity
             else
-               *J = std::numeric_limits<T>::quiet_NaN();  // LCOV_EXCL_LINE, we should never get here, any value will do, not using J.
+               *J = boost::math::numeric_limits<T>::quiet_NaN();  // LCOV_EXCL_LINE, we should never get here, any value will do, not using J.
 
             if((kind & need_y) == 0)
-               *Y = std::numeric_limits<T>::quiet_NaN();  // any value will do, not using Y.
+               *Y = boost::math::numeric_limits<T>::quiet_NaN();  // any value will do, not using Y.
             else
             {
                // We shoud never get here:
@@ -333,7 +335,7 @@ namespace boost { namespace math {
             // and divergent which leads to large errors :-(
             //
             Jv = bessel_j_small_z_series(v, x, pol);
-            Yv = std::numeric_limits<T>::quiet_NaN();
+            Yv = boost::math::numeric_limits<T>::quiet_NaN();
          }
          else if((x < 1) && (u != 0) && (log(policies::get_epsilon<T, Policy>() / 2) > v * log((x/2) * (x/2) / v)))
          {
@@ -344,7 +346,7 @@ namespace boost { namespace math {
             if(kind&need_j)
                Jv = bessel_j_small_z_series(v, x, pol);
             else
-               Jv = std::numeric_limits<T>::quiet_NaN();
+               Jv = boost::math::numeric_limits<T>::quiet_NaN();
             if((org_kind&need_y && (!reflect || (cp != 0)))
                || (org_kind & need_j && (reflect && (sp != 0))))
             {
@@ -352,7 +354,7 @@ namespace boost { namespace math {
                Yv = bessel_y_small_z_series(v, x, &Yv_scale, pol);
             }
             else
-               Yv = std::numeric_limits<T>::quiet_NaN();
+               Yv = boost::math::numeric_limits<T>::quiet_NaN();
          }
          else if((u == 0) && (x < policies::get_epsilon<T, Policy>()))
          {
@@ -363,7 +365,7 @@ namespace boost { namespace math {
             if(kind&need_j)
                Jv = bessel_j_small_z_series(v, x, pol);
             else
-               Jv = std::numeric_limits<T>::quiet_NaN();
+               Jv = boost::math::numeric_limits<T>::quiet_NaN();
             if((org_kind&need_y && (!reflect || (cp != 0)))
                || (org_kind & need_j && (reflect && (sp != 0))))
             {
@@ -371,7 +373,7 @@ namespace boost { namespace math {
                Yv = bessel_yn_small_z(n, x, &Yv_scale, pol);
             }
             else
-               Yv = std::numeric_limits<T>::quiet_NaN();
+               Yv = boost::math::numeric_limits<T>::quiet_NaN();
             // LCOV_EXCL_STOP
          }
          else if(asymptotic_bessel_large_x_limit(v, x))
@@ -381,13 +383,13 @@ namespace boost { namespace math {
                Yv = asymptotic_bessel_y_large_x_2(v, x, pol);
             }
             else
-               Yv = std::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
+               Yv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
             if(kind&need_j)
             {
                Jv = asymptotic_bessel_j_large_x_2(v, x, pol);
             }
             else
-               Jv = std::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
+               Jv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
          }
          else if((x > 8) && hankel_PQ(v, x, &p, &q, pol))
          {
@@ -449,7 +451,7 @@ namespace boost { namespace math {
                Jv = scale * W / (Yv * fv - Yv1);           // Wronskian relation
             }
             else
-               Jv = std::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
+               Jv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
             Yv_scale = scale;
          }
          else                                    // x in (2, \infty)
@@ -564,7 +566,7 @@ namespace boost { namespace math {
                Yv = prev;
             }
             else
-               Yv = std::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
+               Yv = boost::math::numeric_limits<T>::quiet_NaN(); // any value will do, we're not using it.
          }
 
          if (reflect)
diff --git a/include/boost/math/special_functions/detail/bessel_jy_asym.hpp b/include/boost/math/special_functions/detail/bessel_jy_asym.hpp
index cb09b202d5..51e4efafca 100644
--- a/include/boost/math/special_functions/detail/bessel_jy_asym.hpp
+++ b/include/boost/math/special_functions/detail/bessel_jy_asym.hpp
@@ -16,12 +16,15 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/factorials.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
 template <class T>
-inline T asymptotic_bessel_amplitude(T v, T x)
+BOOST_MATH_GPU_ENABLED inline T asymptotic_bessel_amplitude(T v, T x)
 {
    // Calculate the amplitude of J(v, x) and Y(v, x) for large
    // x: see A&S 9.2.28.
@@ -39,7 +42,7 @@ inline T asymptotic_bessel_amplitude(T v, T x)
 }
 
 template <class T>
-T asymptotic_bessel_phase_mx(T v, T x)
+BOOST_MATH_GPU_ENABLED T asymptotic_bessel_phase_mx(T v, T x)
 {
    //
    // Calculate the phase of J(v, x) and Y(v, x) for large x.
@@ -63,7 +66,7 @@ T asymptotic_bessel_phase_mx(T v, T x)
 }
 
 template <class T, class Policy>
-inline T asymptotic_bessel_y_large_x_2(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T asymptotic_bessel_y_large_x_2(T v, T x, const Policy& pol)
 {
    // See A&S 9.2.19.
    BOOST_MATH_STD_USING
@@ -93,7 +96,7 @@ inline T asymptotic_bessel_y_large_x_2(T v, T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline T asymptotic_bessel_j_large_x_2(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T asymptotic_bessel_j_large_x_2(T v, T x, const Policy& pol)
 {
    // See A&S 9.2.19.
    BOOST_MATH_STD_USING
@@ -124,7 +127,7 @@ inline T asymptotic_bessel_j_large_x_2(T v, T x, const Policy& pol)
 }
 
 template <class T>
-inline bool asymptotic_bessel_large_x_limit(int v, const T& x)
+BOOST_MATH_GPU_ENABLED inline bool asymptotic_bessel_large_x_limit(int v, const T& x)
 {
    BOOST_MATH_STD_USING
       //
@@ -142,7 +145,7 @@ inline bool asymptotic_bessel_large_x_limit(int v, const T& x)
 }
 
 template <class T>
-inline bool asymptotic_bessel_large_x_limit(const T& v, const T& x)
+BOOST_MATH_GPU_ENABLED inline bool asymptotic_bessel_large_x_limit(const T& v, const T& x)
 {
    BOOST_MATH_STD_USING
    //
@@ -155,11 +158,11 @@ inline bool asymptotic_bessel_large_x_limit(const T& v, const T& x)
    // error rates either side of the divide for v < 10000.
    // At double precision eps^1/8 ~= 0.01.
    //
-   return (std::max)(T(fabs(v)), T(1)) < x * sqrt(tools::forth_root_epsilon<T>());
+   return BOOST_MATH_GPU_SAFE_MAX(T(fabs(v)), T(1)) < x * sqrt(tools::forth_root_epsilon<T>());
 }
 
 template <class T, class Policy>
-void temme_asymptotic_y_small_x(T v, T x, T* Y, T* Y1, const Policy& pol)
+BOOST_MATH_GPU_ENABLED void temme_asymptotic_y_small_x(T v, T x, T* Y, T* Y1, const Policy& pol)
 {
    T c = 1;
    T p = (v / boost::math::sin_pi(v, pol)) * pow(x / 2, -v) / boost::math::tgamma(1 - v, pol);
@@ -193,7 +196,7 @@ void temme_asymptotic_y_small_x(T v, T x, T* Y, T* Y1, const Policy& pol)
 }
 
 template <class T, class Policy>
-T asymptotic_bessel_i_large_x(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T asymptotic_bessel_i_large_x(T v, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // ADL of std names
    T s = 1;
diff --git a/include/boost/math/special_functions/detail/bessel_jy_series.hpp b/include/boost/math/special_functions/detail/bessel_jy_series.hpp
index db46f36400..5c083f3483 100644
--- a/include/boost/math/special_functions/detail/bessel_jy_series.hpp
+++ b/include/boost/math/special_functions/detail/bessel_jy_series.hpp
@@ -10,10 +10,9 @@
 #pragma once
 #endif
 
-#include <cmath>
-#include <cstdint>
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 namespace boost { namespace math { namespace detail{
 
@@ -22,7 +21,7 @@ struct bessel_j_small_z_series_term
 {
    typedef T result_type;
 
-   bessel_j_small_z_series_term(T v_, T x)
+   BOOST_MATH_GPU_ENABLED bessel_j_small_z_series_term(T v_, T x)
       : N(0), v(v_)
    {
       BOOST_MATH_STD_USING
@@ -30,7 +29,7 @@ struct bessel_j_small_z_series_term
       mult *= -mult;
       term = 1;
    }
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = term;
       ++N;
@@ -49,7 +48,7 @@ struct bessel_j_small_z_series_term
 // Converges rapidly for all z << v.
 //
 template <class T, class Policy>
-inline T bessel_j_small_z_series(T v, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T bessel_j_small_z_series(T v, T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    T prefix;
@@ -66,7 +65,7 @@ inline T bessel_j_small_z_series(T v, T x, const Policy& pol)
       return prefix;
 
    bessel_j_small_z_series_term<T, Policy> s(v, x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
 
@@ -79,7 +78,7 @@ struct bessel_y_small_z_series_term_a
 {
    typedef T result_type;
 
-   bessel_y_small_z_series_term_a(T v_, T x)
+   BOOST_MATH_GPU_ENABLED bessel_y_small_z_series_term_a(T v_, T x)
       : N(0), v(v_)
    {
       BOOST_MATH_STD_USING
@@ -87,7 +86,7 @@ struct bessel_y_small_z_series_term_a
       mult *= -mult;
       term = 1;
    }
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       BOOST_MATH_STD_USING
       T r = term;
@@ -107,7 +106,7 @@ struct bessel_y_small_z_series_term_b
 {
    typedef T result_type;
 
-   bessel_y_small_z_series_term_b(T v_, T x)
+   BOOST_MATH_GPU_ENABLED bessel_y_small_z_series_term_b(T v_, T x)
       : N(0), v(v_)
    {
       BOOST_MATH_STD_USING
@@ -115,7 +114,7 @@ struct bessel_y_small_z_series_term_b
       mult *= -mult;
       term = 1;
    }
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       T r = term;
       ++N;
@@ -138,10 +137,10 @@ struct bessel_y_small_z_series_term_b
 // eps/2 * v^v(x/2)^-v > (x/2)^v or log(eps/2) > v log((x/2)^2/v)
 //
 template <class T, class Policy>
-inline T bessel_y_small_z_series(T v, T x, T* pscale, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T bessel_y_small_z_series(T v, T x, T* pscale, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "bessel_y_small_z_series<%1%>(%1%,%1%)";
+   constexpr auto function = "bessel_y_small_z_series<%1%>(%1%,%1%)";
    T prefix;
    T gam;
    T p = log(x / 2);
@@ -183,7 +182,7 @@ inline T bessel_y_small_z_series(T v, T x, T* pscale, const Policy& pol)
       prefix = -exp(prefix);
    }
    bessel_y_small_z_series_term_a<T, Policy> s(v, x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    *pscale = scale;
 
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
@@ -211,7 +210,7 @@ inline T bessel_y_small_z_series(T v, T x, T* pscale, const Policy& pol)
 }
 
 template <class T, class Policy>
-T bessel_yn_small_z(int n, T z, T* scale, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T bessel_yn_small_z(int n, T z, T* scale, const Policy& pol)
 {
    //
    // See http://functions.wolfram.com/Bessel-TypeFunctions/BesselY/06/01/04/01/02/
diff --git a/include/boost/math/special_functions/detail/bessel_jy_zero.hpp b/include/boost/math/special_functions/detail/bessel_jy_zero.hpp
index cb1fc48d83..15671c0df7 100644
--- a/include/boost/math/special_functions/detail/bessel_jy_zero.hpp
+++ b/include/boost/math/special_functions/detail/bessel_jy_zero.hpp
@@ -18,19 +18,30 @@
 #ifndef BOOST_MATH_BESSEL_JY_ZERO_2013_01_18_HPP_
   #define BOOST_MATH_BESSEL_JY_ZERO_2013_01_18_HPP_
 
-  #include <algorithm>
+  #include <boost/math/tools/config.hpp>
+  #include <boost/math/tools/tuple.hpp>
+  #include <boost/math/tools/precision.hpp>
+  #include <boost/math/tools/cstdint.hpp>
+  #include <boost/math/tools/roots.hpp>
   #include <boost/math/constants/constants.hpp>
-  #include <boost/math/special_functions/math_fwd.hpp>
   #include <boost/math/special_functions/cbrt.hpp>
   #include <boost/math/special_functions/detail/airy_ai_bi_zero.hpp>
 
+  #ifndef BOOST_MATH_HAS_NVRTC
+  #include <boost/math/special_functions/math_fwd.hpp>
+  #endif
+
+  #ifdef BOOST_MATH_ENABLE_CUDA
+  #  pragma nv_diag_suppress 20012
+  #endif
+
   namespace boost { namespace math {
   namespace detail
   {
     namespace bessel_zero
     {
       template<class T>
-      T equation_nist_10_21_19(const T& v, const T& a)
+      BOOST_MATH_GPU_ENABLED T equation_nist_10_21_19(const T& v, const T& a)
       {
         // Get the initial estimate of the m'th root of Jv or Yv.
         // This subroutine is used for the order m with m > 1.
@@ -57,11 +68,11 @@
       class equation_as_9_3_39_and_its_derivative
       {
       public:
-        explicit equation_as_9_3_39_and_its_derivative(const T& zt) : zeta(zt) { }
+        BOOST_MATH_GPU_ENABLED explicit equation_as_9_3_39_and_its_derivative(const T& zt) : zeta(zt) { }
 
-        equation_as_9_3_39_and_its_derivative(const equation_as_9_3_39_and_its_derivative&) = default;
+        BOOST_MATH_GPU_ENABLED equation_as_9_3_39_and_its_derivative(const equation_as_9_3_39_and_its_derivative&) = default;
 
-        boost::math::tuple<T, T> operator()(const T& z) const
+        BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(const T& z) const
         {
           BOOST_MATH_STD_USING // ADL of std names, needed for acos, sqrt.
 
@@ -86,7 +97,7 @@
       };
 
       template<class T, class Policy>
-      static T equation_as_9_5_26(const T& v, const T& ai_bi_root, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED T equation_as_9_5_26(const T& v, const T& ai_bi_root, const Policy& pol)
       {
         BOOST_MATH_STD_USING // ADL of std names, needed for log, sqrt.
 
@@ -132,9 +143,9 @@
 
         // Select the maximum allowed iterations based on the number
         // of decimal digits in the numeric type T, being at least 12.
-        const auto iterations_allowed = static_cast<std::uintmax_t>((std::max)(12, my_digits10 * 2));
+        const auto iterations_allowed = static_cast<boost::math::uintmax_t>(BOOST_MATH_GPU_SAFE_MAX(12, my_digits10 * 2));
 
-        std::uintmax_t iterations_used = iterations_allowed;
+        boost::math::uintmax_t iterations_used = iterations_allowed;
 
         // Calculate the root of z as a function of zeta.
         const T z = boost::math::tools::newton_raphson_iterate(
@@ -142,7 +153,7 @@
           z_estimate,
           range_zmin,
           range_zmax,
-          (std::min)(boost::math::tools::digits<T>(), boost::math::tools::digits<float>()),
+          BOOST_MATH_GPU_SAFE_MIN(boost::math::tools::digits<T>(), boost::math::tools::digits<float>()),
           iterations_used);
 
         static_cast<void>(iterations_used);
@@ -168,7 +179,7 @@
       namespace cyl_bessel_j_zero_detail
       {
         template<class T, class Policy>
-        T equation_nist_10_21_40_a(const T& v, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T equation_nist_10_21_40_a(const T& v, const Policy& pol)
         {
           const T v_pow_third(boost::math::cbrt(v, pol));
           const T v_pow_minus_two_thirds(T(1) / (v_pow_third * v_pow_third));
@@ -185,13 +196,13 @@
         class function_object_jv
         {
         public:
-          function_object_jv(const T& v,
+          BOOST_MATH_GPU_ENABLED function_object_jv(const T& v,
                              const Policy& pol) : my_v(v),
                                                   my_pol(pol) { }
 
-          function_object_jv(const function_object_jv&) = default;
+          BOOST_MATH_GPU_ENABLED function_object_jv(const function_object_jv&) = default;
 
-          T operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED T operator()(const T& x) const
           {
             return boost::math::cyl_bessel_j(my_v, x, my_pol);
           }
@@ -206,15 +217,16 @@
         class function_object_jv_and_jv_prime
         {
         public:
-          function_object_jv_and_jv_prime(const T& v,
-                                          const bool order_is_zero,
-                                          const Policy& pol) : my_v(v),
+          BOOST_MATH_GPU_ENABLED function_object_jv_and_jv_prime(
+                                                         const T& v,
+                                                         const bool order_is_zero,
+                                                         const Policy& pol) : my_v(v),
                                                                my_order_is_zero(order_is_zero),
                                                                my_pol(pol) { }
 
           function_object_jv_and_jv_prime(const function_object_jv_and_jv_prime&) = default;
 
-          boost::math::tuple<T, T> operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(const T& x) const
           {
             // Obtain Jv(x) and Jv'(x).
             // Chris's original code called the Bessel function implementation layer direct, 
@@ -246,10 +258,10 @@
           const function_object_jv_and_jv_prime& operator=(const function_object_jv_and_jv_prime&) = delete;
         };
 
-        template<class T> bool my_bisection_unreachable_tolerance(const T&, const T&) { return false; }
+        template<class T> BOOST_MATH_GPU_ENABLED bool my_bisection_unreachable_tolerance(const T&, const T&) { return false; }
 
         template<class T, class Policy>
-        T initial_guess(const T& v, const int m, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T initial_guess(const T& v, const int m, const Policy& pol)
         {
           BOOST_MATH_STD_USING // ADL of std names, needed for floor.
 
@@ -325,7 +337,7 @@
             }
 
             // Perform several steps of bisection iteration to refine the guess.
-            std::uintmax_t number_of_iterations(12U);
+            boost::math::uintmax_t number_of_iterations(12U);
 
             // Do the bisection iteration.
             const boost::math::tuple<T, T> guess_pair =
@@ -390,7 +402,7 @@
       namespace cyl_neumann_zero_detail
       {
         template<class T, class Policy>
-        T equation_nist_10_21_40_b(const T& v, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T equation_nist_10_21_40_b(const T& v, const Policy& pol)
         {
           const T v_pow_third(boost::math::cbrt(v, pol));
           const T v_pow_minus_two_thirds(T(1) / (v_pow_third * v_pow_third));
@@ -407,13 +419,13 @@
         class function_object_yv
         {
         public:
-          function_object_yv(const T& v,
-                             const Policy& pol) : my_v(v),
-                                                  my_pol(pol) { }
+          BOOST_MATH_GPU_ENABLED function_object_yv(const T& v,
+                                                    const Policy& pol) : my_v(v),
+                                                                         my_pol(pol) { }
 
-          function_object_yv(const function_object_yv&) = default;
+          BOOST_MATH_GPU_ENABLED function_object_yv(const function_object_yv&) = default;
 
-          T operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED T operator()(const T& x) const
           {
             return boost::math::cyl_neumann(my_v, x, my_pol);
           }
@@ -428,13 +440,13 @@
         class function_object_yv_and_yv_prime
         {
         public:
-          function_object_yv_and_yv_prime(const T& v,
-                                          const Policy& pol) : my_v(v),
-                                                               my_pol(pol) { }
+          BOOST_MATH_GPU_ENABLED function_object_yv_and_yv_prime(const T& v,
+                                                                 const Policy& pol) : my_v(v),
+                                                                                      my_pol(pol) { }
 
-          function_object_yv_and_yv_prime(const function_object_yv_and_yv_prime&) = default;
+          BOOST_MATH_GPU_ENABLED function_object_yv_and_yv_prime(const function_object_yv_and_yv_prime&) = default;
 
-          boost::math::tuple<T, T> operator()(const T& x) const
+          BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(const T& x) const
           {
             const T half_epsilon(boost::math::tools::epsilon<T>() / 2U);
 
@@ -469,10 +481,10 @@
           const function_object_yv_and_yv_prime& operator=(const function_object_yv_and_yv_prime&) = delete;
         };
 
-        template<class T> bool my_bisection_unreachable_tolerance(const T&, const T&) { return false; }
+        template<class T> BOOST_MATH_GPU_ENABLED bool my_bisection_unreachable_tolerance(const T&, const T&) { return false; }
 
         template<class T, class Policy>
-        T initial_guess(const T& v, const int m, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED T initial_guess(const T& v, const int m, const Policy& pol)
         {
           BOOST_MATH_STD_USING // ADL of std names, needed for floor.
 
@@ -560,7 +572,7 @@
             }
 
             // Perform several steps of bisection iteration to refine the guess.
-            std::uintmax_t number_of_iterations(12U);
+            boost::math::uintmax_t number_of_iterations(12U);
 
             // Do the bisection iteration.
             const boost::math::tuple<T, T> guess_pair =
@@ -624,4 +636,8 @@
     } // namespace bessel_zero
   } } } // namespace boost::math::detail
 
+  #ifdef BOOST_MATH_ENABLE_CUDA
+  #  pragma nv_diag_default 20012
+  #endif
+
 #endif // BOOST_MATH_BESSEL_JY_ZERO_2013_01_18_HPP_
diff --git a/include/boost/math/special_functions/detail/bessel_k0.hpp b/include/boost/math/special_functions/detail/bessel_k0.hpp
index f29ffa75c4..bab202b6cd 100644
--- a/include/boost/math/special_functions/detail/bessel_k0.hpp
+++ b/include/boost/math/special_functions/detail/bessel_k0.hpp
@@ -13,10 +13,14 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
-#include <boost/math/policies/error_handling.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -44,35 +48,37 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T>
-T bessel_k0(const T& x);
+BOOST_MATH_GPU_ENABLED T bessel_k0(const T& x);
 
 template <class T, class tag>
 struct bessel_k0_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init(tag());
       }
-      static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
       {
          bessel_k0(T(0.5));
          bessel_k0(T(1.5));
       }
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          bessel_k0(T(0.5));
          bessel_k0(T(1.5));
       }
       template <class U>
-      static void do_init(const U&){}
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED static void do_init(const U&){}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -81,14 +87,14 @@ const typename bessel_k0_initializer<T, tag>::init bessel_k0_initializer<T, tag>
 
 
 template <typename T, int N>
-T bessel_k0_imp(const T&, const std::integral_constant<int, N>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T&, const boost::math::integral_constant<int, N>&)
 {
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-T bessel_k0_imp(const T& x, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T& x, const boost::math::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING
    if(x <= 1)
@@ -97,14 +103,14 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 24>&)
       // Expected Error Term : -2.358e-09
       // Maximum Relative Change in Control Points : 9.552e-02
       // Max Error found at float precision = Poly : 4.448220e-08
-      static const T Y = 1.137250900268554688f;
-      static const T P[] = 
+      BOOST_MATH_STATIC const T Y = 1.137250900268554688f;
+      BOOST_MATH_STATIC const T P[] = 
       {
          -1.372508979104259711e-01f,
          2.622545986273687617e-01f,
          5.047103728247919836e-03f
       };
-      static const T Q[] = 
+      BOOST_MATH_STATIC const T Q[] = 
       {
          1.000000000000000000e+00f,
          -8.928694018000029415e-02f,
@@ -117,7 +123,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 24>&)
       // Expected Error Term : -1.343e-09
       // Maximum Relative Change in Control Points : 2.405e-02
       // Max Error found at float precision = Poly : 1.354814e-07
-      static const T P2[] = {
+      BOOST_MATH_STATIC const T P2[] = {
          1.159315158e-01f,
          2.789828686e-01f,
          2.524902861e-02f,
@@ -133,14 +139,14 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 24>&)
       // Maximum Relative Change in Control Points : 9.064e-02
       // Max Error found at float precision = Poly : 5.065020e-08
 
-      static const T P[] =
+      BOOST_MATH_STATIC const T P[] =
       {
          2.533141220e-01f,
          5.221502603e-01f,
          6.380180669e-02f,
          -5.934976547e-02f
       };
-      static const T Q[] =
+      BOOST_MATH_STATIC const T Q[] =
       {
          1.000000000e+00f,
          2.679722431e+00f,
@@ -158,7 +164,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 24>&)
 }
 
 template <typename T>
-T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T& x, const boost::math::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING
    if(x <= 1)
@@ -167,8 +173,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
       // Expected Error Term : -6.077e-17
       // Maximum Relative Change in Control Points : 7.797e-02
       // Max Error found at double precision = Poly : 1.003156e-16
-      static const T Y = 1.137250900268554688;
-      static const T P[] =
+      BOOST_MATH_STATIC const T Y = 1.137250900268554688;
+      BOOST_MATH_STATIC const T P[] =
       {
          -1.372509002685546267e-01,
          2.574916117833312855e-01,
@@ -176,7 +182,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
          5.445476986653926759e-04,
          7.125159422136622118e-06
       };
-      static const T Q[] =
+      BOOST_MATH_STATIC const T Q[] =
       {
          1.000000000000000000e+00,
          -5.458333438017788530e-02,
@@ -191,7 +197,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
       // Expected Error Term : 3.392e-18
       // Maximum Relative Change in Control Points : 2.041e-02
       // Max Error found at double precision = Poly : 2.513112e-16
-      static const T P2[] =
+      BOOST_MATH_STATIC const T P2[] =
       {
          1.159315156584124484e-01,
          2.789828789146031732e-01,
@@ -212,8 +218,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
       // Maximum Relative Change in Control Points : 2.757e-01
       // Max Error found at double precision = Poly : 1.001560e-16
 
-      static const T Y = 1;
-      static const T P[] =
+      BOOST_MATH_STATIC const T Y = 1;
+      BOOST_MATH_STATIC const T P[] =
       {
          2.533141373155002416e-01,
          3.628342133984595192e+00,
@@ -225,7 +231,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
          -1.414237994269995877e+00,
          -9.369168119754924625e-02
       };
-      static const T Q[] =
+      BOOST_MATH_STATIC const T Q[] =
       {
          1.000000000000000000e+00,
          1.494194694879908328e+01,
@@ -248,7 +254,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 53>&)
 }
 
 template <typename T>
-T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T& x, const boost::math::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING
       if(x <= 1)
@@ -257,8 +263,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
          // Expected Error Term : 2.180e-22
          // Maximum Relative Change in Control Points : 2.943e-01
          // Max Error found at float80 precision = Poly : 3.923207e-20
-         static const T Y = 1.137250900268554687500e+00;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.137250900268554687500e+00;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.372509002685546875002e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.566481981037407600436e-01),
@@ -267,7 +273,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.213747930378196492543e-05),
             BOOST_MATH_BIG_CONSTANT(T, 64, 9.423709328020389560844e-08)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.843828412587773008342e-02),
@@ -284,7 +290,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
          // Expected Error Term : -2.434e-21
          // Maximum Relative Change in Control Points : 2.459e-02
          // Max Error found at float80 precision = Poly : 1.482487e-19
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.159315156584124488110e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.764832791416047889734e-01),
@@ -292,7 +298,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.660777862036966089410e-04),
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.094942446930673386849e-06)
          };
-         static const T Q2[] =
+         BOOST_MATH_STATIC const T Q2[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, -2.156100313881251616320e-02),
@@ -308,8 +314,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
          // Expected Error Term : 2.236e-21
          // Maximum Relative Change in Control Points : 3.021e-01
          //Max Error found at float80 precision = Poly : 8.727378e-20
-         static const T Y = 1;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.533141373155002512056e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, 5.417942070721928652715e+00),
@@ -323,7 +329,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.059789241612946683713e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.612783121537333908889e-01)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.200669254769325861404e+01),
@@ -348,7 +354,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 64>&)
 }
 
 template <typename T>
-T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T& x, const boost::math::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING
       if(x <= 1)
@@ -357,8 +363,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
          // Expected Error Term : 5.682e-37
          // Maximum Relative Change in Control Points : 6.094e-04
          // Max Error found at float128 precision = Poly : 5.338213e-35
-         static const T Y = 1.137250900268554687500000000000000000e+00f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.137250900268554687500000000000000000e+00f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, -1.372509002685546875000000000000000006e-01),
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.556212905071072782462974351698081303e-01),
@@ -369,7 +375,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.752489221949580551692915881999762125e-09),
             BOOST_MATH_BIG_CONSTANT(T, 113, 5.243010555737173524710512824955368526e-12)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, -4.095631064064621099785696980653193721e-02),
@@ -387,7 +393,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
          // Expected Error Term : 5.105e-38
          // Maximum Relative Change in Control Points : 9.734e-03
          // Max Error found at float128 precision = Poly : 1.688806e-34
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.159315156584124488107200313757741370e-01),
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.789828789146031122026800078439435369e-01),
@@ -413,8 +419,8 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
          // Expected Error Term : 4.917e-40
          // Maximum Relative Change in Control Points : 3.385e-01
          // Max Error found at float128 precision = Poly : 1.567573e-34
-         static const T Y = 1;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.533141373155002512078826424055226265e-01),
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.001949740768235770078339977110749204e+01),
@@ -439,7 +445,7 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
             BOOST_MATH_BIG_CONSTANT(T, 113, -4.201632288615609937883545928660649813e+03),
             BOOST_MATH_BIG_CONSTANT(T, 113, -3.690820607338480548346746717311811406e+01)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, 7.964877874035741452203497983642653107e+01),
@@ -475,33 +481,33 @@ T bessel_k0_imp(const T& x, const std::integral_constant<int, 113>&)
 }
 
 template <typename T>
-T bessel_k0_imp(const T& x, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED T bessel_k0_imp(const T& x, const boost::math::integral_constant<int, 0>&)
 {
    if(boost::math::tools::digits<T>() <= 24)
-      return bessel_k0_imp(x, std::integral_constant<int, 24>());
+      return bessel_k0_imp(x, boost::math::integral_constant<int, 24>());
    else if(boost::math::tools::digits<T>() <= 53)
-      return bessel_k0_imp(x, std::integral_constant<int, 53>());
+      return bessel_k0_imp(x, boost::math::integral_constant<int, 53>());
    else if(boost::math::tools::digits<T>() <= 64)
-      return bessel_k0_imp(x, std::integral_constant<int, 64>());
+      return bessel_k0_imp(x, boost::math::integral_constant<int, 64>());
    else if(boost::math::tools::digits<T>() <= 113)
-      return bessel_k0_imp(x, std::integral_constant<int, 113>());
+      return bessel_k0_imp(x, boost::math::integral_constant<int, 113>());
    BOOST_MATH_ASSERT(0);
    return 0;
 }
 
 template <typename T>
-inline T bessel_k0(const T& x)
+BOOST_MATH_GPU_ENABLED inline T bessel_k0(const T& x)
 {
-   typedef std::integral_constant<int,
-      ((std::numeric_limits<T>::digits == 0) || (std::numeric_limits<T>::radix != 2)) ?
+   typedef boost::math::integral_constant<int,
+      ((boost::math::numeric_limits<T>::digits == 0) || (boost::math::numeric_limits<T>::radix != 2)) ?
       0 :
-      std::numeric_limits<T>::digits <= 24 ?
+      boost::math::numeric_limits<T>::digits <= 24 ?
       24 :
-      std::numeric_limits<T>::digits <= 53 ?
+      boost::math::numeric_limits<T>::digits <= 53 ?
       53 :
-      std::numeric_limits<T>::digits <= 64 ?
+      boost::math::numeric_limits<T>::digits <= 64 ?
       64 :
-      std::numeric_limits<T>::digits <= 113 ?
+      boost::math::numeric_limits<T>::digits <= 113 ?
       113 : -1
    > tag_type;
 
diff --git a/include/boost/math/special_functions/detail/bessel_k1.hpp b/include/boost/math/special_functions/detail/bessel_k1.hpp
index bd37f90215..49846dc8c5 100644
--- a/include/boost/math/special_functions/detail/bessel_k1.hpp
+++ b/include/boost/math/special_functions/detail/bessel_k1.hpp
@@ -13,6 +13,10 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
 #include <boost/math/policies/error_handling.hpp>
@@ -44,36 +48,38 @@
 namespace boost { namespace math { namespace detail{
 
    template <typename T>
-   T bessel_k1(const T&);
+   BOOST_MATH_GPU_ENABLED T bessel_k1(const T&);
 
    template <class T, class tag>
    struct bessel_k1_initializer
    {
       struct init
       {
-         init()
+         BOOST_MATH_GPU_ENABLED init()
          {
             do_init(tag());
          }
-         static void do_init(const std::integral_constant<int, 113>&)
+         BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
          {
             bessel_k1(T(0.5));
             bessel_k1(T(2));
             bessel_k1(T(6));
          }
-         static void do_init(const std::integral_constant<int, 64>&)
+         BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
          {
             bessel_k1(T(0.5));
             bessel_k1(T(6));
          }
          template <class U>
-         static void do_init(const U&) {}
-         void force_instantiate()const {}
+         BOOST_MATH_GPU_ENABLED static void do_init(const U&) {}
+         BOOST_MATH_GPU_ENABLED void force_instantiate()const {}
       };
-      static const init initializer;
-      static void force_instantiate()
+      BOOST_MATH_STATIC const init initializer;
+      BOOST_MATH_GPU_ENABLED static void force_instantiate()
       {
+         #ifndef BOOST_MATH_HAS_GPU_SUPPORT
          initializer.force_instantiate();
+         #endif
       }
    };
 
@@ -82,14 +88,14 @@ namespace boost { namespace math { namespace detail{
 
 
    template <typename T, int N>
-   inline T bessel_k1_imp(const T&, const std::integral_constant<int, N>&)
+   inline BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T&, const boost::math::integral_constant<int, N>&)
    {
       BOOST_MATH_ASSERT(0);
       return 0;
    }
 
    template <typename T>
-   T bessel_k1_imp(const T& x, const std::integral_constant<int, 24>&)
+   BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T& x, const boost::math::integral_constant<int, 24>&)
    {
       BOOST_MATH_STD_USING
       if(x <= 1)
@@ -98,14 +104,14 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -3.053e-12
          // Maximum Relative Change in Control Points : 4.927e-02
          // Max Error found at float precision = Poly : 7.918347e-10
-         static const T Y = 8.695471287e-02f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 8.695471287e-02f;
+         BOOST_MATH_STATIC const T P[] =
          {
             -3.621379531e-03f,
             7.131781976e-03f,
             -1.535278300e-05f
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             1.000000000e+00f,
             -5.173102701e-02f,
@@ -118,7 +124,7 @@ namespace boost { namespace math { namespace detail{
          // Maximum Deviation Found:                     3.556e-08
          // Expected Error Term : -3.541e-08
          // Maximum Relative Change in Control Points : 8.203e-02
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             -3.079657469e-01f,
             -8.537108913e-02f,
@@ -134,15 +140,15 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -3.227e-08
          // Maximum Relative Change in Control Points : 9.917e-02
          // Max Error found at float precision = Poly : 6.084411e-08
-         static const T Y = 1.450342178f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.450342178f;
+         BOOST_MATH_STATIC const T P[] =
          {
             -1.970280088e-01f,
             2.188747807e-02f,
             7.270394756e-01f,
             2.490678196e-01f
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             1.000000000e+00f,
             2.274292882e+00f,
@@ -160,7 +166,7 @@ namespace boost { namespace math { namespace detail{
    }
 
    template <typename T>
-   T bessel_k1_imp(const T& x, const std::integral_constant<int, 53>&)
+   BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T& x, const boost::math::integral_constant<int, 53>&)
    {
       BOOST_MATH_STD_USING
       if(x <= 1)
@@ -169,15 +175,15 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : 1.921e-17
          // Maximum Relative Change in Control Points : 5.287e-03
          // Max Error found at double precision = Poly : 2.004747e-17
-         static const T Y = 8.69547128677368164e-02f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 8.69547128677368164e-02f;
+         BOOST_MATH_STATIC const T P[] =
          {
             -3.62137953440350228e-03,
             7.11842087490330300e-03,
             1.00302560256614306e-05,
             1.77231085381040811e-06
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             1.00000000000000000e+00,
             -4.80414794429043831e-02,
@@ -193,14 +199,14 @@ namespace boost { namespace math { namespace detail{
          // Maximum Relative Change in Control Points : 3.103e-04
          // Max Error found at double precision = Poly : 1.246698e-16
 
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             -3.07965757829206184e-01,
             -7.80929703673074907e-02,
             -2.70619343754051620e-03,
             -2.49549522229072008e-05
          };
-         static const T Q2[] = 
+         BOOST_MATH_STATIC const T Q2[] = 
          {
             1.00000000000000000e+00,
             -2.36316836412163098e-02,
@@ -217,8 +223,8 @@ namespace boost { namespace math { namespace detail{
          // Maximum Relative Change in Control Points : 2.786e-01
          // Max Error found at double precision = Poly : 1.258798e-16
 
-         static const T Y = 1.45034217834472656f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.45034217834472656f;
+         BOOST_MATH_STATIC const T P[] =
          {
             -1.97028041029226295e-01,
             -2.32408961548087617e+00,
@@ -230,7 +236,7 @@ namespace boost { namespace math { namespace detail{
             6.62582288933739787e+00,
             3.08851840645286691e-01
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             1.00000000000000000e+00,
             1.41811409298826118e+01,
@@ -253,7 +259,7 @@ namespace boost { namespace math { namespace detail{
    }
 
    template <typename T>
-   T bessel_k1_imp(const T& x, const std::integral_constant<int, 64>&)
+   BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T& x, const boost::math::integral_constant<int, 64>&)
    {
       BOOST_MATH_STD_USING
       if(x <= 1)
@@ -262,8 +268,8 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -5.548e-23
          // Maximum Relative Change in Control Points : 2.002e-03
          // Max Error found at float80 precision = Poly : 9.352785e-22
-         static const T Y = 8.695471286773681640625e-02f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 8.695471286773681640625e-02f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, -3.621379534403483072861e-03),
             BOOST_MATH_BIG_CONSTANT(T, 64, 7.102135866103952705932e-03),
@@ -271,7 +277,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.537484002571894870830e-06),
             BOOST_MATH_BIG_CONSTANT(T, 64, 6.603228256820000135990e-09)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.354457194045068370363e-02),
@@ -287,7 +293,7 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : 1.995e-23
          // Maximum Relative Change in Control Points : 8.174e-04
          // Max Error found at float80 precision = Poly : 4.137325e-20
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, -3.079657578292062244054e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -7.963049154965966503231e-02),
@@ -295,7 +301,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.023052834702215699504e-05),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.719459155018493821839e-07)
          };
-         static const T Q2[] = 
+         BOOST_MATH_STATIC const T Q2[] = 
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.863917670410152669768e-02),
@@ -312,8 +318,8 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -3.302e-21
          // Maximum Relative Change in Control Points : 3.432e-01
          // Max Error found at float80 precision = Poly : 1.083755e-19
-         static const T Y = 1.450342178344726562500e+00f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.450342178344726562500e+00f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, -1.970280410292263112917e-01),
             BOOST_MATH_BIG_CONSTANT(T, 64, -4.058564803062959169322e+00),
@@ -328,7 +334,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 64, 4.319614662598089438939e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, 3.710715864316521856193e-02)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 64, 1.000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 64, 2.298433045824439052398e+01),
@@ -353,7 +359,7 @@ namespace boost { namespace math { namespace detail{
    }
 
    template <typename T>
-   T bessel_k1_imp(const T& x, const std::integral_constant<int, 113>&)
+   BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T& x, const boost::math::integral_constant<int, 113>&)
    {
       BOOST_MATH_STD_USING
       if(x <= 1)
@@ -362,8 +368,8 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -7.119e-35
          // Maximum Relative Change in Control Points : 1.207e-03
          // Max Error found at float128 precision = Poly : 7.143688e-35
-         static const T Y = 8.695471286773681640625000000000000000e-02f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 8.695471286773681640625000000000000000e-02f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, -3.621379534403483072916666666666595475e-03),
             BOOST_MATH_BIG_CONSTANT(T, 113, 7.074117676930975433219826471336547627e-03),
@@ -373,7 +379,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.347140307321161346703214099534250263e-10),
             BOOST_MATH_BIG_CONSTANT(T, 113, 5.569608494081482873946791086435679661e-13)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, -3.580768910152105375615558920428350204e-02),
@@ -391,7 +397,7 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : 4.473e-37
          // Maximum Relative Change in Control Points : 8.550e-04
          // Max Error found at float128 precision = Poly : 8.167701e-35
-         static const T P2[] =
+         BOOST_MATH_STATIC const T P2[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, -3.079657578292062244053600156878870690e-01),
             BOOST_MATH_BIG_CONSTANT(T, 113, -8.133183745732467770755578848987414875e-02),
@@ -401,7 +407,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 113, -1.632502325880313239698965376754406011e-09),
             BOOST_MATH_BIG_CONSTANT(T, 113, -2.311973065898784812266544485665624227e-12)
          };
-         static const T Q2[] = 
+         BOOST_MATH_STATIC const T Q2[] = 
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, -1.311471216733781016657962995723287450e-02),
@@ -418,8 +424,8 @@ namespace boost { namespace math { namespace detail{
       {
          // Max error in interpolated form: 5.307e-37
          // Max Error found at float128 precision = Poly: 7.087862e-35
-         static const T Y = 1.5023040771484375f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.5023040771484375f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, -2.489899398329369710528254347931380044e-01),
             BOOST_MATH_BIG_CONSTANT(T, 113, -6.819080211203854781858815596508456873e+00),
@@ -438,7 +444,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.039705646510167437971862966128055524e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.008418100718254816100425022904039530e-02)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.927456835239137986889227412815459529e+01),
@@ -465,8 +471,8 @@ namespace boost { namespace math { namespace detail{
          // Expected Error Term : -6.565e-40
          // Maximum Relative Change in Control Points : 1.880e-01
          // Max Error found at float128 precision = Poly : 2.943572e-35
-         static const T Y = 1.308816909790039062500000000000000000f;
-         static const T P[] =
+         BOOST_MATH_STATIC const T Y = 1.308816909790039062500000000000000000f;
+         BOOST_MATH_STATIC const T P[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, -5.550277247453881129211735759447737350e-02),
             BOOST_MATH_BIG_CONSTANT(T, 113, -3.485883080219574328217554864956175929e+00),
@@ -486,7 +492,7 @@ namespace boost { namespace math { namespace detail{
             BOOST_MATH_BIG_CONSTANT(T, 113, 8.981057433937398731355768088809437625e+05),
             BOOST_MATH_BIG_CONSTANT(T, 113, 2.519440069856232098711793483639792952e+04)
          };
-         static const T Q[] =
+         BOOST_MATH_STATIC const T Q[] =
          {
             BOOST_MATH_BIG_CONSTANT(T, 113, 1.000000000000000000000000000000000000e+00),
             BOOST_MATH_BIG_CONSTANT(T, 113, 7.127348248283623146544565916604103560e+01),
@@ -517,33 +523,33 @@ namespace boost { namespace math { namespace detail{
     }
 
     template <typename T>
-    T bessel_k1_imp(const T& x, const std::integral_constant<int, 0>&)
+    BOOST_MATH_GPU_ENABLED T bessel_k1_imp(const T& x, const boost::math::integral_constant<int, 0>&)
     {
        if(boost::math::tools::digits<T>() <= 24)
-          return bessel_k1_imp(x, std::integral_constant<int, 24>());
+          return bessel_k1_imp(x, boost::math::integral_constant<int, 24>());
        else if(boost::math::tools::digits<T>() <= 53)
-          return bessel_k1_imp(x, std::integral_constant<int, 53>());
+          return bessel_k1_imp(x, boost::math::integral_constant<int, 53>());
        else if(boost::math::tools::digits<T>() <= 64)
-          return bessel_k1_imp(x, std::integral_constant<int, 64>());
+          return bessel_k1_imp(x, boost::math::integral_constant<int, 64>());
        else if(boost::math::tools::digits<T>() <= 113)
-          return bessel_k1_imp(x, std::integral_constant<int, 113>());
+          return bessel_k1_imp(x, boost::math::integral_constant<int, 113>());
        BOOST_MATH_ASSERT(0);
        return 0;
     }
 
-    template <typename T>
-   inline T bessel_k1(const T& x)
+   template <typename T>
+   inline BOOST_MATH_GPU_ENABLED T bessel_k1(const T& x)
    {
-      typedef std::integral_constant<int,
-         ((std::numeric_limits<T>::digits == 0) || (std::numeric_limits<T>::radix != 2)) ?
+      typedef boost::math::integral_constant<int,
+         ((boost::math::numeric_limits<T>::digits == 0) || (boost::math::numeric_limits<T>::radix != 2)) ?
          0 :
-         std::numeric_limits<T>::digits <= 24 ?
+         boost::math::numeric_limits<T>::digits <= 24 ?
          24 :
-         std::numeric_limits<T>::digits <= 53 ?
+         boost::math::numeric_limits<T>::digits <= 53 ?
          53 :
-         std::numeric_limits<T>::digits <= 64 ?
+         boost::math::numeric_limits<T>::digits <= 64 ?
          64 :
-         std::numeric_limits<T>::digits <= 113 ?
+         boost::math::numeric_limits<T>::digits <= 113 ?
          113 : -1
       > tag_type;
 
diff --git a/include/boost/math/special_functions/detail/bessel_kn.hpp b/include/boost/math/special_functions/detail/bessel_kn.hpp
index d0ddcd0db4..41becc8aa9 100644
--- a/include/boost/math/special_functions/detail/bessel_kn.hpp
+++ b/include/boost/math/special_functions/detail/bessel_kn.hpp
@@ -10,8 +10,12 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/detail/bessel_k0.hpp>
 #include <boost/math/special_functions/detail/bessel_k1.hpp>
+#include <boost/math/special_functions/sign.hpp>
 #include <boost/math/policies/error_handling.hpp>
 
 // Modified Bessel function of the second kind of integer order
@@ -20,14 +24,14 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T bessel_kn(int n, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T bessel_kn(int n, T x, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     T value, current, prev;
 
     using namespace boost::math::tools;
 
-    static const char* function = "boost::math::bessel_kn<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::bessel_kn<%1%>(%1%,%1%)";
 
     if (x < 0)
     {
diff --git a/include/boost/math/special_functions/detail/bessel_y0.hpp b/include/boost/math/special_functions/detail/bessel_y0.hpp
index 1679820d19..f1aea6acbd 100644
--- a/include/boost/math/special_functions/detail/bessel_y0.hpp
+++ b/include/boost/math/special_functions/detail/bessel_y0.hpp
@@ -12,6 +12,7 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/detail/bessel_j0.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/rational.hpp>
@@ -36,12 +37,12 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T bessel_y0(T x, const Policy&);
+BOOST_MATH_GPU_ENABLED T bessel_y0(T x, const Policy&);
 
 template <typename T, typename Policy>
-T bessel_y0(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED T bessel_y0(T x, const Policy&)
 {
-    static const T P1[] = {
+    BOOST_MATH_STATIC const T P1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0723538782003176831e+11)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.3716255451260504098e+09)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.0422274357376619816e+08)),
@@ -49,7 +50,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0102532948020907590e+04)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.8402381979244993524e+01)),
     };
-    static const T Q1[] = {
+    BOOST_MATH_STATIC const T Q1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.8873865738997033405e+11)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.1617187777290363573e+09)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.5662956624278251596e+07)),
@@ -57,7 +58,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.6475986689240190091e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T P2[] = {
+    BOOST_MATH_STATIC const T P2[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -2.2213976967566192242e+13)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -5.5107435206722644429e+11)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.3600098638603061642e+10)),
@@ -66,7 +67,7 @@ T bessel_y0(T x, const Policy&)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.4566865832663635920e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.7427031242901594547e+01)),
     };
-    static const T Q2[] = {
+    BOOST_MATH_STATIC const T Q2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.3386146580707264428e+14)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.4266824419412347550e+12)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.4015103849971240096e+10)),
@@ -75,7 +76,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.3030857612070288823e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T P3[] = {
+    BOOST_MATH_STATIC const T P3[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.0728726905150210443e+15)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.7016641869173237784e+14)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2829912364088687306e+11)),
@@ -85,7 +86,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1363534169313901632e+04)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.7439661319197499338e+01)),
     };
-    static const T Q3[] = {
+    BOOST_MATH_STATIC const T Q3[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.4563724628846457519e+17)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.9272425569640309819e+15)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2598377924042897629e+13)),
@@ -95,7 +96,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.7903362168128450017e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T PC[] = {
+    BOOST_MATH_STATIC const T PC[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2779090197304684302e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1345386639580765797e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1170523380864944322e+04)),
@@ -103,7 +104,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.5376201909008354296e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.8961548424210455236e-01)),
     };
-    static const T QC[] = {
+    BOOST_MATH_STATIC const T QC[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2779090197304684318e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1370412495510416640e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1215350561880115730e+04)),
@@ -111,7 +112,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.5711159858080893649e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T PS[] = {
+    BOOST_MATH_STATIC const T PS[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.9226600200800094098e+01)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.8591953644342993800e+02)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.1183429920482737611e+02)),
@@ -119,7 +120,7 @@ T bessel_y0(T x, const Policy&)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2441026745835638459e+00)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -8.8033303048680751817e-03)),
     };
-    static const T QS[] = {
+    BOOST_MATH_STATIC const T QS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.7105024128512061905e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.1951131543434613647e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.2642780169211018836e+03)),
@@ -127,7 +128,7 @@ T bessel_y0(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 9.0593769594993125859e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.9357696627916752158e-01)),
+    BOOST_MATH_STATIC const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.9357696627916752158e-01)),
                    x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.9576784193148578684e+00)),
                    x3  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.0860510603017726976e+00)),
                    x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.280e+02)),
diff --git a/include/boost/math/special_functions/detail/bessel_y1.hpp b/include/boost/math/special_functions/detail/bessel_y1.hpp
index 3ac696bb5c..0f0dbdf3bb 100644
--- a/include/boost/math/special_functions/detail/bessel_y1.hpp
+++ b/include/boost/math/special_functions/detail/bessel_y1.hpp
@@ -12,6 +12,7 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/detail/bessel_j1.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/tools/rational.hpp>
@@ -36,12 +37,12 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T bessel_y1(T x, const Policy&);
+BOOST_MATH_GPU_ENABLED T bessel_y1(T x, const Policy&);
 
 template <typename T, typename Policy>
-T bessel_y1(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED T bessel_y1(T x, const Policy&)
 {
-    static const T P1[] = {
+    BOOST_MATH_STATIC const T P1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.0535726612579544093e+13)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.4708611716525426053e+12)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.7595974497819597599e+11)),
@@ -50,7 +51,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.2157953222280260820e+05)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -3.1714424660046133456e+02)),
     };
-    static const T Q1[] = {
+    BOOST_MATH_STATIC const T Q1[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.0737873921079286084e+14)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 4.1272286200406461981e+12)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.7800352738690585613e+10)),
@@ -59,7 +60,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.2079908168393867438e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T P2[] = {
+    BOOST_MATH_STATIC const T P2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.1514276357909013326e+19)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -5.6808094574724204577e+18)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -2.3638408497043134724e+16)),
@@ -70,7 +71,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.9153806858264202986e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.2337180442012953128e+03)),
     };
-    static const T Q2[] = {
+    BOOST_MATH_STATIC const T Q2[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.3321844313316185697e+20)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.6968198822857178911e+18)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.0837179548112881950e+16)),
@@ -81,7 +82,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.2855164849321609336e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T PC[] = {
+    BOOST_MATH_STATIC const T PC[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -4.4357578167941278571e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -9.9422465050776411957e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -6.6033732483649391093e+06)),
@@ -90,7 +91,7 @@ T bessel_y1(T x, const Policy&)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.6116166443246101165e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0)),
     };
-    static const T QC[] = {
+    BOOST_MATH_STATIC const T QC[] = {
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -4.4357578167941278568e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -9.9341243899345856590e+06)),
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -6.5853394797230870728e+06)),
@@ -99,7 +100,7 @@ T bessel_y1(T x, const Policy&)
         static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, -1.4550094401904961825e+03)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T PS[] = {
+    BOOST_MATH_STATIC const T PS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.3220913409857223519e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.5145160675335701966e+04)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 6.6178836581270835179e+04)),
@@ -108,7 +109,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 3.5265133846636032186e+01)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 0.0)),
     };
-    static const T QS[] = {
+    BOOST_MATH_STATIC const T QS[] = {
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 7.0871281941028743574e+05)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.8194580422439972989e+06)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.4194606696037208929e+06)),
@@ -117,7 +118,7 @@ T bessel_y1(T x, const Policy&)
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 8.6383677696049909675e+02)),
          static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.0)),
     };
-    static const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1971413260310170351e+00)),
+    BOOST_MATH_STATIC const T x1  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 2.1971413260310170351e+00)),
                    x2  =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.4296810407941351328e+00)),
                    x11 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 5.620e+02)),
                    x12 =  static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 64, 1.8288260310170351490e-03)),
diff --git a/include/boost/math/special_functions/detail/bessel_yn.hpp b/include/boost/math/special_functions/detail/bessel_yn.hpp
index 73dee0bbb8..a45d1761cd 100644
--- a/include/boost/math/special_functions/detail/bessel_yn.hpp
+++ b/include/boost/math/special_functions/detail/bessel_yn.hpp
@@ -10,9 +10,11 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/detail/bessel_y0.hpp>
 #include <boost/math/special_functions/detail/bessel_y1.hpp>
 #include <boost/math/special_functions/detail/bessel_jy_series.hpp>
+#include <boost/math/special_functions/sign.hpp>
 #include <boost/math/policies/error_handling.hpp>
 
 // Bessel function of the second kind of integer order
@@ -21,14 +23,14 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T bessel_yn(int n, T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T bessel_yn(int n, T x, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     T value, factor, current, prev;
 
     using namespace boost::math::tools;
 
-    static const char* function = "boost::math::bessel_yn<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::bessel_yn<%1%>(%1%,%1%)";
 
     if ((x == 0) && (n == 0))
     {
diff --git a/include/boost/math/special_functions/detail/iconv.hpp b/include/boost/math/special_functions/detail/iconv.hpp
index 90b4aa9381..20889d411e 100644
--- a/include/boost/math/special_functions/detail/iconv.hpp
+++ b/include/boost/math/special_functions/detail/iconv.hpp
@@ -10,28 +10,29 @@
 #pragma once
 #endif
 
-#include <type_traits>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/round.hpp>
 
 namespace boost { namespace math { namespace detail{
 
 template <class T, class Policy>
-inline int iconv_imp(T v, Policy const&, std::true_type const&)
+BOOST_MATH_GPU_ENABLED inline int iconv_imp(T v, Policy const&, boost::math::true_type const&)
 {
    return static_cast<int>(v);
 }
 
 template <class T, class Policy>
-inline int iconv_imp(T v, Policy const& pol, std::false_type const&)
+BOOST_MATH_GPU_ENABLED inline int iconv_imp(T v, Policy const& pol, boost::math::false_type const&)
 {
    BOOST_MATH_STD_USING
    return iround(v, pol);
 }
 
 template <class T, class Policy>
-inline int iconv(T v, Policy const& pol)
+BOOST_MATH_GPU_ENABLED inline int iconv(T v, Policy const& pol)
 {
-   typedef typename std::is_convertible<T, int>::type tag_type;
+   typedef typename boost::math::is_convertible<T, int>::type tag_type;
    return iconv_imp(v, pol, tag_type());
 }
 
diff --git a/include/boost/math/special_functions/detail/unchecked_factorial.hpp b/include/boost/math/special_functions/detail/unchecked_factorial.hpp
index f7720a2aba..92481f2c6e 100644
--- a/include/boost/math/special_functions/detail/unchecked_factorial.hpp
+++ b/include/boost/math/special_functions/detail/unchecked_factorial.hpp
@@ -10,19 +10,23 @@
 #pragma once
 #endif
 
-#ifdef _MSC_VER
-#pragma warning(push) // Temporary until lexical cast fixed.
-#pragma warning(disable: 4127 4701)
-#endif
-#include <boost/math/tools/convert_from_string.hpp>
-#ifdef _MSC_VER
-#pragma warning(pop)
-#endif
-#include <cmath>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/array.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
-#include <boost/math/tools/cxx03_warn.hpp>
-#include <array>
-#include <type_traits>
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+#  ifdef _MSC_VER
+#    pragma warning(push) // Temporary until lexical cast fixed.
+#    pragma warning(disable: 4127 4701)
+#  endif
+#  include <boost/math/tools/convert_from_string.hpp>
+#  ifdef _MSC_VER
+#    pragma warning(pop)
+#  endif
+#endif
+
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -46,13 +50,21 @@ struct max_factorial;
 template <class T, bool = true>
 struct unchecked_factorial_data;
 
+#ifdef BOOST_MATH_HAS_NVRTC
+
+// Need fwd decl
+template <typename T>
+BOOST_MATH_GPU_ENABLED inline T unchecked_factorial(unsigned i);
+
+#endif
+
 #ifndef BOOST_MATH_HAS_GPU_SUPPORT
 
 template <bool b>
 struct unchecked_factorial_data<float, b>
 {
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   static constexpr std::array<float, 35> factorials = { {
+   static constexpr boost::math::array<float, 35> factorials = { {
       1.0F,
       1.0F,
       2.0F,
@@ -90,15 +102,15 @@ struct unchecked_factorial_data<float, b>
       0.29523279903960414084761860964352e39F,
    }};
 #else
-   static const std::array<float, 35> factorials;
+   static const boost::math::array<float, 35> factorials;
 #endif
 };
 
 template<bool b>
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   constexpr std::array<float, 35> unchecked_factorial_data<float, b>::factorials;
+   constexpr boost::math::array<float, 35> unchecked_factorial_data<float, b>::factorials;
 #else
-   const std::array<float, 35> unchecked_factorial_data<float, b>::factorials = {{
+   const boost::math::array<float, 35> unchecked_factorial_data<float, b>::factorials = {{
       1.0F,
       1.0F,
       2.0F,
@@ -204,7 +216,7 @@ template <bool b>
 struct unchecked_factorial_data<double, b>
 {
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   static constexpr std::array<double, 171> factorials = { {
+   static constexpr boost::math::array<double, 171> factorials = { {
       1.0,
       1.0,
       2.0,
@@ -378,15 +390,15 @@ struct unchecked_factorial_data<double, b>
       0.7257415615307998967396728211129263114717e307,
    }};
 #else
-   static const std::array<double, 171> factorials;
+   static const boost::math::array<double, 171> factorials;
 #endif
 };
 
 template <bool b>
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   constexpr std::array<double, 171> unchecked_factorial_data<double, b>::factorials;
+   constexpr boost::math::array<double, 171> unchecked_factorial_data<double, b>::factorials;
 #else
-   const std::array<double, 171> unchecked_factorial_data<double, b>::factorials = {{
+   const boost::math::array<double, 171> unchecked_factorial_data<double, b>::factorials = {{
       1.0,
       1.0,
       2.0,
@@ -633,7 +645,7 @@ template <bool b>
 struct unchecked_factorial_data<long double, b>
 {
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   static constexpr std::array<long double, 171> factorials = { {
+   static constexpr boost::math::array<long double, 171> factorials = { {
       1L,
       1L,
       2L,
@@ -807,15 +819,15 @@ struct unchecked_factorial_data<long double, b>
       0.7257415615307998967396728211129263114717e307L,
    }};
 #else
-   static const std::array<long double, 171> factorials;
+   static const boost::math::array<long double, 171> factorials;
 #endif
 };
 
 template <bool b>
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   constexpr std::array<long double, 171> unchecked_factorial_data<long double, b>::factorials;
+   constexpr boost::math::array<long double, 171> unchecked_factorial_data<long double, b>::factorials;
 #else
-   const std::array<long double, 171> unchecked_factorial_data<long double, b>::factorials = {{
+   const boost::math::array<long double, 171> unchecked_factorial_data<long double, b>::factorials = {{
       1L,
       1L,
       2L,
@@ -1008,7 +1020,7 @@ template <bool b>
 struct unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>
 {
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-   static constexpr std::array<BOOST_MATH_FLOAT128_TYPE, 171> factorials = { {
+   static constexpr boost::math::array<BOOST_MATH_FLOAT128_TYPE, 171> factorials = { {
       1,
       1,
       2,
@@ -1182,15 +1194,15 @@ struct unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>
       0.7257415615307998967396728211129263114717e307Q,
    } };
 #else
-   static const std::array<BOOST_MATH_FLOAT128_TYPE, 171> factorials;
+   static const boost::math::array<BOOST_MATH_FLOAT128_TYPE, 171> factorials;
 #endif
 };
 
 template <bool b>
 #ifdef BOOST_MATH_HAVE_CONSTEXPR_TABLES
-constexpr std::array<BOOST_MATH_FLOAT128_TYPE, 171> unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>::factorials;
+constexpr boost::math::array<BOOST_MATH_FLOAT128_TYPE, 171> unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>::factorials;
 #else
-const std::array<BOOST_MATH_FLOAT128_TYPE, 171> unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>::factorials = { {
+const boost::math::array<BOOST_MATH_FLOAT128_TYPE, 171> unchecked_factorial_data<BOOST_MATH_FLOAT128_TYPE, b>::factorials = { {
       1,
       1,
       2,
@@ -1402,7 +1414,7 @@ const typename unchecked_factorial_initializer<T>::init unchecked_factorial_init
 
 
 template <class T, int N>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, N>&)
+inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, N>&)
 {
    //
    // If you're foolish enough to instantiate factorial
@@ -1416,10 +1428,10 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, N
    // unsigned int nfac = static_cast<unsigned int>(factorial<double>(n));
    // See factorial documentation for more detail.
    //
-   static_assert(!std::is_integral<T>::value && !std::numeric_limits<T>::is_integer, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value && !boost::math::numeric_limits<T>::is_integer, "Type T must not be an integral type");
 
    // We rely on C++11 thread safe initialization here:
-   static const std::array<T, 101> factorials = {{
+   static const boost::math::array<T, 101> factorials = {{
       T(boost::math::tools::convert_from_string<T>("1")),
       T(boost::math::tools::convert_from_string<T>("1")),
       T(boost::math::tools::convert_from_string<T>("2")),
@@ -1527,7 +1539,7 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, N
 }
 
 template <class T>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 0>&)
+inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, 0>&)
 {
    //
    // If you're foolish enough to instantiate factorial
@@ -1541,7 +1553,7 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 0
    // unsigned int nfac = static_cast<unsigned int>(factorial<double>(n));
    // See factorial documentation for more detail.
    //
-   static_assert(!std::is_integral<T>::value && !std::numeric_limits<T>::is_integer, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value && !boost::math::numeric_limits<T>::is_integer, "Type T must not be an integral type");
 
    static const char* const factorial_strings[] = {
          "1",
@@ -1667,13 +1679,13 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 0
 #endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 template <class T>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, std::numeric_limits<float>::digits>&)
+BOOST_MATH_GPU_ENABLED inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, boost::math::numeric_limits<float>::digits>&)
 {
    return unchecked_factorial<float>(i);
 }
 
 template <class T>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, std::numeric_limits<double>::digits>&)
+BOOST_MATH_GPU_ENABLED inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, boost::math::numeric_limits<double>::digits>&)
 {
    return unchecked_factorial<double>(i);
 }
@@ -1682,14 +1694,14 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, s
 
 #if DBL_MANT_DIG != LDBL_MANT_DIG
 template <class T>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, LDBL_MANT_DIG>&)
+inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, LDBL_MANT_DIG>&)
 {
    return unchecked_factorial<long double>(i);
 }
 #endif
 #ifdef BOOST_MATH_USE_FLOAT128
 template <class T>
-inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 113>&)
+inline T unchecked_factorial_imp(unsigned i, const boost::math::integral_constant<int, 113>&)
 {
    return unchecked_factorial<BOOST_MATH_FLOAT128_TYPE>(i);
 }
@@ -1698,14 +1710,14 @@ inline T unchecked_factorial_imp(unsigned i, const std::integral_constant<int, 1
 #endif // BOOST_MATH_HAS_GPU_SUPPORT
 
 template <class T>
-inline T unchecked_factorial(unsigned i)
+BOOST_MATH_GPU_ENABLED inline T unchecked_factorial(unsigned i)
 {
    typedef typename boost::math::policies::precision<T, boost::math::policies::policy<> >::type tag_type;
    return unchecked_factorial_imp<T>(i, tag_type());
 }
 
 #ifdef BOOST_MATH_USE_FLOAT128
-#define BOOST_MATH_DETAIL_FLOAT128_MAX_FACTORIAL : std::numeric_limits<T>::digits == 113 ? max_factorial<BOOST_MATH_FLOAT128_TYPE>::value
+#define BOOST_MATH_DETAIL_FLOAT128_MAX_FACTORIAL : boost::math::numeric_limits<T>::digits == 113 ? max_factorial<BOOST_MATH_FLOAT128_TYPE>::value
 #else
 #define BOOST_MATH_DETAIL_FLOAT128_MAX_FACTORIAL
 #endif
@@ -1714,10 +1726,10 @@ template <class T>
 struct max_factorial
 {
    static constexpr unsigned value = 
-      std::numeric_limits<T>::digits == std::numeric_limits<float>::digits ? max_factorial<float>::value 
-      : std::numeric_limits<T>::digits == std::numeric_limits<double>::digits ? max_factorial<double>::value
+      boost::math::numeric_limits<T>::digits == boost::math::numeric_limits<float>::digits ? max_factorial<float>::value 
+      : boost::math::numeric_limits<T>::digits == boost::math::numeric_limits<double>::digits ? max_factorial<double>::value
       #ifndef BOOST_MATH_GPU_ENABLED 
-      : std::numeric_limits<T>::digits == std::numeric_limits<long double>::digits ? max_factorial<long double>::value 
+      : boost::math::numeric_limits<T>::digits == boost::math::numeric_limits<long double>::digits ? max_factorial<long double>::value 
       BOOST_MATH_DETAIL_FLOAT128_MAX_FACTORIAL
       #endif
       : 100;
diff --git a/include/boost/math/special_functions/expm1.hpp b/include/boost/math/special_functions/expm1.hpp
index b59721e932..5e61ca20b0 100644
--- a/include/boost/math/special_functions/expm1.hpp
+++ b/include/boost/math/special_functions/expm1.hpp
@@ -15,9 +15,6 @@
 
 #ifndef BOOST_MATH_HAS_NVRTC
 
-#include <cmath>
-#include <cstdint>
-#include <limits>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/big_constant.hpp>
@@ -25,6 +22,9 @@
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/assert.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -49,10 +49,10 @@ namespace detail
   {
      typedef T result_type;
 
-     expm1_series(T x)
+     BOOST_MATH_GPU_ENABLED expm1_series(T x)
         : k(0), m_x(x), m_term(1) {}
 
-     T operator()()
+     BOOST_MATH_GPU_ENABLED T operator()()
      {
         ++k;
         m_term *= m_x;
@@ -60,7 +60,7 @@ namespace detail
         return m_term;
      }
 
-     int count()const
+     BOOST_MATH_GPU_ENABLED int count()const
      {
         return k;
      }
@@ -78,26 +78,28 @@ struct expm1_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init(tag());
       }
       template <int N>
-      static void do_init(const std::integral_constant<int, N>&){}
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, N>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          expm1(T(0.5));
       }
-      static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
       {
          expm1(T(0.5));
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
-   static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_STATIC const init initializer;
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -110,7 +112,7 @@ const typename expm1_initializer<T, Policy, tag>::init expm1_initializer<T, Poli
 // This version uses a Taylor series expansion for 0.5 > |x| > epsilon.
 //
 template <class T, class Policy>
-T expm1_imp(T x, const std::integral_constant<int, 0>&, const Policy& pol)
+T expm1_imp(T x, const boost::math::integral_constant<int, 0>&, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -132,7 +134,7 @@ T expm1_imp(T x, const std::integral_constant<int, 0>&, const Policy& pol)
    if(a < tools::epsilon<T>())
       return x;
    detail::expm1_series<T> s(x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    T result = tools::sum_series(s, policies::get_epsilon<T, Policy>(), max_iter);
 
@@ -141,7 +143,7 @@ T expm1_imp(T x, const std::integral_constant<int, 0>&, const Policy& pol)
 }
 
 template <class T, class P>
-T expm1_imp(T x, const std::integral_constant<int, 53>&, const P& pol)
+BOOST_MATH_GPU_ENABLED T expm1_imp(T x, const boost::math::integral_constant<int, 53>&, const P& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -159,16 +161,16 @@ T expm1_imp(T x, const std::integral_constant<int, 53>&, const P& pol)
    if(a < tools::epsilon<T>())
       return x;
 
-   static const float Y = 0.10281276702880859e1f;
-   static const T n[] = { static_cast<T>(-0.28127670288085937e-1), static_cast<T>(0.51278186299064534e0), static_cast<T>(-0.6310029069350198e-1), static_cast<T>(0.11638457975729296e-1), static_cast<T>(-0.52143390687521003e-3), static_cast<T>(0.21491399776965688e-4) };
-   static const T d[] = { 1, static_cast<T>(-0.45442309511354755e0), static_cast<T>(0.90850389570911714e-1), static_cast<T>(-0.10088963629815502e-1), static_cast<T>(0.63003407478692265e-3), static_cast<T>(-0.17976570003654402e-4) };
+   BOOST_MATH_STATIC const float Y = 0.10281276702880859e1f;
+   BOOST_MATH_STATIC const T n[] = { static_cast<T>(-0.28127670288085937e-1), static_cast<T>(0.51278186299064534e0), static_cast<T>(-0.6310029069350198e-1), static_cast<T>(0.11638457975729296e-1), static_cast<T>(-0.52143390687521003e-3), static_cast<T>(0.21491399776965688e-4) };
+   BOOST_MATH_STATIC const T d[] = { 1, static_cast<T>(-0.45442309511354755e0), static_cast<T>(0.90850389570911714e-1), static_cast<T>(-0.10088963629815502e-1), static_cast<T>(0.63003407478692265e-3), static_cast<T>(-0.17976570003654402e-4) };
 
    T result = x * Y + x * tools::evaluate_polynomial(n, x) / tools::evaluate_polynomial(d, x);
    return result;
 }
 
 template <class T, class P>
-T expm1_imp(T x, const std::integral_constant<int, 64>&, const P& pol)
+BOOST_MATH_GPU_ENABLED T expm1_imp(T x, const boost::math::integral_constant<int, 64>&, const P& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -186,8 +188,8 @@ T expm1_imp(T x, const std::integral_constant<int, 64>&, const P& pol)
    if(a < tools::epsilon<T>())
       return x;
 
-   static const float Y = 0.10281276702880859375e1f;
-   static const T n[] = {
+   BOOST_MATH_STATIC const float Y = 0.10281276702880859375e1f;
+   BOOST_MATH_STATIC const T n[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.281276702880859375e-1),
        BOOST_MATH_BIG_CONSTANT(T, 64, 0.512980290285154286358e0),
        BOOST_MATH_BIG_CONSTANT(T, 64, -0.667758794592881019644e-1),
@@ -196,7 +198,7 @@ T expm1_imp(T x, const std::integral_constant<int, 64>&, const P& pol)
        BOOST_MATH_BIG_CONSTANT(T, 64, 0.447441185192951335042e-4),
        BOOST_MATH_BIG_CONSTANT(T, 64, -0.714539134024984593011e-6)
    };
-   static const T d[] = {
+   BOOST_MATH_STATIC const T d[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 1.0),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.461477618025562520389e0),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.961237488025708540713e-1),
@@ -211,7 +213,7 @@ T expm1_imp(T x, const std::integral_constant<int, 64>&, const P& pol)
 }
 
 template <class T, class P>
-T expm1_imp(T x, const std::integral_constant<int, 113>&, const P& pol)
+BOOST_MATH_GPU_ENABLED T expm1_imp(T x, const boost::math::integral_constant<int, 113>&, const P& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -263,7 +265,7 @@ T expm1_imp(T x, const std::integral_constant<int, 113>&, const P& pol)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type expm1(T x, const Policy& /* pol */)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type expm1(T x, const Policy& /* pol */)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -275,7 +277,7 @@ inline typename tools::promote_args<T>::type expm1(T x, const Policy& /* pol */)
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 53 ? 53 :
       precision_type::value <= 64 ? 64 :
diff --git a/include/boost/math/special_functions/factorials.hpp b/include/boost/math/special_functions/factorials.hpp
index 7229635cb9..ec6978bdc5 100644
--- a/include/boost/math/special_functions/factorials.hpp
+++ b/include/boost/math/special_functions/factorials.hpp
@@ -10,10 +10,14 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/detail/unchecked_factorial.hpp>
-#include <array>
+#include <boost/math/special_functions/math_fwd.hpp>
+
 #ifdef _MSC_VER
 #pragma warning(push) // Temporary until lexical cast fixed.
 #pragma warning(disable: 4127 4701)
@@ -21,16 +25,14 @@
 #ifdef _MSC_VER
 #pragma warning(pop)
 #endif
-#include <type_traits>
-#include <cmath>
 
 namespace boost { namespace math
 {
 
 template <class T, class Policy>
-inline T factorial(unsigned i, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T factorial(unsigned i, const Policy& pol)
 {
-   static_assert(!std::is_integral<T>::value, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value, "Type T must not be an integral type");
    // factorial<unsigned int>(n) is not implemented
    // because it would overflow integral type T for too small n
    // to be useful. Use instead a floating-point type,
@@ -49,7 +51,7 @@ inline T factorial(unsigned i, const Policy& pol)
 }
 
 template <class T>
-inline T factorial(unsigned i)
+BOOST_MATH_GPU_ENABLED inline T factorial(unsigned i)
 {
    return factorial<T>(i, policies::policy<>());
 }
@@ -72,9 +74,9 @@ inline double factorial<double>(unsigned i)
 }
 */
 template <class T, class Policy>
-T double_factorial(unsigned i, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T double_factorial(unsigned i, const Policy& pol)
 {
-   static_assert(!std::is_integral<T>::value, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value, "Type T must not be an integral type");
    BOOST_MATH_STD_USING  // ADL lookup of std names
    if(i & 1)
    {
@@ -107,17 +109,20 @@ T double_factorial(unsigned i, const Policy& pol)
 }
 
 template <class T>
-inline T double_factorial(unsigned i)
+BOOST_MATH_GPU_ENABLED inline T double_factorial(unsigned i)
 {
    return double_factorial<T>(i, policies::policy<>());
 }
 
+// TODO(mborland): We do not currently have support for tgamma_delta_ratio
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 namespace detail{
 
 template <class T, class Policy>
 T rising_factorial_imp(T x, int n, const Policy& pol)
 {
-   static_assert(!std::is_integral<T>::value, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value, "Type T must not be an integral type");
    if(x < 0)
    {
       //
@@ -165,7 +170,7 @@ T rising_factorial_imp(T x, int n, const Policy& pol)
 template <class T, class Policy>
 inline T falling_factorial_imp(T x, unsigned n, const Policy& pol)
 {
-   static_assert(!std::is_integral<T>::value, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value, "Type T must not be an integral type");
    BOOST_MATH_STD_USING // ADL of std names
    if(x == 0)
       return 0;
@@ -262,6 +267,8 @@ inline typename tools::promote_args<RT>::type
       static_cast<result_type>(x), n, pol);
 }
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 } // namespace math
 } // namespace boost
 
diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index afb8e97282..9268ba4156 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -2287,6 +2287,7 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 #else
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/expm1.hpp>
 
 namespace boost {
 namespace math {
@@ -2295,7 +2296,7 @@ inline BOOST_MATH_GPU_ENABLED float tgamma(float x) { return ::tgammaf(x); }
 inline BOOST_MATH_GPU_ENABLED double tgamma(double x) { return ::tgamma(x); }
 
 template <typename T, typename Policy>
-inline BOOST_MATH_GPU_ENABLED T tgamma(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED T tgamma(T x, const Policy&)
 {
    return boost::math::tgamma(x);
 }
@@ -2304,11 +2305,49 @@ inline BOOST_MATH_GPU_ENABLED float lgamma(float x) { return ::lgammaf(x); }
 inline BOOST_MATH_GPU_ENABLED double lgamma(double x) { return ::lgamma(x); }
 
 template <typename T, typename Policy>
-inline BOOST_MATH_GPU_ENABLED T lgamma(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED T lgamma(T x, const Policy&)
 {
    return boost::math::lgamma(x);
 }
 
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED T lgamma(T x, int* sign, const Policy&)
+{
+   auto res = boost::math::lgamma(x);
+   if (sign != nullptr)
+   {
+      if (res < 0)
+      {
+         *sign = -1;
+      }
+      else
+      {
+         *sign = 1;
+      }
+   }
+
+   return res;
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED T tgamma1pm1(T z)
+{
+   using namespace boost::math;
+
+   if (fabs(z) < T(0.55))
+   {
+      return expm1(lgamma(z));
+   }
+
+   return expm1(lgamma(1 + z));
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED T tgamma1pm1(T x, const Policy&)
+{
+   return tgamma1pm1(x);
+}
+
 } // namespace math
 } // namespace boost
 
diff --git a/include/boost/math/special_functions/hypot.hpp b/include/boost/math/special_functions/hypot.hpp
index c56c751102..f38e37e872 100644
--- a/include/boost/math/special_functions/hypot.hpp
+++ b/include/boost/math/special_functions/hypot.hpp
@@ -12,20 +12,20 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
-#include <algorithm> // for swap
-#include <cmath>
 
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
-T hypot_imp(T x, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T hypot_imp(T x, T y, const Policy& pol)
 {
    //
    // Normalize x and y, so that both are positive and x >= y:
    //
-   using std::fabs; using std::sqrt; // ADL of std names
+   BOOST_MATH_STD_USING
 
    x = fabs(x);
    y = fabs(y);
@@ -35,16 +35,16 @@ T hypot_imp(T x, T y, const Policy& pol)
 #pragma warning(disable: 4127)
 #endif
    // special case, see C99 Annex F:
-   if(std::numeric_limits<T>::has_infinity
-      && ((x == std::numeric_limits<T>::infinity())
-      || (y == std::numeric_limits<T>::infinity())))
+   if(boost::math::numeric_limits<T>::has_infinity
+      && ((x == boost::math::numeric_limits<T>::infinity())
+      || (y == boost::math::numeric_limits<T>::infinity())))
       return policies::raise_overflow_error<T>("boost::math::hypot<%1%>(%1%,%1%)", nullptr, pol);
 #ifdef _MSC_VER
 #pragma warning(pop)
 #endif
 
    if(y > x)
-      (std::swap)(x, y);
+      BOOST_MATH_GPU_SAFE_SWAP(x, y);
 
    if(x * tools::epsilon<T>() >= y)
       return x;
@@ -56,7 +56,7 @@ T hypot_imp(T x, T y, const Policy& pol)
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    hypot(T1 x, T2 y)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -65,7 +65,7 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    hypot(T1 x, T2 y, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 289b27592a..21f51e5075 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -24,12 +24,16 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <vector>
 #include <complex>
 #include <type_traits>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/detail/round_fwd.hpp>
 #include <boost/math/tools/promotion.hpp> // for argument promotion.
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/policies/policy.hpp>
 
 #define BOOST_NO_MACRO_EXPAND /**/
@@ -420,15 +424,15 @@ namespace boost
    template <class RT>
    struct max_factorial;
    template <class RT>
-   RT factorial(unsigned int);
+   BOOST_MATH_GPU_ENABLED RT factorial(unsigned int);
    template <class RT, class Policy>
-   RT factorial(unsigned int, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED RT factorial(unsigned int, const Policy& pol);
    template <class RT>
    BOOST_MATH_GPU_ENABLED RT unchecked_factorial(unsigned int BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE(RT));
    template <class RT>
-   RT double_factorial(unsigned i);
+   BOOST_MATH_GPU_ENABLED RT double_factorial(unsigned i);
    template <class RT, class Policy>
-   RT double_factorial(unsigned i, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED RT double_factorial(unsigned i, const Policy& pol);
 
    template <class RT>
    tools::promote_args_t<RT> falling_factorial(RT x, unsigned n);
@@ -554,11 +558,11 @@ namespace boost
 
    // Hypotenuse function sqrt(x ^ 2 + y ^ 2).
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          hypot(T1 x, T2 y);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          hypot(T1 x, T2 y, const Policy&);
 
    // cbrt - cube root.
@@ -607,10 +611,10 @@ namespace boost
 
    // sinus cardinals:
    template <class T>
-   tools::promote_args_t<T> sinc_pi(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sinc_pi(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> sinc_pi(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> sinc_pi(T x, const Policy&);
 
    template <class T>
    tools::promote_args_t<T> sinhc_pi(T x);
@@ -639,36 +643,36 @@ namespace boost
 
    namespace detail{
 
-      typedef std::integral_constant<int, 0> bessel_no_int_tag;      // No integer optimisation possible.
-      typedef std::integral_constant<int, 1> bessel_maybe_int_tag;   // Maybe integer optimisation.
-      typedef std::integral_constant<int, 2> bessel_int_tag;         // Definite integer optimisation.
+      typedef boost::math::integral_constant<int, 0> bessel_no_int_tag;      // No integer optimisation possible.
+      typedef boost::math::integral_constant<int, 1> bessel_maybe_int_tag;   // Maybe integer optimisation.
+      typedef boost::math::integral_constant<int, 2> bessel_int_tag;         // Definite integer optimisation.
 
       template <class T1, class T2, class Policy>
       struct bessel_traits
       {
-         using result_type = typename std::conditional<
-            std::is_integral<T1>::value,
+         using result_type = typename boost::math::conditional<
+            boost::math::is_integral<T1>::value,
             typename tools::promote_args<T2>::type,
             tools::promote_args_t<T1, T2>
          >::type;
 
          typedef typename policies::precision<result_type, Policy>::type precision_type;
 
-         using optimisation_tag = typename std::conditional<
+         using optimisation_tag = typename boost::math::conditional<
             (precision_type::value <= 0 || precision_type::value > 64),
             bessel_no_int_tag,
-            typename std::conditional<
-               std::is_integral<T1>::value,
+            typename boost::math::conditional<
+               boost::math::is_integral<T1>::value,
                bessel_int_tag,
                bessel_maybe_int_tag
             >::type
          >::type;
 
-         using optimisation_tag128 = typename std::conditional<
+         using optimisation_tag128 = typename boost::math::conditional<
             (precision_type::value <= 0 || precision_type::value > 113),
             bessel_no_int_tag,
-            typename std::conditional<
-               std::is_integral<T1>::value,
+            typename boost::math::conditional<
+               boost::math::is_integral<T1>::value,
                bessel_int_tag,
                bessel_maybe_int_tag
             >::type
@@ -678,98 +682,98 @@ namespace boost
 
    // Bessel functions:
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j(T1 v, T2 x, const Policy& pol);
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j_prime(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_j_prime(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j(T1 v, T2 x);
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j_prime(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_j_prime(T1 v, T2 x);
 
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel(unsigned v, T x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel(unsigned v, T x, const Policy& pol);
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel_prime(unsigned v, T x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type sph_bessel_prime(unsigned v, T x, const Policy& pol);
 
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel(unsigned v, T x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel(unsigned v, T x);
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel_prime(unsigned v, T x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_bessel_prime(unsigned v, T x);
 
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i(T1 v, T2 x, const Policy& pol);
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i_prime(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_i_prime(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i(T1 v, T2 x);
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i_prime(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_i_prime(T1 v, T2 x);
 
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k(T1 v, T2 x, const Policy& pol);
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k_prime(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_bessel_k_prime(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k(T1 v, T2 x);
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k_prime(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_bessel_k_prime(T1 v, T2 x);
 
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann(T1 v, T2 x, const Policy& pol);
    template <class T1, class T2, class Policy>
-   typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann_prime(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, Policy>::result_type cyl_neumann_prime(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann(T1 v, T2 x);
    template <class T1, class T2>
-   typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann_prime(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type cyl_neumann_prime(T1 v, T2 x);
 
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann(unsigned v, T x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann(unsigned v, T x, const Policy& pol);
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann_prime(unsigned v, T x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type sph_neumann_prime(unsigned v, T x, const Policy& pol);
 
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann(unsigned v, T x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann(unsigned v, T x);
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann_prime(unsigned v, T x);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type sph_neumann_prime(unsigned v, T x);
 
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type cyl_bessel_j_zero(T v, int m, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type cyl_bessel_j_zero(T v, int m, const Policy& pol);
 
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_bessel_j_zero(T v, int m);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_bessel_j_zero(T v, int m);
 
    template <class T, class OutputIterator>
-   OutputIterator cyl_bessel_j_zero(T v,
+   BOOST_MATH_GPU_ENABLED OutputIterator cyl_bessel_j_zero(T v,
                           int start_index,
                           unsigned number_of_zeros,
                           OutputIterator out_it);
 
    template <class T, class OutputIterator, class Policy>
-   OutputIterator cyl_bessel_j_zero(T v,
+   BOOST_MATH_GPU_ENABLED OutputIterator cyl_bessel_j_zero(T v,
                           int start_index,
                           unsigned number_of_zeros,
                           OutputIterator out_it,
                           const Policy&);
 
    template <class T, class Policy>
-   typename detail::bessel_traits<T, T, Policy>::result_type cyl_neumann_zero(T v, int m, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, Policy>::result_type cyl_neumann_zero(T v, int m, const Policy& pol);
 
    template <class T>
-   typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_neumann_zero(T v, int m);
+   BOOST_MATH_GPU_ENABLED typename detail::bessel_traits<T, T, policies::policy<> >::result_type cyl_neumann_zero(T v, int m);
 
    template <class T, class OutputIterator>
-   OutputIterator cyl_neumann_zero(T v,
+   BOOST_MATH_GPU_ENABLED OutputIterator cyl_neumann_zero(T v,
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it);
 
    template <class T, class OutputIterator, class Policy>
-   OutputIterator cyl_neumann_zero(T v,
+   BOOST_MATH_GPU_ENABLED OutputIterator cyl_neumann_zero(T v,
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it,
@@ -1400,10 +1404,10 @@ namespace boost
 \
    using boost::math::max_factorial;\
    template <class RT>\
-   inline RT factorial(unsigned int i) { return boost::math::factorial<RT>(i, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline RT factorial(unsigned int i) { return boost::math::factorial<RT>(i, Policy()); }\
    using boost::math::unchecked_factorial;\
    template <class RT>\
-   inline RT double_factorial(unsigned i){ return boost::math::double_factorial<RT>(i, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline RT double_factorial(unsigned i){ return boost::math::double_factorial<RT>(i, Policy()); }\
    template <class RT>\
    inline boost::math::tools::promote_args_t<RT> falling_factorial(RT x, unsigned n){ return boost::math::falling_factorial(x, n, Policy()); }\
    template <class RT>\
@@ -1465,7 +1469,7 @@ namespace boost
    \
    template <class T1, class T2>\
    inline boost::math::tools::promote_args_t<T1, T2> \
-   hypot(T1 x, T2 y){ return boost::math::hypot(x, y, Policy()); }\
+   BOOST_MATH_GPU_ENABLED hypot(T1 x, T2 y){ return boost::math::hypot(x, y, Policy()); }\
 \
    template <class RT>\
    inline boost::math::tools::promote_args_t<RT> cbrt(RT z){ return boost::math::cbrt(z, Policy()); }\
@@ -1487,7 +1491,7 @@ namespace boost
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sqrt1pm1(const T& val){ return boost::math::sqrt1pm1(val, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> sinc_pi(T x){ return boost::math::sinc_pi(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> sinc_pi(T x){ return boost::math::sinc_pi(x, Policy()); }\
 \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> sinhc_pi(T x){ return boost::math::sinhc_pi(x, Policy()); }\
@@ -1817,6 +1821,6 @@ template <class OutputIterator, class T>\
 
 
 
-
+#endif // BOOST_MATH_HAS_NVRTC
 
 #endif // BOOST_MATH_SPECIAL_MATH_FWD_HPP
diff --git a/include/boost/math/special_functions/next.hpp b/include/boost/math/special_functions/next.hpp
index 02a208e4eb..fd08162f98 100644
--- a/include/boost/math/special_functions/next.hpp
+++ b/include/boost/math/special_functions/next.hpp
@@ -10,6 +10,11 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+// TODO(mborland): Need to remove recurrsion from these algos
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
@@ -920,4 +925,6 @@ inline typename tools::promote_args<T>::type float_advance(const T& val, int dis
 
 }} // boost math namespaces
 
+#endif
+
 #endif // BOOST_MATH_SPECIAL_NEXT_HPP
diff --git a/include/boost/math/special_functions/round.hpp b/include/boost/math/special_functions/round.hpp
index 7a76cd32ff..bb99da7e31 100644
--- a/include/boost/math/special_functions/round.hpp
+++ b/include/boost/math/special_functions/round.hpp
@@ -273,6 +273,30 @@ BOOST_MATH_GPU_ENABLED float round(float x, const Policy&)
    return ::roundf(x);
 }
 
+template <typename T>
+BOOST_MATH_GPU_ENABLED int iround(T x)
+{
+   return static_cast<int>(::lround(x));
+}
+
+template <>
+BOOST_MATH_GPU_ENABLED int iround(float x)
+{
+   return static_cast<int>(::lroundf(x));
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED int iround(T x, const Policy&)
+{
+   return static_cast<int>(::lround(x));
+}
+
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED int iround(float x, const Policy&)
+{
+   return static_cast<int>(::lroundf(x));
+}
+
 template <typename T>
 BOOST_MATH_GPU_ENABLED long lround(T x)
 {
diff --git a/include/boost/math/special_functions/sinc.hpp b/include/boost/math/special_functions/sinc.hpp
index ff1b2e966b..0c18ac3468 100644
--- a/include/boost/math/special_functions/sinc.hpp
+++ b/include/boost/math/special_functions/sinc.hpp
@@ -17,13 +17,13 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/policies/policy.hpp>
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
-#include <limits>
-#include <string>
-#include <stdexcept>
-#include <cmath>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+#include <boost/math/special_functions/math_fwd.hpp>
+#endif
 
 // These are the the "Sinus Cardinal" functions.
 
@@ -36,7 +36,7 @@ namespace boost
         // This is the "Sinus Cardinal" of index Pi.
 
         template<typename T>
-        inline T    sinc_pi_imp(const T x)
+        BOOST_MATH_GPU_ENABLED inline T    sinc_pi_imp(const T x)
         {
             BOOST_MATH_STD_USING
 
@@ -44,7 +44,7 @@ namespace boost
             {
                return 0;
             }
-            else if (abs(x) >= 3.3 * tools::forth_root_epsilon<T>())
+            else if (abs(x) >= T(3.3) * tools::forth_root_epsilon<T>())
             {
                 return(sin(x)/x);
             }
@@ -58,24 +58,23 @@ namespace boost
        } // namespace detail
 
        template <class T>
-       inline typename tools::promote_args<T>::type sinc_pi(T x)
+       BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sinc_pi(T x)
        {
           typedef typename tools::promote_args<T>::type result_type;
           return detail::sinc_pi_imp(static_cast<result_type>(x));
        }
 
        template <class T, class Policy>
-       inline typename tools::promote_args<T>::type sinc_pi(T x, const Policy&)
+       BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type sinc_pi(T x, const Policy&)
        {
           typedef typename tools::promote_args<T>::type result_type;
           return detail::sinc_pi_imp(static_cast<result_type>(x));
        }
 
         template<typename T, template<typename> class U>
-        inline U<T>    sinc_pi(const U<T> x)
+        BOOST_MATH_GPU_ENABLED inline U<T>    sinc_pi(const U<T> x)
         {
             BOOST_MATH_STD_USING
-            using    ::std::numeric_limits;
 
             T const    taylor_0_bound = tools::epsilon<T>();
             T const    taylor_2_bound = tools::root_epsilon<T>();
@@ -88,11 +87,11 @@ namespace boost
             else
             {
                 // approximation by taylor series in x at 0 up to order 0
-#ifdef __MWERKS__
+                #ifdef __MWERKS__
                 U<T>    result = static_cast<U<T> >(1);
-#else
+                #else
                 U<T>    result = U<T>(1);
-#endif
+                #endif
 
                 if    (abs(x) >= taylor_0_bound)
                 {
@@ -113,7 +112,7 @@ namespace boost
         }
 
         template<typename T, template<typename> class U, class Policy>
-        inline U<T>    sinc_pi(const U<T> x, const Policy&)
+        BOOST_MATH_GPU_ENABLED inline U<T>    sinc_pi(const U<T> x, const Policy&)
         {
            return sinc_pi(x);
         }
diff --git a/include/boost/math/special_functions/ulp.hpp b/include/boost/math/special_functions/ulp.hpp
index 3c0616db0e..5d1617aced 100644
--- a/include/boost/math/special_functions/ulp.hpp
+++ b/include/boost/math/special_functions/ulp.hpp
@@ -14,6 +14,7 @@
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
 #include <boost/math/special_functions/next.hpp>
+#include <boost/math/tools/precision.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
diff --git a/include/boost/math/tools/array.hpp b/include/boost/math/tools/array.hpp
new file mode 100644
index 0000000000..23e666673c
--- /dev/null
+++ b/include/boost/math/tools/array.hpp
@@ -0,0 +1,41 @@
+//  Copyright (c) 2024 Matt Borland
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+//  Regular use of std::array functions can not be used on 
+//  GPU platforms like CUDA since they are missing the __device__ marker
+//  Alias as needed to get correct support
+
+#ifndef BOOST_MATH_TOOLS_ARRAY_HPP
+#define BOOST_MATH_TOOLS_ARRAY_HPP
+
+#include <boost/math/tools/config.hpp>
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+#include <cuda/std/array>
+
+namespace boost {
+namespace math {
+
+using cuda::std::array;
+
+} // namespace math
+} // namespace boost
+
+#else
+
+#include <array>
+
+namespace boost {
+namespace math {
+
+using std::array;
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
+#endif // BOOST_MATH_TOOLS_ARRAY_HPP
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 2736d660fe..1f444c0048 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -676,6 +676,7 @@ namespace boost{ namespace math{
 #include <cuda/std/type_traits>
 #include <cuda/std/utility>
 #include <cuda/std/cstdint>
+#include <cuda/std/array>
 
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
@@ -733,7 +734,7 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 template <class T>
 BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_min(const T& a, const T& b) { return a < b ? a : b; }
 template <class T>
-BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { return a > b ? a : b; }
+BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_max(const T& a, const T& b) { return a > b ? a : b; }
 
 #define BOOST_MATH_GPU_SAFE_SWAP(a, b) gpu_safe_swap(a, b)
 #define BOOST_MATH_GPU_SAFE_MIN(a, b) gpu_safe_min(a, b)
@@ -794,10 +795,13 @@ BOOST_MATH_GPU_ENABLED constexpr T cuda_safe_max(const T& a, const T& b) { retur
 #define BOOST_MATH_NOEXCEPT(T) noexcept(boost::math::is_floating_point_v<T>)
 #define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE(T) 
 #define BOOST_MATH_EXPLICIT_TEMPLATE_TYPE_SPEC(T) 
+#define BOOST_MATH_APPEND_EXPLICIT_TEMPLATE_TYPE_SPEC(T) 
 #define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
 #define BOOST_MATH_FORCEINLINE __forceinline__
 #define BOOST_MATH_STD_USING  
 #define BOOST_MATH_IF_CONSTEXPR if constexpr
+#define BOOST_MATH_IS_FLOAT(T) (boost::math::is_floating_point<T>::value)
+#define BOOST_MATH_CONSTEXPR_TABLE_FUNCTION constexpr
 
 // This should be defined to nothing but since it is not specifically a math macro
 // we need to undef before proceeding
@@ -829,6 +833,9 @@ BOOST_MATH_GPU_ENABLED constexpr void gpu_safe_swap(T& a, T& b) { T t(a); a = b;
 #  define BOOST_MATH_INLINE_CONSTEXPR constexpr
 #endif
 
+#define BOOST_MATH_INSTRUMENT_VARIABLE(x)
+#define BOOST_MATH_INSTRUMENT_CODE(x) 
+
 #endif // NVRTC
 
 #endif // BOOST_MATH_TOOLS_CONFIG_HPP
diff --git a/include/boost/math/tools/roots.hpp b/include/boost/math/tools/roots.hpp
index 8f36aa22df..b0b0fc246c 100644
--- a/include/boost/math/tools/roots.hpp
+++ b/include/boost/math/tools/roots.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,22 +12,19 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-
-#ifndef BOOST_MATH_HAS_NVRTC // Disabled for now
-
 #include <boost/math/tools/complex.hpp> // test for multiprecision types in complex Newton
-
-#include <utility>
-#include <cmath>
-#include <tuple>
-#include <cstdint>
-
-#include <boost/math/tools/cxx03_warn.hpp>
-
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/special_functions/sign.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #include <boost/math/special_functions/next.hpp>
 #include <boost/math/tools/toms748_solve.hpp>
-#include <boost/math/policies/error_handling.hpp>
+#endif
 
 namespace boost {
 namespace math {
@@ -37,11 +35,11 @@ namespace detail {
 namespace dummy {
 
    template<int n, class T>
-   typename T::value_type get(const T&) BOOST_MATH_NOEXCEPT(T);
+   BOOST_MATH_GPU_ENABLED typename T::value_type get(const T&) BOOST_MATH_NOEXCEPT(T);
 }
 
 template <class Tuple, class T>
-void unpack_tuple(const Tuple& t, T& a, T& b) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED void unpack_tuple(const Tuple& t, T& a, T& b) BOOST_MATH_NOEXCEPT(T)
 {
    using dummy::get;
    // Use ADL to find the right overload for get:
@@ -49,7 +47,7 @@ void unpack_tuple(const Tuple& t, T& a, T& b) BOOST_MATH_NOEXCEPT(T)
    b = get<1>(t);
 }
 template <class Tuple, class T>
-void unpack_tuple(const Tuple& t, T& a, T& b, T& c) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED void unpack_tuple(const Tuple& t, T& a, T& b, T& c) BOOST_MATH_NOEXCEPT(T)
 {
    using dummy::get;
    // Use ADL to find the right overload for get:
@@ -59,7 +57,7 @@ void unpack_tuple(const Tuple& t, T& a, T& b, T& c) BOOST_MATH_NOEXCEPT(T)
 }
 
 template <class Tuple, class T>
-inline void unpack_0(const Tuple& t, T& val) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED inline void unpack_0(const Tuple& t, T& val) BOOST_MATH_NOEXCEPT(T)
 {
    using dummy::get;
    // Rely on ADL to find the correct overload of get:
@@ -67,26 +65,30 @@ inline void unpack_0(const Tuple& t, T& val) BOOST_MATH_NOEXCEPT(T)
 }
 
 template <class T, class U, class V>
-inline void unpack_tuple(const std::pair<T, U>& p, V& a, V& b) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED inline void unpack_tuple(const boost::math::pair<T, U>& p, V& a, V& b) BOOST_MATH_NOEXCEPT(T)
 {
    a = p.first;
    b = p.second;
 }
 template <class T, class U, class V>
-inline void unpack_0(const std::pair<T, U>& p, V& a) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED inline void unpack_0(const boost::math::pair<T, U>& p, V& a) BOOST_MATH_NOEXCEPT(T)
 {
    a = p.first;
 }
 
 template <class F, class T>
-void handle_zero_derivative(F f,
+BOOST_MATH_GPU_ENABLED void handle_zero_derivative(F f,
    T& last_f0,
    const T& f0,
    T& delta,
    T& result,
    T& guess,
    const T& min,
-   const T& max) noexcept(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+   const T& max) noexcept(BOOST_MATH_IS_FLOAT(T) 
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
+   && noexcept(std::declval<F>()(std::declval<T>()))
+   #endif
+   )
 {
    if (last_f0 == 0)
    {
@@ -132,25 +134,29 @@ void handle_zero_derivative(F f,
 } // namespace
 
 template <class F, class T, class Tol, class Policy>
-std::pair<T, T> bisect(F f, T min, T max, Tol tol, std::uintmax_t& max_iter, const Policy& pol) noexcept(policies::is_noexcept_error_policy<Policy>::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> bisect(F f, T min, T max, Tol tol, boost::math::uintmax_t& max_iter, const Policy& pol) noexcept(policies::is_noexcept_error_policy<Policy>::value && BOOST_MATH_IS_FLOAT(T) 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<F>()(std::declval<T>()))
+#endif
+)
 {
    T fmin = f(min);
    T fmax = f(max);
    if (fmin == 0)
    {
       max_iter = 2;
-      return std::make_pair(min, min);
+      return boost::math::make_pair(min, min);
    }
    if (fmax == 0)
    {
       max_iter = 2;
-      return std::make_pair(max, max);
+      return boost::math::make_pair(max, max);
    }
 
    //
    // Error checking:
    //
-   static const char* function = "boost::math::tools::bisect<%1%>";
+   constexpr auto function = "boost::math::tools::bisect<%1%>";
    if (min >= max)
    {
       return boost::math::detail::pair_from_single(policies::raise_evaluation_error(function,
@@ -200,29 +206,41 @@ std::pair<T, T> bisect(F f, T min, T max, Tol tol, std::uintmax_t& max_iter, con
    std::cout << "Bisection required " << max_iter << " iterations.\n";
 #endif
 
-   return std::make_pair(min, max);
+   return boost::math::make_pair(min, max);
 }
 
 template <class F, class T, class Tol>
-inline std::pair<T, T> bisect(F f, T min, T max, Tol tol, std::uintmax_t& max_iter)  noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> bisect(F f, T min, T max, Tol tol, boost::math::uintmax_t& max_iter)  noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value && BOOST_MATH_IS_FLOAT(T)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<F>()(std::declval<T>()))
+#endif
+)
 {
    return bisect(f, min, max, tol, max_iter, policies::policy<>());
 }
 
 template <class F, class T, class Tol>
-inline std::pair<T, T> bisect(F f, T min, T max, Tol tol) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> bisect(F f, T min, T max, Tol tol) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value && BOOST_MATH_IS_FLOAT(T) 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<F>()(std::declval<T>()))
+#endif
+)
 {
-   std::uintmax_t m = (std::numeric_limits<std::uintmax_t>::max)();
+   boost::math::uintmax_t m = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return bisect(f, min, max, tol, m, policies::policy<>());
 }
 
 
 template <class F, class T>
-T newton_raphson_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t& max_iter) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED T newton_raphson_iterate(F f, T guess, T min, T max, int digits, boost::math::uintmax_t& max_iter) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value && BOOST_MATH_IS_FLOAT(T)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<F>()(std::declval<T>()))
+#endif
+)
 {
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::tools::newton_raphson_iterate<%1%>";
+   constexpr auto function = "boost::math::tools::newton_raphson_iterate<%1%>";
    if (min > max)
    {
       return policies::raise_evaluation_error(function, "Range arguments in wrong order in boost::math::tools::newton_raphson_iterate(first arg=%1%)", min, boost::math::policies::policy<>());
@@ -249,7 +267,7 @@ T newton_raphson_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t&
    T max_range_f = 0;
    T min_range_f = 0;
 
-   std::uintmax_t count(max_iter);
+   boost::math::uintmax_t count(max_iter);
 
 #ifdef BOOST_MATH_INSTRUMENT
    std::cout << "Newton_raphson_iterate, guess = " << guess << ", min = " << min << ", max = " << max
@@ -336,12 +354,22 @@ T newton_raphson_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t&
 }
 
 template <class F, class T>
-inline T newton_raphson_iterate(F f, T guess, T min, T max, int digits) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED inline T newton_raphson_iterate(F f, T guess, T min, T max, int digits) noexcept(policies::is_noexcept_error_policy<policies::policy<> >::value && BOOST_MATH_IS_FLOAT(T)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<F>()(std::declval<T>()))
+#endif
+)
 {
-   std::uintmax_t m = (std::numeric_limits<std::uintmax_t>::max)();
+   boost::math::uintmax_t m = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return newton_raphson_iterate(f, guess, min, max, digits, m);
 }
 
+// TODO(mborland): Disabled for now
+// Recursion needs to be removed, but there is no demand at this time
+#ifdef BOOST_MATH_HAS_NVRTC
+}}} // Namespaces
+#else
+
 namespace detail {
 
    struct halley_step
diff --git a/include/boost/math/tools/series.hpp b/include/boost/math/tools/series.hpp
index a4b5cc6265..50f2828bb4 100644
--- a/include/boost/math/tools/series.hpp
+++ b/include/boost/math/tools/series.hpp
@@ -10,10 +10,10 @@
 #pragma once
 #endif
 
-#include <cmath>
-#include <cstdint>
-#include <limits>
+
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 
 namespace boost{ namespace math{ namespace tools{
 
@@ -21,13 +21,17 @@ namespace boost{ namespace math{ namespace tools{
 // Simple series summation come first:
 //
 template <class Functor, class U, class V>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, boost::math::uintmax_t& max_terms, const V& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
 
    typedef typename Functor::result_type result_type;
 
-   std::uintmax_t counter = max_terms;
+   boost::math::uintmax_t counter = max_terms;
 
    result_type result = init_value;
    result_type next_term;
@@ -44,14 +48,22 @@ BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor&
 }
 
 template <class Functor, class U>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, const U& factor, boost::math::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    typename Functor::result_type init_value = 0;
    return sum_series(func, factor, max_terms, init_value);
 }
 
 template <class Functor, class U>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, boost::math::uintmax_t& max_terms, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
@@ -60,17 +72,25 @@ BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor&
 }
 
 template <class Functor>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
-   std::uintmax_t iters = (std::numeric_limits<std::uintmax_t>::max)();
+   boost::math::uintmax_t iters = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    result_type init_val = 0;
    return sum_series(func, bits, iters, init_val);
 }
 
 template <class Functor>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, boost::math::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
    typedef typename Functor::result_type result_type;
@@ -79,23 +99,31 @@ BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor&
 }
 
 template <class Functor, class U>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type sum_series(Functor& func, int bits, const U& init_value) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
-   std::uintmax_t iters = (std::numeric_limits<std::uintmax_t>::max)();
+   boost::math::uintmax_t iters = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return sum_series(func, bits, iters, init_value);
 }
 //
 // Checked summation:
 //
 template <class Functor, class U, class V>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type checked_sum_series(Functor& func, const U& factor, std::uintmax_t& max_terms, const V& init_value, V& norm) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type checked_sum_series(Functor& func, const U& factor, boost::math::uintmax_t& max_terms, const V& init_value, V& norm) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
 
    typedef typename Functor::result_type result_type;
 
-   std::uintmax_t counter = max_terms;
+   boost::math::uintmax_t counter = max_terms;
 
    result_type result = init_value;
    result_type next_term;
@@ -125,7 +153,11 @@ BOOST_MATH_GPU_ENABLED inline typename Functor::result_type checked_sum_series(F
 // in any case the result is still much better than a naive summation.
 //
 template <class Functor>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
 
@@ -148,13 +180,17 @@ BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Fun
 }
 
 template <class Functor>
-BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits, std::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type) && noexcept(std::declval<Functor>()()))
+BOOST_MATH_GPU_ENABLED inline typename Functor::result_type kahan_sum_series(Functor& func, int bits, boost::math::uintmax_t& max_terms) noexcept(BOOST_MATH_IS_FLOAT(typename Functor::result_type)
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+&& noexcept(std::declval<Functor>()())
+#endif
+)
 {
    BOOST_MATH_STD_USING
 
    typedef typename Functor::result_type result_type;
 
-   std::uintmax_t counter = max_terms;
+   boost::math::uintmax_t counter = max_terms;
 
    result_type factor = ldexp(result_type(1), bits);
    result_type result = func();
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 44e818c58a..64fac76fba 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -17,12 +17,14 @@ run test_arcsine_pdf_float.cu ;
 run test_arcsine_quan_double.cu ;
 run test_arcsine_quan_float.cu ;
 run test_arcsine_range_support_double.cu ;
+
 run test_bernoulli_cdf_double.cu ;
 run test_bernoulli_cdf_float.cu ;
 run test_bernoulli_pdf_double.cu ;
 run test_bernoulli_pdf_float.cu ;
 run test_bernoulli_range_support_double.cu ;
 run test_bernoulli_range_support_float.cu ;
+
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;
@@ -31,6 +33,7 @@ run test_cauchy_quan_double.cu ;
 run test_cauchy_quan_float.cu ;
 run test_cauchy_range_support_double.cu ;
 run test_cauchy_range_support_float.cu ;
+
 run test_exponential_cdf_double.cu ;
 run test_exponential_cdf_float.cu ;
 run test_exponential_pdf_double.cu ;
@@ -39,40 +42,47 @@ run test_exponential_quan_double.cu ;
 run test_exponential_quan_float.cu ;
 run test_exponential_range_support_double.cu ;
 run test_exponential_range_support_float.cu ;
+
 run test_extreme_value_cdf_double.cu ;
 run test_extreme_value_cdf_float.cu ;
 run test_extreme_value_pdf_double.cu ;
 run test_extreme_value_pdf_float.cu ;
 run test_extreme_value_quan_double.cu ;
 run test_extreme_value_quan_float.cu ;
+
 run test_holtsmark_cdf_double.cu ;
 run test_holtsmark_cdf_float.cu ;
 run test_holtsmark_pdf_double.cu ;
 run test_holtsmark_pdf_float.cu ;
+
 run test_landau_cdf_double.cu ;
 run test_landau_cdf_float.cu ;
 run test_landau_pdf_double.cu ;
 run test_landau_pdf_float.cu ;
 run test_landau_quan_double.cu;
 run test_landau_quan_float.cu ;
+
 run test_laplace_cdf_double.cu ;
 run test_laplace_cdf_float.cu ;
 run test_laplace_pdf_double.cu ;
 run test_laplace_pdf_float.cu ;
 run test_laplace_quan_double.cu ;
 run test_laplace_quan_float.cu ;
+
 run test_logistic_cdf_double.cu ;
 run test_logistic_cdf_float.cu ;
 run test_logistic_pdf_double.cu ;
 run test_logistic_pdf_float.cu ;
 run test_logistic_quan_double.cu ;
 run test_logistic_quan_float.cu ;
+
 run test_mapairy_cdf_double.cu ;
 run test_mapairy_cdf_float.cu ;
 run test_mapairy_pdf_double.cu ;
 run test_mapairy_pdf_float.cu ;
 run test_mapairy_quan_double.cu ;
 run test_mapairy_quan_float.cu ;
+
 run test_saspoint5_cdf_double.cu ;
 run test_saspoint5_cdf_float.cu ;
 run test_saspoint5_pdf_double.cu ;
@@ -81,17 +91,52 @@ run test_saspoint5_quan_double.cu ;
 run test_saspoint5_quan_float.cu ;
 
 # Special Functions
-# run test_beta_simple.cpp ;
 run test_beta_double.cu ;
 run test_beta_float.cu ;
+
+run test_bessel_i0_double.cu ;
+run test_bessel_i0_float.cu ;
+run test_bessel_i1_double.cu ;
+run test_bessel_i1_float.cu ;
+run test_bessel_j0_double.cu ;
+run test_bessel_j0_float.cu ;
+run test_bessel_j1_double.cu ;
+run test_bessel_j1_float.cu ;
+run test_bessel_k0_double.cu ;
+run test_bessel_k0_float.cu ;
+run test_bessel_k1_double.cu ;
+run test_bessel_k1_float.cu ;
+run test_bessel_kn_double.cu ;
+run test_bessel_kn_float.cu ;
+run test_bessel_y0_double.cu ;
+run test_bessel_y0_float.cu ;
+run test_bessel_y1_double.cu ;
+run test_bessel_y1_float.cu ;
+run test_cyl_bessel_i_double.cu ;
+run test_cyl_bessel_i_float.cu ;
+run test_cyl_bessel_j_double.cu ;
+run test_cyl_bessel_j_float.cu ;
+run test_cyl_bessel_k_double.cu ;
+run test_cyl_bessel_k_float.cu ;
+run test_sph_bessel_double.cu ;
+run test_sph_bessel_float.cu ;
+run test_cyl_neumann_double.cu ;
+run test_cyl_neumann_float.cu ;
+run test_sph_neumann_double.cu ;
+run test_sph_neumann_float.cu ;
+
 run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
+
 run test_changesign_double.cu ;
 run test_changesign_float.cu ;
+
 run test_cos_pi_double.cu ;
 run test_cos_pi_float.cu ;
+
 run test_digamma_double.cu ;
 run test_digamma_float.cu ;
+
 run test_erf_double.cu ;
 run test_erf_float.cu ;
 run test_erf_inv_double.cu ;
@@ -100,21 +145,29 @@ run test_erfc_double.cu ;
 run test_erfc_float.cu ;
 run test_erfc_inv_double.cu ;
 run test_erfc_inv_float.cu ;
+
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
+
 run test_lgamma_double.cu ;
 run test_lgamma_float.cu ;
+run test_tgamma_double.cu ;
+run test_tgamma_float.cu ;
+
 run test_log1p_double.cu ;
 run test_log1p_float.cu ;
+
 run test_modf_double.cu ;
 run test_modf_float.cu ;
+
 run test_round_double.cu ;
 run test_round_float.cu ;
+
 run test_sin_pi_double.cu ; 
 run test_sin_pi_float.cu ;
-run test_tgamma_double.cu ;
-run test_tgamma_float.cu ;
+
 run test_trigamma_double.cu ;
 run test_trigamma_float.cu ;
+
 run test_trunc_double.cu ;
 run test_trunc_float.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 7e57f93ce6..de235822ef 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -90,12 +90,47 @@ run test_saspoint5_quan_nvrtc_float.cpp ;
 # Special Functions
 run test_beta_nvrtc_double.cpp ;
 run test_beta_nvrtc_float.cpp ;
+
+run test_bessel_i0_nvrtc_double.cpp ;
+run test_bessel_i0_nvrtc_float.cpp ;
+run test_bessel_i1_nvrtc_double.cpp ;
+run test_bessel_i1_nvrtc_float.cpp ;
+run test_bessel_j0_nvrtc_double.cpp ;
+run test_bessel_j0_nvrtc_float.cpp ;
+run test_bessel_j1_nvrtc_double.cpp ;
+run test_bessel_j1_nvrtc_float.cpp ;
+run test_bessel_k0_nvrtc_double.cpp ;
+run test_bessel_k0_nvrtc_float.cpp ;
+run test_bessel_k1_nvrtc_double.cpp ;
+run test_bessel_k1_nvrtc_float.cpp ;
+run test_bessel_kn_nvrtc_double.cpp ;
+run test_bessel_kn_nvrtc_float.cpp ;
+run test_bessel_y0_nvrtc_double.cpp ;
+run test_bessel_y0_nvrtc_float.cpp ;
+run test_bessel_y1_nvrtc_double.cpp ;
+run test_bessel_y1_nvrtc_float.cpp ;
+run test_cyl_bessel_i_nvrtc_double.cpp ;
+run test_cyl_bessel_i_nvrtc_float.cpp ;
+run test_cyl_bessel_j_nvrtc_double.cpp ;
+run test_cyl_bessel_j_nvrtc_float.cpp ;
+run test_cyl_bessel_k_nvrtc_double.cpp ;
+run test_cyl_bessel_k_nvrtc_float.cpp ;
+run test_sph_bessel_nvrtc_double.cpp ;
+run test_sph_bessel_nvrtc_float.cpp ;
+run test_cyl_neumann_nvrtc_double.cpp ;
+run test_cyl_neumann_nvrtc_float.cpp ;
+run test_sph_neumann_nvrtc_double.cpp ;
+run test_sph_neumann_nvrtc_float.cpp ;
+
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
+
 run test_cos_pi_nvrtc_double.cpp ;
 run test_cos_pi_nvrtc_float.cpp ;
+
 run test_digamma_nvrtc_double.cpp ;
 run test_digamma_nvrtc_float.cpp ;
+
 run test_erf_nvrtc_double.cpp ;
 run test_erf_nvrtc_float.cpp ;
 run test_erfc_nvrtc_double.cpp ;
@@ -104,22 +139,32 @@ run test_erf_inv_nvrtc_double.cpp ;
 run test_erf_inv_nvrtc_float.cpp ;
 run test_erfc_inv_nvrtc_double.cpp ;
 run test_erfc_inv_nvrtc_float.cpp ;
+
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
+
 run test_fpclassify_nvrtc_double.cpp ;
 run test_fpclassify_nvrtc_float.cpp ;
+
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
+
 run test_log1p_nvrtc_double.cpp ;
 run test_log1p_nvrtc_float.cpp ;
+
 run test_modf_nvrtc_double.cpp ;
 run test_modf_nvrtc_float.cpp ;
+
 run test_round_nvrtc_double.cpp ;
 run test_round_nvrtc_float.cpp ;
+
 run test_sign_nvrtc_double.cpp ;
 run test_sign_nvrtc_float.cpp ;
+
 run test_sin_pi_nvrtc_double.cpp ;
 run test_sin_pi_nvrtc_float.cpp ;
+
 run test_trigamma_nvrtc_double.cpp ;
 run test_trigamma_nvrtc_float.cpp ;
+
 run test_trunc_nvrtc_double.cpp ;
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index d0a458cce6..97c48474ca 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -25,6 +25,10 @@ run test_saspoint5.cpp ;
 # Special Functions
 run pow_test.cpp ;
 run test_beta_simple.cpp ;
+run test_bessel_i.cpp ;
+run test_bessel_j.cpp ;
+run test_bessel_k.cpp ;
+run test_bessel_y.cpp ;
 run test_cbrt.cpp ;
 run test_sign.cpp ;
 run test_round.cpp ;
diff --git a/test/test_bessel_i.cpp b/test/test_bessel_i.cpp
index 68dcab0a5d..70aac91e45 100644
--- a/test/test_bessel_i.cpp
+++ b/test/test_bessel_i.cpp
@@ -3,7 +3,13 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#else
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+#include <boost/math/tools/config.hpp>
+#endif
+
 #include "test_bessel_i.hpp"
 
 //
@@ -82,7 +88,11 @@ void expected_results()
       "linux",                       // platform
       largest_type,                  // test type(s)
       ".*Random.*",                    // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      ".*", 600, 200);
+      #else
       ".*", 400, 200);               // test function
+      #endif
 
    add_expected_result(
       "GNU.*",                       // compiler
@@ -111,7 +121,11 @@ void expected_results()
       ".*",                          // platform
       largest_type,                  // test type(s)
       ".*",                          // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      ".*", 400, 200);
+      #else
       ".*", 20, 10);                 // test function
+      #endif
    //
    // Set error rates a little higher for real_concept - 
    // now that we use a series approximation for small z
diff --git a/test/test_bessel_i.hpp b/test/test_bessel_i.hpp
index 2da559f320..aa4f6a4ea3 100644
--- a/test/test_bessel_i.hpp
+++ b/test/test_bessel_i.hpp
@@ -9,6 +9,7 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/bessel.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
@@ -180,7 +181,10 @@ void test_bessel(T, const char* name)
     //
     // Special cases for full coverage:
     //
+    #ifndef BOOST_MATH_NO_EXCEPTIONS
     BOOST_CHECK_THROW(boost::math::cyl_bessel_i(T(-2.5), T(-2.5)), std::domain_error);
+    #endif
+
     BOOST_CHECK_EQUAL(boost::math::cyl_bessel_i(T(0), T(0)), T(1));
     BOOST_CHECK_EQUAL(boost::math::cyl_bessel_i(T(10), T(0)), T(0));
     BOOST_CHECK_EQUAL(boost::math::cyl_bessel_i(T(-10), T(0)), T(0));
@@ -197,10 +201,12 @@ void test_bessel(T, const char* name)
        }
     }
     T tolerance = boost::math::tools::epsilon<T>() * 100;
+#ifndef SYCL_LANGUAGE_VERSION
     if ((boost::math::tools::digits<T>() <= std::numeric_limits<double>::digits) && (std::numeric_limits<T>::max_exponent > 1000))
     {
        BOOST_CHECK_CLOSE_FRACTION(boost::math::cyl_bessel_i(T(0.5), T(710)), SC_(3.3447452278080108123142599104927325061327359278058601201179e306), tolerance);
     }
+#endif
 #if LDBL_MAX_EXP >= 11356
     BOOST_IF_CONSTEXPR (std::numeric_limits<T>::max_exponent >= 11356)
     {
diff --git a/test/test_bessel_i0_double.cu b/test/test_bessel_i0_double.cu
new file mode 100644
index 0000000000..1c5d0ca14b
--- /dev/null
+++ b/test/test_bessel_i0_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_i0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_i0_float.cu b/test/test_bessel_i0_float.cu
new file mode 100644
index 0000000000..39929d5481
--- /dev/null
+++ b/test/test_bessel_i0_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_i0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_i0_nvrtc_double.cpp b/test/test_bessel_i0_nvrtc_double.cpp
new file mode 100644
index 0000000000..0c5db47b49
--- /dev/null
+++ b/test/test_bessel_i0_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_i0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_i0.hpp>
+extern "C" __global__ 
+void test_bessel_i0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_i0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_i0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_i0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_i0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_i0_nvrtc_float.cpp b/test/test_bessel_i0_nvrtc_float.cpp
new file mode 100644
index 0000000000..26d667b973
--- /dev/null
+++ b/test/test_bessel_i0_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_i0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_i0.hpp>
+extern "C" __global__ 
+void test_bessel_i0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_i0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_i0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_i0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_i0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_i1_double.cu b/test/test_bessel_i1_double.cu
new file mode 100644
index 0000000000..e4d6443a68
--- /dev/null
+++ b/test/test_bessel_i1_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_i1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_i1_float.cu b/test/test_bessel_i1_float.cu
new file mode 100644
index 0000000000..12ae535428
--- /dev/null
+++ b/test/test_bessel_i1_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_i1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_i1_nvrtc_double.cpp b/test/test_bessel_i1_nvrtc_double.cpp
new file mode 100644
index 0000000000..c270a66940
--- /dev/null
+++ b/test/test_bessel_i1_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_i1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_i1.hpp>
+extern "C" __global__ 
+void test_bessel_i1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_i1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_i1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_i1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_i1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_i1_nvrtc_float.cpp b/test/test_bessel_i1_nvrtc_float.cpp
new file mode 100644
index 0000000000..158c6a8159
--- /dev/null
+++ b/test/test_bessel_i1_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_i1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_i1.hpp>
+extern "C" __global__ 
+void test_bessel_i1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_i1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_i1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_i1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_i1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_i1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_j.cpp b/test/test_bessel_j.cpp
index 19a5f7426e..516e34c29a 100644
--- a/test/test_bessel_j.cpp
+++ b/test/test_bessel_j.cpp
@@ -3,7 +3,12 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#else
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+#include <boost/math/tools/config.hpp>
+#endif
 
 #include "test_bessel_j.hpp"
 
diff --git a/test/test_bessel_j.hpp b/test/test_bessel_j.hpp
index 82106213ea..c0b719ad89 100644
--- a/test/test_bessel_j.hpp
+++ b/test/test_bessel_j.hpp
@@ -9,6 +9,7 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/bessel.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
@@ -279,7 +280,9 @@ void test_bessel(T, const char* name)
     BOOST_MATH_CHECK_THROW(boost::math::sph_bessel(2, T(-2.0)), std::domain_error);
     BOOST_CHECK_EQUAL(boost::math::cyl_bessel_j(T(0), T(2.5)), boost::math::cyl_bessel_j(T(0), T(-2.5)));
     BOOST_CHECK_EQUAL(boost::math::cyl_bessel_j(T(1), T(2.5)), -boost::math::cyl_bessel_j(T(1), T(-2.5)));
+    #ifndef SYCL_LANGUAGE_VERSION
     BOOST_CHECK_CLOSE_FRACTION(boost::math::cyl_bessel_j(364, T(38.5)), SC_(1.793940496519190500748409872348034004417458734118663909894e-309), tolerance);
+    #endif
     //
     // Special cases at infinity:
     //
diff --git a/test/test_bessel_j0_double.cu b/test/test_bessel_j0_double.cu
new file mode 100644
index 0000000000..d32474d964
--- /dev/null
+++ b/test/test_bessel_j0_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_j0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_j0_float.cu b/test/test_bessel_j0_float.cu
new file mode 100644
index 0000000000..48c6b9e399
--- /dev/null
+++ b/test/test_bessel_j0_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_j0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_j0_nvrtc_double.cpp b/test/test_bessel_j0_nvrtc_double.cpp
new file mode 100644
index 0000000000..8c8b798410
--- /dev/null
+++ b/test/test_bessel_j0_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_j0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_j0.hpp>
+extern "C" __global__ 
+void test_bessel_j0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_j0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_j0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_j0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_j0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_j0_nvrtc_float.cpp b/test/test_bessel_j0_nvrtc_float.cpp
new file mode 100644
index 0000000000..4a54b1eaa8
--- /dev/null
+++ b/test/test_bessel_j0_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_j0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_j0.hpp>
+extern "C" __global__ 
+void test_bessel_j0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_j0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_j0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_j0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_j0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_j1_double.cu b/test/test_bessel_j1_double.cu
new file mode 100644
index 0000000000..33a6e71b6e
--- /dev/null
+++ b/test/test_bessel_j1_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_j1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_j1_float.cu b/test/test_bessel_j1_float.cu
new file mode 100644
index 0000000000..14dd37be31
--- /dev/null
+++ b/test/test_bessel_j1_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_j1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_j1_nvrtc_double.cpp b/test/test_bessel_j1_nvrtc_double.cpp
new file mode 100644
index 0000000000..11460c11da
--- /dev/null
+++ b/test/test_bessel_j1_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_j1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_j1.hpp>
+extern "C" __global__ 
+void test_bessel_j1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_j1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_j1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_j1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_j1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_j1_nvrtc_float.cpp b/test/test_bessel_j1_nvrtc_float.cpp
new file mode 100644
index 0000000000..8f7cc6e3fe
--- /dev/null
+++ b/test/test_bessel_j1_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_j1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_j1.hpp>
+extern "C" __global__ 
+void test_bessel_j1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_j1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_j1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_j1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_j1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_j1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_k.cpp b/test/test_bessel_k.cpp
index f0975b46d2..d4ab7721f4 100644
--- a/test/test_bessel_k.cpp
+++ b/test/test_bessel_k.cpp
@@ -5,7 +5,12 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#else
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+#include <boost/math/tools/config.hpp>
+#endif
 
 #ifdef _MSC_VER
 #  pragma warning(disable : 4756) // overflow in constant arithmetic
diff --git a/test/test_bessel_k.hpp b/test/test_bessel_k.hpp
index 22df3218f0..6a2a8179d9 100644
--- a/test/test_bessel_k.hpp
+++ b/test/test_bessel_k.hpp
@@ -9,6 +9,7 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/bessel.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
@@ -175,6 +176,7 @@ void test_bessel(T, const char* name)
     //
     // Extra test coverage:
     //
+    #ifndef SYCL_LANGUAGE_VERSION // SYCL doesn't throw 
     BOOST_CHECK_THROW(boost::math::cyl_bessel_k(T(2), T(-1)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::cyl_bessel_k(T(2.2), T(-1)), std::domain_error);
     BOOST_IF_CONSTEXPR(std::numeric_limits<T>::has_infinity)
@@ -194,6 +196,7 @@ void test_bessel(T, const char* name)
     BOOST_CHECK_THROW(boost::math::cyl_bessel_k(T(-1.25), T(0)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::cyl_bessel_k(T(-1), T(0)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::cyl_bessel_k(T(1), T(0)), std::domain_error);
+    #endif
 }
 
 
diff --git a/test/test_bessel_k0_double.cu b/test/test_bessel_k0_double.cu
new file mode 100644
index 0000000000..26d0e2bffa
--- /dev/null
+++ b/test/test_bessel_k0_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_k0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_k0_float.cu b/test/test_bessel_k0_float.cu
new file mode 100644
index 0000000000..ffe59c25bd
--- /dev/null
+++ b/test/test_bessel_k0_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k0(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_k0(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_k0_nvrtc_double.cpp b/test/test_bessel_k0_nvrtc_double.cpp
new file mode 100644
index 0000000000..d412212125
--- /dev/null
+++ b/test/test_bessel_k0_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_k0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_k0.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_k0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_k0_nvrtc_float.cpp b/test/test_bessel_k0_nvrtc_float.cpp
new file mode 100644
index 0000000000..389fce21a4
--- /dev/null
+++ b/test/test_bessel_k0_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_k0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_k0.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k0(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_k0(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_k1_double.cu b/test/test_bessel_k1_double.cu
new file mode 100644
index 0000000000..ed1b353d93
--- /dev/null
+++ b/test/test_bessel_k1_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_k1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_k1_float.cu b/test/test_bessel_k1_float.cu
new file mode 100644
index 0000000000..65fd802f22
--- /dev/null
+++ b/test/test_bessel_k1_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::detail::bessel_k1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_k1_nvrtc_double.cpp b/test/test_bessel_k1_nvrtc_double.cpp
new file mode 100644
index 0000000000..1e0f1e7f4b
--- /dev/null
+++ b/test/test_bessel_k1_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_k1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_k1.hpp>
+extern "C" __global__ 
+void test_bessel_k1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_k1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_k1_nvrtc_float.cpp b/test/test_bessel_k1_nvrtc_float.cpp
new file mode 100644
index 0000000000..1422a58869
--- /dev/null
+++ b/test/test_bessel_k1_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_k1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_k1.hpp>
+extern "C" __global__ 
+void test_bessel_k1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_k1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_k1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_kn_double.cu b/test/test_bessel_kn_double.cu
new file mode 100644
index 0000000000..d15ba73041
--- /dev/null
+++ b/test/test_bessel_kn_double.cu
@@ -0,0 +1,105 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_kn(2, in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    boost::math::policies::policy<> pol;
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_kn(2, input_vector[i], pol));
+    }
+
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_kn_float.cu b/test/test_bessel_kn_float.cu
new file mode 100644
index 0000000000..d15ba73041
--- /dev/null
+++ b/test/test_bessel_kn_float.cu
@@ -0,0 +1,105 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_kn(2, in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    boost::math::policies::policy<> pol;
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_kn(2, input_vector[i], pol));
+    }
+
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_kn_nvrtc_double.cpp b/test/test_bessel_kn_nvrtc_double.cpp
new file mode 100644
index 0000000000..3b581f77c3
--- /dev/null
+++ b/test/test_bessel_kn_nvrtc_double.cpp
@@ -0,0 +1,192 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_kn.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_kn.hpp>
+extern "C" __global__ 
+void test_bessel_kn_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_kn(2, in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_kn_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_kn_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_kn_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_kn(2, h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_kn_nvrtc_float.cpp b/test/test_bessel_kn_nvrtc_float.cpp
new file mode 100644
index 0000000000..dcc987a70a
--- /dev/null
+++ b/test/test_bessel_kn_nvrtc_float.cpp
@@ -0,0 +1,192 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/detail/bessel_kn.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/detail/bessel_kn.hpp>
+extern "C" __global__ 
+void test_bessel_kn_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_kn(2, in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_kn_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_kn_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_kn_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_kn(2, h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_y.cpp b/test/test_bessel_y.cpp
index 83c24b95f4..0bbefba55f 100644
--- a/test/test_bessel_y.cpp
+++ b/test/test_bessel_y.cpp
@@ -3,7 +3,12 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#else
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+#include <boost/math/tools/config.hpp>
+#endif
 
 #include "test_bessel_y.hpp"
 
@@ -234,7 +239,11 @@ void expected_results()
       ".*",                          // platform
       largest_type,                  // test type(s)
       ".*(Y[nv]|y).*Random.*",           // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      ".*", 2000, 1000);
+      #else
       ".*", 1500, 1000);               // test function
+      #endif
    //
    // Fallback for sun has to go after the general cases above:
    //
diff --git a/test/test_bessel_y.hpp b/test/test_bessel_y.hpp
index 28361a227c..14b0be4564 100644
--- a/test/test_bessel_y.hpp
+++ b/test/test_bessel_y.hpp
@@ -9,6 +9,7 @@
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/bessel.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
@@ -241,10 +242,12 @@ void test_bessel(T, const char* name)
        BOOST_CHECK_EQUAL(boost::math::sph_neumann(2, std::numeric_limits<T>::infinity()), T(0));
     }
 
+    #ifndef BOOST_MATH_NO_EXCEPTIONS
     BOOST_CHECK_THROW(boost::math::cyl_neumann(T(0), T(-1)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::cyl_neumann(T(0.2), T(-1)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::cyl_neumann(T(2), T(0)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::sph_neumann(2, T(-2)), std::domain_error);
+    #endif
 #if LDBL_MAX_EXP > 1024
     if (std::numeric_limits<T>::max_exponent > 1024)
     {
diff --git a/test/test_bessel_y0_double.cu b/test/test_bessel_y0_double.cu
new file mode 100644
index 0000000000..c8deada7d7
--- /dev/null
+++ b/test/test_bessel_y0_double.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y0(in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+
+    boost::math::policies::policy<> pol;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_y0(input_vector[i], pol));
+    }
+    
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_y0_float.cu b/test/test_bessel_y0_float.cu
new file mode 100644
index 0000000000..c8deada7d7
--- /dev/null
+++ b/test/test_bessel_y0_float.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y0(in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+
+    boost::math::policies::policy<> pol;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_y0(input_vector[i], pol));
+    }
+    
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_y0_nvrtc_double.cpp b/test/test_bessel_y0_nvrtc_double.cpp
new file mode 100644
index 0000000000..8645a0fdd0
--- /dev/null
+++ b/test/test_bessel_y0_nvrtc_double.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y0.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y0(in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_y0(h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_y0_nvrtc_float.cpp b/test/test_bessel_y0_nvrtc_float.cpp
new file mode 100644
index 0000000000..75a065bd6c
--- /dev/null
+++ b/test/test_bessel_y0_nvrtc_float.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y0.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y0.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y0(in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_y0(h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_y1_double.cu b/test/test_bessel_y1_double.cu
new file mode 100644
index 0000000000..a5b3051b40
--- /dev/null
+++ b/test/test_bessel_y1_double.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y1(in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+
+    boost::math::policies::policy<> pol;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_y1(input_vector[i], pol));
+    }
+    
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_y1_float.cu b/test/test_bessel_y1_float.cu
new file mode 100644
index 0000000000..532aaf328d
--- /dev/null
+++ b/test/test_bessel_y1_float.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y1(in[i], pol);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 1024;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+
+    boost::math::policies::policy<> pol;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(boost::math::detail::bessel_y1(input_vector[i], pol));
+    }
+    
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_bessel_y1_nvrtc_double.cpp b/test/test_bessel_y1_nvrtc_double.cpp
new file mode 100644
index 0000000000..383d879eb1
--- /dev/null
+++ b/test/test_bessel_y1_nvrtc_double.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y1.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y1(in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_y1(h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_bessel_y1_nvrtc_float.cpp b/test/test_bessel_y1_nvrtc_float.cpp
new file mode 100644
index 0000000000..c2c1355e64
--- /dev/null
+++ b/test/test_bessel_y1_nvrtc_float.cpp
@@ -0,0 +1,194 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/special_functions/detail/bessel_y1.hpp>
+extern "C" __global__ 
+void test_bessel_k0_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    boost::math::policies::policy<> pol;
+    if (i < numElements)
+    {
+        out[i] = boost::math::detail::bessel_y1(in1[i], pol);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_bessel_k0_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_bessel_k0_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_bessel_k0_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        boost::math::policies::policy<> pol;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::detail::bessel_y1(h_in1[i], pol);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_i_double.cu b/test/test_cyl_bessel_i_double.cu
new file mode 100644
index 0000000000..91a3ed8ebf
--- /dev/null
+++ b/test/test_cyl_bessel_i_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_i(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_i(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_i_float.cu b/test/test_cyl_bessel_i_float.cu
new file mode 100644
index 0000000000..5aad1be88b
--- /dev/null
+++ b/test/test_cyl_bessel_i_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_i(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_i(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_i_nvrtc_double.cpp b/test/test_cyl_bessel_i_nvrtc_double.cpp
new file mode 100644
index 0000000000..50bfc0c790
--- /dev/null
+++ b/test/test_cyl_bessel_i_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_i_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_i(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_i_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_i_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_i_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_i(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_i_nvrtc_float.cpp b/test/test_cyl_bessel_i_nvrtc_float.cpp
new file mode 100644
index 0000000000..c73992a27a
--- /dev/null
+++ b/test/test_cyl_bessel_i_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_i_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_i(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_i_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_i_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_i_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_i(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_j_double.cu b/test/test_cyl_bessel_j_double.cu
new file mode 100644
index 0000000000..b5d93f1ddb
--- /dev/null
+++ b/test/test_cyl_bessel_j_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_j(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_j(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_j_float.cu b/test/test_cyl_bessel_j_float.cu
new file mode 100644
index 0000000000..3edc2a7c9c
--- /dev/null
+++ b/test/test_cyl_bessel_j_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_j(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_j(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_j_nvrtc_double.cpp b/test/test_cyl_bessel_j_nvrtc_double.cpp
new file mode 100644
index 0000000000..f74e112edd
--- /dev/null
+++ b/test/test_cyl_bessel_j_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_j_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_j(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_j_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_j_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_j_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_j(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_j_nvrtc_float.cpp b/test/test_cyl_bessel_j_nvrtc_float.cpp
new file mode 100644
index 0000000000..e3d7928438
--- /dev/null
+++ b/test/test_cyl_bessel_j_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_j_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_j(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_j_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_j_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_j_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_j(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_k_double.cu b/test/test_cyl_bessel_k_double.cu
new file mode 100644
index 0000000000..3dfd2bf388
--- /dev/null
+++ b/test/test_cyl_bessel_k_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_k(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_k(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_k_float.cu b/test/test_cyl_bessel_k_float.cu
new file mode 100644
index 0000000000..b874857a05
--- /dev/null
+++ b/test/test_cyl_bessel_k_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_k(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_bessel_k(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_bessel_k_nvrtc_double.cpp b/test/test_cyl_bessel_k_nvrtc_double.cpp
new file mode 100644
index 0000000000..66a8b14900
--- /dev/null
+++ b/test/test_cyl_bessel_k_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_k_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_k(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_k_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_k_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_k_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_k(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_bessel_k_nvrtc_float.cpp b/test/test_cyl_bessel_k_nvrtc_float.cpp
new file mode 100644
index 0000000000..e23ff82c0d
--- /dev/null
+++ b/test/test_cyl_bessel_k_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_k_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_bessel_k(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_k_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_k_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_k_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_bessel_k(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_neumann_double.cu b/test/test_cyl_neumann_double.cu
new file mode 100644
index 0000000000..0e7a72ff98
--- /dev/null
+++ b/test/test_cyl_neumann_double.cu
@@ -0,0 +1,116 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_neumann(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_neumann(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(output_vector[i]) && std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000)
+            {
+                std::cout << "error at line: " << i
+                            << "\nParallel: " << results[i]
+                            << "\n  Serial: " << output_vector[i]
+                            << "\n    Dist: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_neumann_float.cu b/test/test_cyl_neumann_float.cu
new file mode 100644
index 0000000000..f621d2fc65
--- /dev/null
+++ b/test/test_cyl_neumann_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_neumann(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::cyl_neumann(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_neumann_nvrtc_double.cpp b/test/test_cyl_neumann_nvrtc_double.cpp
new file mode 100644
index 0000000000..78bbd3b5ca
--- /dev/null
+++ b/test/test_cyl_neumann_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_neumann_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_neumann(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_neumann_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_neumann_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_neumann_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_neumann(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_neumann_nvrtc_float.cpp b/test/test_cyl_neumann_nvrtc_float.cpp
new file mode 100644
index 0000000000..78bbd3b5ca
--- /dev/null
+++ b/test/test_cyl_neumann_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_neumann_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_neumann(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_neumann_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_neumann_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_neumann_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_neumann(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_bessel_double.cu b/test/test_sph_bessel_double.cu
new file mode 100644
index 0000000000..5229dd8b5e
--- /dev/null
+++ b/test/test_sph_bessel_double.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const unsigned *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_bessel(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<unsigned> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 rng {42};
+    std::uniform_int_distribution<unsigned> order(1, 100);
+    std::uniform_real_distribution<float_type> val(0, 100);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = order(rng);
+        input_vector2[i] = val(rng);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sph_bessel(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    bool failed = false;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(output_vector[i]) && std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 3000)
+            {
+                std::cout << "error at line: " << i
+                            << "\nParallel: " << results[i]
+                            << "\n  Serial: " << output_vector[i]
+                            << "\n    Dist: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_bessel_float.cu b/test/test_sph_bessel_float.cu
new file mode 100644
index 0000000000..bd068a1a01
--- /dev/null
+++ b/test/test_sph_bessel_float.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const unsigned *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_bessel(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<unsigned> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 rng {42};
+    std::uniform_int_distribution<unsigned> order(1, 100);
+    std::uniform_real_distribution<float_type> val(0, 100);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = order(rng);
+        input_vector2[i] = val(rng);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sph_bessel(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    bool failed = false;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(output_vector[i]) && std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 150)
+            {
+                std::cout << "error at line: " << i
+                            << "\nParallel: " << results[i]
+                            << "\n  Serial: " << output_vector[i]
+                            << "\n    Dist: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_bessel_nvrtc_double.cpp b/test/test_sph_bessel_nvrtc_double.cpp
new file mode 100644
index 0000000000..e88726ed71
--- /dev/null
+++ b/test/test_sph_bessel_nvrtc_double.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_j_kernel(const unsigned *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_bessel(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_j_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_j_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_j_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        unsigned *h_in1, *d_in1;
+        float_type *h_in2, *h_out;
+        float_type *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new unsigned[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_int_distribution<unsigned> order(1, 100);
+        std::uniform_real_distribution<float_type> val(0.0f, 100.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(order(rng));
+            h_in2[i] = static_cast<float_type>(val(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(unsigned)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(unsigned), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        bool failed = false;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_bessel(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 3000)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                    failed = true;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (failed)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_bessel_nvrtc_float.cpp b/test/test_sph_bessel_nvrtc_float.cpp
new file mode 100644
index 0000000000..c9538cd5bf
--- /dev/null
+++ b/test/test_sph_bessel_nvrtc_float.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_cyl_bessel_j_kernel(const unsigned *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_bessel(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_bessel_j_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_bessel_j_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_bessel_j_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        unsigned *h_in1, *d_in1;
+        float_type *h_in2, *h_out;
+        float_type *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new unsigned[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_int_distribution<unsigned> order(1, 100);
+        std::uniform_real_distribution<float_type> val(0.0f, 100.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(order(rng));
+            h_in2[i] = static_cast<float_type>(val(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(unsigned)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(unsigned), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        bool failed = false;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_bessel(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 3000)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                    failed = true;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (failed)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_neumann_double.cu b/test/test_sph_neumann_double.cu
new file mode 100644
index 0000000000..f59dc7acca
--- /dev/null
+++ b/test/test_sph_neumann_double.cu
@@ -0,0 +1,116 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_neumann(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sph_neumann(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(output_vector[i]) && std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000)
+            {
+                std::cout << "error at line: " << i
+                            << "\nParallel: " << results[i]
+                            << "\n  Serial: " << output_vector[i]
+                            << "\n    Dist: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_neumann_float.cu b/test/test_sph_neumann_float.cu
new file mode 100644
index 0000000000..a295e376f6
--- /dev/null
+++ b/test/test_sph_neumann_float.cu
@@ -0,0 +1,116 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_neumann(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::sph_neumann(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(output_vector[i]) && std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 5000)
+            {
+                std::cout << "error at line: " << i
+                            << "\nParallel: " << results[i]
+                            << "\n  Serial: " << output_vector[i]
+                            << "\n    Dist: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_neumann_nvrtc_double.cpp b/test/test_sph_neumann_nvrtc_double.cpp
new file mode 100644
index 0000000000..61dcb07ddc
--- /dev/null
+++ b/test/test_sph_neumann_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_sph_neumann_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_neumann(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_neumann_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_neumann_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_neumann_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_neumann(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_neumann_nvrtc_float.cpp b/test/test_sph_neumann_nvrtc_float.cpp
new file mode 100644
index 0000000000..5d7ae59fee
--- /dev/null
+++ b/test/test_sph_neumann_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/bessel.hpp>
+extern "C" __global__ 
+void test_sph_neumann_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_neumann(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_neumann_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_neumann_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_neumann_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_neumann(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 98622966ecbdf16897015080d90dce5b5a77710d Mon Sep 17 00:00:00 2001
From: dschmitz89 <danielschmitzsiegen@googlemail.com>
Date: Fri, 23 Aug 2024 20:34:35 +0200
Subject: [PATCH 361/399] DOC: fix Cauchy CDF formula

---
 doc/distributions/cauchy.qbk                          | 2 +-
 doc/html/math_toolkit/dist_ref/dists/cauchy_dist.html | 2 +-
 include/boost/math/distributions/cauchy.hpp           | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/doc/distributions/cauchy.qbk b/doc/distributions/cauchy.qbk
index 6ae090818a..2d388740a3 100644
--- a/doc/distributions/cauchy.qbk
+++ b/doc/distributions/cauchy.qbk
@@ -116,7 +116,7 @@ So recall that for `x < 0`:
 
 Substituting into the above we get:
 
-[expression p = -atan(1/x)  ; x < 0]
+[expression p = -atan(1/x) / [pi]  ; x < 0]
 
 So the procedure is to calculate the cdf for -fabs(x)
 using the above formula.  Note that to factor in the location and scale
diff --git a/doc/html/math_toolkit/dist_ref/dists/cauchy_dist.html b/doc/html/math_toolkit/dist_ref/dists/cauchy_dist.html
index c3562135a4..9d69b1e0d3 100644
--- a/doc/html/math_toolkit/dist_ref/dists/cauchy_dist.html
+++ b/doc/html/math_toolkit/dist_ref/dists/cauchy_dist.html
@@ -221,7 +221,7 @@ <h5>
                     Substituting into the above we get:
                   </p>
                   <div class="blockquote"><blockquote class="blockquote"><p>
-                      <span class="serif_italic">p = -atan(1/x) ; x &lt; 0</span>
+                      <span class="serif_italic">p = -atan(1/x)/π ; x &lt; 0</span>
                     </p></blockquote></div>
                   <p>
                     So the procedure is to calculate the cdf for -fabs(x) using the
diff --git a/include/boost/math/distributions/cauchy.hpp b/include/boost/math/distributions/cauchy.hpp
index 4cc93b260b..3a5af69e43 100644
--- a/include/boost/math/distributions/cauchy.hpp
+++ b/include/boost/math/distributions/cauchy.hpp
@@ -57,7 +57,7 @@ BOOST_MATH_GPU_ENABLED RealType cdf_imp(const cauchy_distribution<RealType, Poli
    //
    // Substituting into the above we get:
    //
-   // CDF = -atan(1/x)  ; x < 0
+   // CDF = -atan(1/x)/pi  ; x < 0
    //
    // So the procedure is to calculate the cdf for -fabs(x)
    // using the above formula, and then subtract from 1 when required

From e4a01104d0d9a53ddb560a959400e07e7679f314 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 27 Aug 2024 15:32:03 -0400
Subject: [PATCH 362/399] GPU Batch 7

Fix igamma_large support on device

Add GPU support to toms748

Add GPU support to igamma_inv

Add GPU markers to gamma_inva

Add GPU Markers to lgamma_small

Remove STL usage from gamma

Remove NVRTC workaround

Fix fraction use of STL headers

Mark gamma functions in fwd

Disable declval on all GPU platforms

Disable more unneeded code on device

Add forward decl for NVRTC tgamma

Disable unneeded items for all GPU

Change workaround for missing overloads

Rearrange definition location

Add include path to cuda now that workaround is removed

Fix NVRTC incompatibility with recursion and forward decls

Add tgamma_ratio CUDA and NVRTC testing

Fix NVRTC handling of gamma_p_derivative

Add gamma_p_derivative CUDA and NVRTC testing

Remove recursion from gamma_incomplete_imp

Add SYCL testing of igamma, igamma_inv, and igamma_inva

Ignore literal-range warnings

Remove use of static const char* for function name

Fix missing CUDA header

Remove calls under NVRTC to fwd decl

Add more nvrtc workarounds

Use builtin erfc instead of header cycle

Add CUDA and NVRTC testing of gamma_p_inv

Adjust tolerances

Add GPU support to chi squared dist

Fix static local variable

Add chi squared dist SYCL testing

Add chi squared dist CUDA testing

Add chi squared dist NVRTC testing

Add GPU support to weibull dist

Add weibull dist SYCL testing

Add weibull dist CUDA testing

Add weibull dist NVRTC testing
---
 .../boost/math/distributions/chi_squared.hpp  |  71 +--
 include/boost/math/distributions/weibull.hpp  |  89 +--
 include/boost/math/special_functions/beta.hpp |   8 +-
 .../special_functions/detail/gamma_inva.hpp   |  19 +-
 .../detail/igamma_inverse.hpp                 |  65 ++-
 .../special_functions/detail/igamma_large.hpp |  95 ++-
 .../special_functions/detail/lgamma_small.hpp |  15 +-
 .../boost/math/special_functions/gamma.hpp    | 551 ++++++++++++------
 .../boost/math/special_functions/log1p.hpp    |  64 +-
 .../boost/math/special_functions/math_fwd.hpp |  24 +-
 include/boost/math/tools/config.hpp           |   2 +
 include/boost/math/tools/fraction.hpp         |  33 +-
 include/boost/math/tools/precision.hpp        |   2 +-
 include/boost/math/tools/series.hpp           |   1 +
 include/boost/math/tools/toms748_solve.hpp    |  96 +--
 include/boost/math/tools/tuple.hpp            |   1 +
 test/cuda_jamfile                             |  20 +
 test/nvrtc_jamfile                            |  20 +
 test/sycl_jamfile                             |  16 +
 test/test_bessel_i.cpp                        |   8 +
 test/test_bessel_j.cpp                        |   8 +
 test/test_bessel_k.cpp                        |   8 +
 test/test_bessel_y.cpp                        |   8 +
 test/test_chi_squared.cpp                     |   6 +-
 test/test_chi_squared_cdf_double.cu           | 109 ++++
 test/test_chi_squared_cdf_float.cu            | 109 ++++
 test/test_chi_squared_cdf_nvrtc_double.cpp    | 191 ++++++
 test/test_chi_squared_cdf_nvrtc_float.cpp     | 191 ++++++
 test/test_chi_squared_pdf_double.cu           | 109 ++++
 test/test_chi_squared_pdf_float.cu            | 109 ++++
 test/test_chi_squared_pdf_nvrtc_double.cpp    | 191 ++++++
 test/test_chi_squared_pdf_nvrtc_float.cpp     | 191 ++++++
 test/test_chi_squared_quan_double.cu          | 109 ++++
 test/test_chi_squared_quan_float.cu           | 109 ++++
 test/test_chi_squared_quan_nvrtc_double.cpp   | 191 ++++++
 test/test_chi_squared_quan_nvrtc_float.cpp    | 191 ++++++
 test/test_gamma_nvrtc_double.cpp              |   4 +-
 test/test_gamma_nvrtc_float.cpp               |   2 +-
 test/test_gamma_p_derivative_double.cu        | 104 ++++
 test/test_gamma_p_derivative_float.cu         | 104 ++++
 test/test_gamma_p_derivative_nvrtc_double.cpp | 190 ++++++
 test/test_gamma_p_derivative_nvrtc_float.cpp  | 190 ++++++
 test/test_gamma_p_inv_double.cu               | 108 ++++
 test/test_gamma_p_inv_float.cu                | 107 ++++
 test/test_gamma_p_inv_nvrtc_double.cpp        | 190 ++++++
 test/test_gamma_p_inv_nvrtc_float.cpp         | 190 ++++++
 test/test_holtsmark.cpp                       |   8 +
 test/test_igamma.cpp                          |  11 +
 test/test_igamma.hpp                          |   3 +-
 test/test_igamma_inv.cpp                      |  19 +
 test/test_igamma_inv.hpp                      |   3 +-
 test/test_igamma_inva.cpp                     |  11 +
 test/test_igamma_inva.hpp                     |   3 +-
 test/test_landau.cpp                          |   8 +
 test/test_log1p_nvrtc_double.cpp              |   4 +-
 test/test_log1p_nvrtc_float.cpp               |  12 +-
 test/test_round.cpp                           |   5 +
 test/test_tgamma_ratio_double.cu              | 104 ++++
 test/test_tgamma_ratio_float.cu               | 104 ++++
 test/test_tgamma_ratio_nvrtc_double.cpp       | 190 ++++++
 test/test_tgamma_ratio_nvrtc_float.cpp        | 190 ++++++
 test/test_weibull.cpp                         |   6 +-
 test/test_weibull_cdf_double.cu               | 109 ++++
 test/test_weibull_cdf_float.cu                | 109 ++++
 test/test_weibull_cdf_nvrtc_double.cpp        | 191 ++++++
 test/test_weibull_cdf_nvrtc_float.cpp         | 191 ++++++
 test/test_weibull_pdf_double.cu               | 109 ++++
 test/test_weibull_pdf_float.cu                | 109 ++++
 test/test_weibull_pdf_nvrtc_double.cpp        | 191 ++++++
 test/test_weibull_pdf_nvrtc_float.cpp         | 191 ++++++
 test/test_weibull_quan_double.cu              | 109 ++++
 test/test_weibull_quan_float.cu               | 109 ++++
 test/test_weibull_quan_nvrtc_double.cpp       | 191 ++++++
 test/test_weibull_quan_nvrtc_float.cpp        | 191 ++++++
 74 files changed, 6233 insertions(+), 467 deletions(-)
 create mode 100644 test/test_chi_squared_cdf_double.cu
 create mode 100644 test/test_chi_squared_cdf_float.cu
 create mode 100644 test/test_chi_squared_cdf_nvrtc_double.cpp
 create mode 100644 test/test_chi_squared_cdf_nvrtc_float.cpp
 create mode 100644 test/test_chi_squared_pdf_double.cu
 create mode 100644 test/test_chi_squared_pdf_float.cu
 create mode 100644 test/test_chi_squared_pdf_nvrtc_double.cpp
 create mode 100644 test/test_chi_squared_pdf_nvrtc_float.cpp
 create mode 100644 test/test_chi_squared_quan_double.cu
 create mode 100644 test/test_chi_squared_quan_float.cu
 create mode 100644 test/test_chi_squared_quan_nvrtc_double.cpp
 create mode 100644 test/test_chi_squared_quan_nvrtc_float.cpp
 create mode 100644 test/test_gamma_p_derivative_double.cu
 create mode 100644 test/test_gamma_p_derivative_float.cu
 create mode 100644 test/test_gamma_p_derivative_nvrtc_double.cpp
 create mode 100644 test/test_gamma_p_derivative_nvrtc_float.cpp
 create mode 100644 test/test_gamma_p_inv_double.cu
 create mode 100644 test/test_gamma_p_inv_float.cu
 create mode 100644 test/test_gamma_p_inv_nvrtc_double.cpp
 create mode 100644 test/test_gamma_p_inv_nvrtc_float.cpp
 create mode 100644 test/test_tgamma_ratio_double.cu
 create mode 100644 test/test_tgamma_ratio_float.cu
 create mode 100644 test/test_tgamma_ratio_nvrtc_double.cpp
 create mode 100644 test/test_tgamma_ratio_nvrtc_float.cpp
 create mode 100644 test/test_weibull_cdf_double.cu
 create mode 100644 test/test_weibull_cdf_float.cu
 create mode 100644 test/test_weibull_cdf_nvrtc_double.cpp
 create mode 100644 test/test_weibull_cdf_nvrtc_float.cpp
 create mode 100644 test/test_weibull_pdf_double.cu
 create mode 100644 test/test_weibull_pdf_float.cu
 create mode 100644 test/test_weibull_pdf_nvrtc_double.cpp
 create mode 100644 test/test_weibull_pdf_nvrtc_float.cpp
 create mode 100644 test/test_weibull_quan_double.cu
 create mode 100644 test/test_weibull_quan_float.cu
 create mode 100644 test/test_weibull_quan_nvrtc_double.cpp
 create mode 100644 test/test_weibull_quan_nvrtc_float.cpp

diff --git a/include/boost/math/distributions/chi_squared.hpp b/include/boost/math/distributions/chi_squared.hpp
index f5daddc0ad..3944569e89 100644
--- a/include/boost/math/distributions/chi_squared.hpp
+++ b/include/boost/math/distributions/chi_squared.hpp
@@ -9,14 +9,17 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_CHI_SQUARED_HPP
 #define BOOST_MATH_DISTRIBUTIONS_CHI_SQUARED_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/toms748_solve.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp> // for incomplete beta.
 #include <boost/math/distributions/complement.hpp> // complements
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp>
 
-#include <utility>
-
 namespace boost{ namespace math{
 
 template <class RealType = double, class Policy = policies::policy<> >
@@ -26,20 +29,20 @@ class chi_squared_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit chi_squared_distribution(RealType i) : m_df(i)
+   BOOST_MATH_GPU_ENABLED explicit chi_squared_distribution(RealType i) : m_df(i)
    {
       RealType result;
       detail::check_df(
          "boost::math::chi_squared_distribution<%1%>::chi_squared_distribution", m_df, &result, Policy());
    } // chi_squared_distribution
 
-   RealType degrees_of_freedom()const
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const
    {
       return m_df;
    }
 
    // Parameter estimation:
-   static RealType find_degrees_of_freedom(
+   BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(
       RealType difference_from_variance,
       RealType alpha,
       RealType beta,
@@ -66,16 +69,16 @@ chi_squared_distribution(RealType)->chi_squared_distribution<typename boost::mat
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const chi_squared_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const chi_squared_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-    return std::pair<RealType, RealType>(static_cast<RealType>(0), std::numeric_limits<RealType>::infinity()); // 0 to + infinity.
+    return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), boost::math::numeric_limits<RealType>::infinity()); // 0 to + infinity.
   }
   else
   {
     using boost::math::tools::max_value;
-    return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + max.
+    return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + max.
   }
 }
 
@@ -84,21 +87,21 @@ inline std::pair<RealType, RealType> range(const chi_squared_distribution<RealTy
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const chi_squared_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const chi_squared_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), tools::max_value<RealType>()); // 0 to + infinity.
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), tools::max_value<RealType>()); // 0 to + infinity.
 }
 
 template <class RealType, class Policy>
-RealType pdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square)
+BOOST_MATH_GPU_ENABLED RealType pdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    RealType degrees_of_freedom = dist.degrees_of_freedom();
    // Error check:
    RealType error_result;
 
-   static const char* function = "boost::math::pdf(const chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const chi_squared_distribution<%1%>&, %1%)";
 
    if(false == detail::check_df(
          function, degrees_of_freedom, &error_result, Policy()))
@@ -132,12 +135,12 @@ RealType pdf(const chi_squared_distribution<RealType, Policy>& dist, const RealT
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const chi_squared_distribution<RealType, Policy>& dist, const RealType& chi_square)
 {
    RealType degrees_of_freedom = dist.degrees_of_freedom();
    // Error check:
    RealType error_result;
-   static const char* function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";
 
    if(false == detail::check_df(
          function, degrees_of_freedom, &error_result, Policy()))
@@ -153,10 +156,10 @@ inline RealType cdf(const chi_squared_distribution<RealType, Policy>& dist, cons
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
 {
    RealType degrees_of_freedom = dist.degrees_of_freedom();
-   static const char* function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false ==
@@ -170,11 +173,11 @@ inline RealType quantile(const chi_squared_distribution<RealType, Policy>& dist,
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c)
 {
    RealType const& degrees_of_freedom = c.dist.degrees_of_freedom();
    RealType const& chi_square = c.param;
-   static const char* function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false == detail::check_df(
@@ -191,11 +194,11 @@ inline RealType cdf(const complemented2_type<chi_squared_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<chi_squared_distribution<RealType, Policy>, RealType>& c)
 {
    RealType const& degrees_of_freedom = c.dist.degrees_of_freedom();
    RealType const& q = c.param;
-   static const char* function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false == (
@@ -208,22 +211,22 @@ inline RealType quantile(const complemented2_type<chi_squared_distribution<RealT
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const chi_squared_distribution<RealType, Policy>& dist)
 { // Mean of Chi-Squared distribution = v.
   return dist.degrees_of_freedom();
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const chi_squared_distribution<RealType, Policy>& dist)
 { // Variance of Chi-Squared distribution = 2v.
   return 2 * dist.degrees_of_freedom();
 } // variance
 
 template <class RealType, class Policy>
-inline RealType mode(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const chi_squared_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
-   static const char* function = "boost::math::mode(const chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mode(const chi_squared_distribution<%1%>&)";
 
    if(df < 2)
       return policies::raise_domain_error<RealType>(
@@ -234,7 +237,7 @@ inline RealType mode(const chi_squared_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const chi_squared_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING // For ADL
    RealType df = dist.degrees_of_freedom();
@@ -242,14 +245,14 @@ inline RealType skewness(const chi_squared_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const chi_squared_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
    return 3 + 12 / df;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const chi_squared_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
    return 12 / df;
@@ -264,12 +267,12 @@ namespace detail
 template <class RealType, class Policy>
 struct df_estimator
 {
-   df_estimator(RealType a, RealType b, RealType variance, RealType delta)
+   BOOST_MATH_GPU_ENABLED df_estimator(RealType a, RealType b, RealType variance, RealType delta)
       : alpha(a), beta(b), ratio(delta/variance)
    { // Constructor
    }
 
-   RealType operator()(const RealType& df)
+   BOOST_MATH_GPU_ENABLED RealType operator()(const RealType& df)
    {
       if(df <= tools::min_value<RealType>())
          return 1;
@@ -297,14 +300,14 @@ struct df_estimator
 } // namespace detail
 
 template <class RealType, class Policy>
-RealType chi_squared_distribution<RealType, Policy>::find_degrees_of_freedom(
+BOOST_MATH_GPU_ENABLED RealType chi_squared_distribution<RealType, Policy>::find_degrees_of_freedom(
    RealType difference_from_variance,
    RealType alpha,
    RealType beta,
    RealType variance,
    RealType hint)
 {
-   static const char* function = "boost::math::chi_squared_distribution<%1%>::find_degrees_of_freedom(%1%,%1%,%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::chi_squared_distribution<%1%>::find_degrees_of_freedom(%1%,%1%,%1%,%1%,%1%)";
    // Check for domain errors:
    RealType error_result;
    if(false ==
@@ -321,8 +324,8 @@ RealType chi_squared_distribution<RealType, Policy>::find_degrees_of_freedom(
 
    detail::df_estimator<RealType, Policy> f(alpha, beta, variance, difference_from_variance);
    tools::eps_tolerance<RealType> tol(policies::digits<RealType, Policy>());
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
-   std::pair<RealType, RealType> r =
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::pair<RealType, RealType> r =
      tools::bracket_and_solve_root(f, hint, RealType(2), false, tol, max_iter, Policy());
    RealType result = r.first + (r.second - r.first) / 2;
    if(max_iter >= policies::get_max_root_iterations<Policy>())
diff --git a/include/boost/math/distributions/weibull.hpp b/include/boost/math/distributions/weibull.hpp
index ca4bbd7b53..eb4de106c8 100644
--- a/include/boost/math/distributions/weibull.hpp
+++ b/include/boost/math/distributions/weibull.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -9,6 +10,10 @@
 // http://www.itl.nist.gov/div898/handbook/eda/section3/eda3668.htm
 // http://mathworld.wolfram.com/WeibullDistribution.html
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/log1p.hpp>
@@ -16,14 +21,12 @@
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 
-#include <utility>
-
 namespace boost{ namespace math
 {
 namespace detail{
 
 template <class RealType, class Policy>
-inline bool check_weibull_shape(
+BOOST_MATH_GPU_ENABLED inline bool check_weibull_shape(
       const char* function,
       RealType shape,
       RealType* result, const Policy& pol)
@@ -39,7 +42,7 @@ inline bool check_weibull_shape(
 }
 
 template <class RealType, class Policy>
-inline bool check_weibull_x(
+BOOST_MATH_GPU_ENABLED inline bool check_weibull_x(
       const char* function,
       RealType const& x,
       RealType* result, const Policy& pol)
@@ -55,7 +58,7 @@ inline bool check_weibull_x(
 }
 
 template <class RealType, class Policy>
-inline bool check_weibull(
+BOOST_MATH_GPU_ENABLED inline bool check_weibull(
       const char* function,
       RealType scale,
       RealType shape,
@@ -73,19 +76,19 @@ class weibull_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit weibull_distribution(RealType l_shape, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED explicit weibull_distribution(RealType l_shape, RealType l_scale = 1)
       : m_shape(l_shape), m_scale(l_scale)
    {
       RealType result;
       detail::check_weibull("boost::math::weibull_distribution<%1%>::weibull_distribution", l_scale, l_shape, &result, Policy());
    }
 
-   RealType shape()const
+   BOOST_MATH_GPU_ENABLED RealType shape()const
    {
       return m_shape;
    }
 
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_scale;
    }
@@ -107,28 +110,28 @@ weibull_distribution(RealType,RealType)->weibull_distribution<typename boost::ma
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const weibull_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const weibull_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const weibull_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const weibull_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
    using boost::math::tools::min_value;
-   return std::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
    // A discontinuity at x == 0, so only support down to min_value.
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::pdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -158,11 +161,11 @@ inline RealType pdf(const weibull_distribution<RealType, Policy>& dist, const Re
 }
 
 template <class RealType, class Policy>
-inline RealType logpdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::logpdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::logpdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -192,11 +195,11 @@ inline RealType logpdf(const weibull_distribution<RealType, Policy>& dist, const
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::cdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -213,11 +216,11 @@ inline RealType cdf(const weibull_distribution<RealType, Policy>& dist, const Re
 }
 
 template <class RealType, class Policy>
-inline RealType logcdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const weibull_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::logcdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -234,11 +237,11 @@ inline RealType logcdf(const weibull_distribution<RealType, Policy>& dist, const
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const weibull_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const weibull_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::quantile(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -258,11 +261,11 @@ inline RealType quantile(const weibull_distribution<RealType, Policy>& dist, con
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::cdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -279,11 +282,11 @@ inline RealType cdf(const complemented2_type<weibull_distribution<RealType, Poli
 }
 
 template <class RealType, class Policy>
-inline RealType logcdf(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::logcdf(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::logcdf(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -300,11 +303,11 @@ inline RealType logcdf(const complemented2_type<weibull_distribution<RealType, P
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<weibull_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const weibull_distribution<%1%>, %1%)";
+   constexpr auto function = "boost::math::quantile(const weibull_distribution<%1%>, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -325,11 +328,11 @@ inline RealType quantile(const complemented2_type<weibull_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const weibull_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::mean(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::mean(const weibull_distribution<%1%>)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -343,12 +346,12 @@ inline RealType mean(const weibull_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const weibull_distribution<RealType, Policy>& dist)
 {
    RealType shape = dist.shape();
    RealType scale = dist.scale();
 
-   static const char* function = "boost::math::variance(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::variance(const weibull_distribution<%1%>)";
 
    RealType result = 0;
    if(false == detail::check_weibull(function, scale, shape, &result, Policy()))
@@ -363,11 +366,11 @@ inline RealType variance(const weibull_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const weibull_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std function pow.
 
-   static const char* function = "boost::math::mode(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::mode(const weibull_distribution<%1%>)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -384,11 +387,11 @@ inline RealType mode(const weibull_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType median(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const weibull_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std function pow.
 
-   static const char* function = "boost::math::median(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::median(const weibull_distribution<%1%>)";
 
    RealType shape = dist.shape(); // Wikipedia k
    RealType scale = dist.scale(); // Wikipedia lambda
@@ -404,11 +407,11 @@ inline RealType median(const weibull_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const weibull_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::skewness(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::skewness(const weibull_distribution<%1%>)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -429,11 +432,11 @@ inline RealType skewness(const weibull_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const weibull_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::kurtosis_excess(const weibull_distribution<%1%>)";
+   constexpr auto function = "boost::math::kurtosis_excess(const weibull_distribution<%1%>)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -457,15 +460,15 @@ inline RealType kurtosis_excess(const weibull_distribution<RealType, Policy>& di
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const weibull_distribution<RealType, Policy>& dist)
 {
    return kurtosis_excess(dist) + 3;
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const weibull_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const weibull_distribution<RealType, Policy>& dist)
 {
-   using std::log;
+   BOOST_MATH_STD_USING
    RealType k = dist.shape();
    RealType lambda = dist.scale();
    return constants::euler<RealType>()*(1-1/k) + log(lambda/k) + 1;
diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index f0ac6318b5..00b8e45bf2 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -136,7 +136,7 @@ BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const Lanczos&, const Policy& pol)
 // Generic implementation of Beta(a,b) without Lanczos approximation support
 // (Caution this is slow!!!):
 //
-#ifndef BOOST_MATH_HAS_NVRTC
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T beta_imp(T a, T b, const lanczos::undefined_lanczos& l, const Policy& pol)
 {
@@ -461,7 +461,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
 //
 // This version is generic, slow, and does not use the Lanczos approximation.
 //
-#ifndef BOOST_MATH_HAS_NVRTC
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_power_terms(T a,
                         T b,
@@ -741,7 +741,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const Lanczos&, bool
 //
 // Incomplete Beta series again, this time without Lanczos support:
 //
-#ifndef BOOST_MATH_HAS_NVRTC
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::lanczos::undefined_lanczos& l, bool normalised, T* p_derivative, T y, const Policy& pol)
 {
@@ -958,7 +958,7 @@ struct Pn_size<long double>
 #endif
 };
 
-#ifndef BOOST_MATH_HAS_NVRTC
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& pol, bool normalised)
 {
diff --git a/include/boost/math/special_functions/detail/gamma_inva.hpp b/include/boost/math/special_functions/detail/gamma_inva.hpp
index 75ac89e433..61c64a6486 100644
--- a/include/boost/math/special_functions/detail/gamma_inva.hpp
+++ b/include/boost/math/special_functions/detail/gamma_inva.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -17,7 +18,7 @@
 #pragma once
 #endif
 
-#include <cstdint>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/toms748_solve.hpp>
 
 namespace boost{ namespace math{ namespace detail{
@@ -25,8 +26,8 @@ namespace boost{ namespace math{ namespace detail{
 template <class T, class Policy>
 struct gamma_inva_t
 {
-   gamma_inva_t(T z_, T p_, bool invert_) : z(z_), p(p_), invert(invert_) {}
-   T operator()(T a)
+   BOOST_MATH_GPU_ENABLED gamma_inva_t(T z_, T p_, bool invert_) : z(z_), p(p_), invert(invert_) {}
+   BOOST_MATH_GPU_ENABLED T operator()(T a)
    {
       return invert ? p - boost::math::gamma_q(a, z, Policy()) : boost::math::gamma_p(a, z, Policy()) - p;
    }
@@ -36,7 +37,7 @@ struct gamma_inva_t
 };
 
 template <class T, class Policy>
-T inverse_poisson_cornish_fisher(T lambda, T p, T q, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T inverse_poisson_cornish_fisher(T lambda, T p, T q, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    // mean:
@@ -67,7 +68,7 @@ T inverse_poisson_cornish_fisher(T lambda, T p, T q, const Policy& pol)
 }
 
 template <class T, class Policy>
-T gamma_inva_imp(const T& z, const T& p, const T& q, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T gamma_inva_imp(const T& z, const T& p, const T& q, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // for ADL of std lib math functions
    //
@@ -151,7 +152,7 @@ T gamma_inva_imp(const T& z, const T& p, const T& q, const Policy& pol)
 } // namespace detail
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_p_inva(T1 x, T2 p, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -181,7 +182,7 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_q_inva(T1 x, T2 q, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -211,14 +212,14 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_p_inva(T1 x, T2 p)
 {
    return boost::math::gamma_p_inva(x, p, policies::policy<>());
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_q_inva(T1 x, T2 q)
 {
    return boost::math::gamma_q_inva(x, q, policies::policy<>());
diff --git a/include/boost/math/special_functions/detail/igamma_inverse.hpp b/include/boost/math/special_functions/detail/igamma_inverse.hpp
index f6bbcd72d5..4efd4f78a3 100644
--- a/include/boost/math/special_functions/detail/igamma_inverse.hpp
+++ b/include/boost/math/special_functions/detail/igamma_inverse.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,8 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/sign.hpp>
@@ -21,7 +24,7 @@ namespace boost{ namespace math{
 namespace detail{
 
 template <class T>
-T find_inverse_s(T p, T q)
+BOOST_MATH_GPU_ENABLED T find_inverse_s(T p, T q)
 {
    //
    // Computation of the Incomplete Gamma Function Ratios and their Inverse
@@ -41,8 +44,8 @@ T find_inverse_s(T p, T q)
    {
       t = sqrt(-2 * log(q));
    }
-   static const double a[4] = { 3.31125922108741, 11.6616720288968, 4.28342155967104, 0.213623493715853 };
-   static const double b[5] = { 1, 6.61053765625462, 6.40691597760039, 1.27364489782223, 0.3611708101884203e-1 };
+   BOOST_MATH_STATIC const double a[4] = { 3.31125922108741, 11.6616720288968, 4.28342155967104, 0.213623493715853 };
+   BOOST_MATH_STATIC const double b[5] = { 1, 6.61053765625462, 6.40691597760039, 1.27364489782223, 0.3611708101884203e-1 };
    T s = t - tools::evaluate_polynomial(a, t) / tools::evaluate_polynomial(b, t);
    if(p < T(0.5))
       s = -s;
@@ -50,7 +53,7 @@ T find_inverse_s(T p, T q)
 }
 
 template <class T>
-T didonato_SN(T a, T x, unsigned N, T tolerance = 0)
+BOOST_MATH_GPU_ENABLED T didonato_SN(T a, T x, unsigned N, T tolerance = 0)
 {
    //
    // Computation of the Incomplete Gamma Function Ratios and their Inverse
@@ -77,7 +80,7 @@ T didonato_SN(T a, T x, unsigned N, T tolerance = 0)
 }
 
 template <class T, class Policy>
-inline T didonato_FN(T p, T a, T x, unsigned N, T tolerance, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T didonato_FN(T p, T a, T x, unsigned N, T tolerance, const Policy& pol)
 {
    //
    // Computation of the Incomplete Gamma Function Ratios and their Inverse
@@ -93,7 +96,7 @@ inline T didonato_FN(T p, T a, T x, unsigned N, T tolerance, const Policy& pol)
 }
 
 template <class T, class Policy>
-T find_inverse_gamma(T a, T p, T q, const Policy& pol, bool* p_has_10_digits)
+BOOST_MATH_GPU_ENABLED T find_inverse_gamma(T a, T p, T q, const Policy& pol, bool* p_has_10_digits)
 {
    //
    // In order to understand what's going on here, you will
@@ -233,7 +236,7 @@ T find_inverse_gamma(T a, T p, T q, const Policy& pol, bool* p_has_10_digits)
          }
          else
          {
-            T D = (std::max)(T(2), T(a * (a - 1)));
+            T D = BOOST_MATH_GPU_SAFE_MAX(T(2), T(a * (a - 1)));
             T lg = boost::math::lgamma(a, pol);
             T lb = log(q) + lg;
             if(lb < -D * T(2.3))
@@ -315,7 +318,7 @@ T find_inverse_gamma(T a, T p, T q, const Policy& pol, bool* p_has_10_digits)
 template <class T, class Policy>
 struct gamma_p_inverse_func
 {
-   gamma_p_inverse_func(T a_, T p_, bool inv) : a(a_), p(p_), invert(inv)
+   BOOST_MATH_GPU_ENABLED gamma_p_inverse_func(T a_, T p_, bool inv) : a(a_), p(p_), invert(inv)
    {
       //
       // If p is too near 1 then P(x) - p suffers from cancellation
@@ -333,7 +336,7 @@ struct gamma_p_inverse_func
       }
    }
 
-   boost::math::tuple<T, T, T> operator()(const T& x)const
+   BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T, T> operator()(const T& x)const
    {
       BOOST_FPU_EXCEPTION_GUARD
       //
@@ -395,11 +398,11 @@ struct gamma_p_inverse_func
 };
 
 template <class T, class Policy>
-T gamma_p_inv_imp(T a, T p, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T gamma_p_inv_imp(T a, T p, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // ADL of std functions.
 
-   static const char* function = "boost::math::gamma_p_inv<%1%>(%1%, %1%)";
+   constexpr auto function = "boost::math::gamma_p_inv<%1%>(%1%, %1%)";
 
    BOOST_MATH_INSTRUMENT_VARIABLE(a);
    BOOST_MATH_INSTRUMENT_VARIABLE(p);
@@ -442,7 +445,9 @@ T gamma_p_inv_imp(T a, T p, const Policy& pol)
    //
    // Go ahead and iterate:
    //
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    guess = tools::halley_iterate(
       detail::gamma_p_inverse_func<T, Policy>(a, p, false),
       guess,
@@ -450,6 +455,16 @@ T gamma_p_inv_imp(T a, T p, const Policy& pol)
       tools::max_value<T>(),
       digits,
       max_iter);
+   #else
+   guess = tools::newton_raphson_iterate(
+      detail::gamma_p_inverse_func<T, Policy>(a, p, false),
+      guess,
+      lower,
+      tools::max_value<T>(),
+      digits,
+      max_iter);
+   #endif
+   
    policies::check_root_iterations<T>(function, max_iter, pol);
    BOOST_MATH_INSTRUMENT_VARIABLE(guess);
    if(guess == lower)
@@ -458,11 +473,11 @@ T gamma_p_inv_imp(T a, T p, const Policy& pol)
 }
 
 template <class T, class Policy>
-T gamma_q_inv_imp(T a, T q, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T gamma_q_inv_imp(T a, T q, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // ADL of std functions.
 
-   static const char* function = "boost::math::gamma_q_inv<%1%>(%1%, %1%)";
+   constexpr auto function = "boost::math::gamma_q_inv<%1%>(%1%, %1%)";
 
    if(a <= 0)
       return policies::raise_domain_error<T>(function, "Argument a in the incomplete gamma function inverse must be >= 0 (got a=%1%).", a, pol);
@@ -501,7 +516,9 @@ T gamma_q_inv_imp(T a, T q, const Policy& pol)
    //
    // Go ahead and iterate:
    //
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    guess = tools::halley_iterate(
       detail::gamma_p_inverse_func<T, Policy>(a, q, true),
       guess,
@@ -509,6 +526,16 @@ T gamma_q_inv_imp(T a, T q, const Policy& pol)
       tools::max_value<T>(),
       digits,
       max_iter);
+   #else
+   guess = tools::newton_raphson_iterate(
+      detail::gamma_p_inverse_func<T, Policy>(a, q, true),
+      guess,
+      lower,
+      tools::max_value<T>(),
+      digits,
+      max_iter);
+   #endif
+
    policies::check_root_iterations<T>(function, max_iter, pol);
    if(guess == lower)
       guess = policies::raise_underflow_error<T>(function, "Expected result known to be non-zero, but is smaller than the smallest available number.", pol);
@@ -518,7 +545,7 @@ T gamma_q_inv_imp(T a, T q, const Policy& pol)
 } // namespace detail
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_p_inv(T1 a, T2 p, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -528,7 +555,7 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_q_inv(T1 a, T2 p, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -538,14 +565,14 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_p_inv(T1 a, T2 p)
 {
    return gamma_p_inv(a, p, policies::policy<>());
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type
    gamma_q_inv(T1 a, T2 p)
 {
    return gamma_q_inv(a, p, policies::policy<>());
diff --git a/include/boost/math/special_functions/detail/igamma_large.hpp b/include/boost/math/special_functions/detail/igamma_large.hpp
index 1fa13c6921..8e0ad1b0dd 100644
--- a/include/boost/math/special_functions/detail/igamma_large.hpp
+++ b/include/boost/math/special_functions/detail/igamma_large.hpp
@@ -61,6 +61,7 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
@@ -68,7 +69,7 @@ namespace boost{ namespace math{ namespace detail{
 // when T is unsuitable to be passed to these routines:
 //
 template <class T, class Policy>
-inline T igamma_temme_large(T, T, const Policy& /* pol */, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED inline T igamma_temme_large(T, T, const Policy& /* pol */, const boost::math::integral_constant<int, 0>&)
 {
    // stub function, should never actually be called
    BOOST_MATH_ASSERT(0);
@@ -78,8 +79,11 @@ inline T igamma_temme_large(T, T, const Policy& /* pol */, const std::integral_c
 // This version is accurate for up to 64-bit mantissa's, 
 // (80-bit long double, or 10^-20).
 //
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const boost::math::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -91,7 +95,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 
    T workspace[13];
 
-   static const T C0[] = {
+   BOOST_MATH_STATIC const T C0[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.333333333333333333333),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.0833333333333333333333),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.0148148148148148148148),
@@ -114,7 +118,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[0] = tools::evaluate_polynomial(C0, z);
 
-   static const T C1[] = {
+   BOOST_MATH_STATIC const T C1[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00185185185185185185185),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00347222222222222222222),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00264550264550264550265),
@@ -135,7 +139,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[1] = tools::evaluate_polynomial(C1, z);
 
-   static const T C2[] = {
+   BOOST_MATH_STATIC const T C2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00413359788359788359788),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00268132716049382716049),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000771604938271604938272),
@@ -154,7 +158,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[2] = tools::evaluate_polynomial(C2, z);
 
-   static const T C3[] = {
+   BOOST_MATH_STATIC const T C3[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000649434156378600823045),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000229472093621399176955),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000469189494395255712128),
@@ -171,7 +175,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[3] = tools::evaluate_polynomial(C3, z);
 
-   static const T C4[] = {
+   BOOST_MATH_STATIC const T C4[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000861888290916711698605),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000784039221720066627474),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000299072480303190179733),
@@ -186,7 +190,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[4] = tools::evaluate_polynomial(C4, z);
 
-   static const T C5[] = {
+   BOOST_MATH_STATIC const T C5[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000336798553366358150309),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.697281375836585777429e-4),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000277275324495939207873),
@@ -199,7 +203,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[5] = tools::evaluate_polynomial(C5, z);
 
-   static const T C6[] = {
+   BOOST_MATH_STATIC const T C6[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000531307936463992223166),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000592166437353693882865),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000270878209671804482771),
@@ -214,7 +218,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[6] = tools::evaluate_polynomial(C6, z);
 
-   static const T C7[] = {
+   BOOST_MATH_STATIC const T C7[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000344367606892377671254),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.517179090826059219337e-4),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000334931610811422363117),
@@ -227,7 +231,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[7] = tools::evaluate_polynomial(C7, z);
 
-   static const T C8[] = {
+   BOOST_MATH_STATIC const T C8[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000652623918595309418922),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000839498720672087279993),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000438297098541721005061),
@@ -238,7 +242,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[8] = tools::evaluate_polynomial(C8, z);
 
-   static const T C9[] = {
+   BOOST_MATH_STATIC const T C9[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.000596761290192746250124),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.720489541602001055909e-4),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000678230883766732836162),
@@ -247,14 +251,14 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[9] = tools::evaluate_polynomial(C9, z);
 
-   static const T C10[] = {
+   BOOST_MATH_STATIC const T C10[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00133244544948006563713),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.0019144384985654775265),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00110893691345966373396),
    };
    workspace[10] = tools::evaluate_polynomial(C10, z);
 
-   static const T C11[] = {
+   BOOST_MATH_STATIC const T C11[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00157972766073083495909),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.000162516262783915816899),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00206334210355432762645),
@@ -263,7 +267,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[11] = tools::evaluate_polynomial(C11, z);
 
-   static const T C12[] = {
+   BOOST_MATH_STATIC const T C12[] = {
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00407251211951401664727),
       BOOST_MATH_BIG_CONSTANT(T, 64, 0.00640336283380806979482),
       BOOST_MATH_BIG_CONSTANT(T, 64, -0.00404101610816766177474),
@@ -279,12 +283,15 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 
    return result;
 }
+
+#endif
+
 //
 // This one is accurate for 53-bit mantissa's
 // (IEEE double precision or 10^-17).
 //
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const boost::math::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -417,7 +424,18 @@ BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const s
    if(x < a)
       result = -result;
 
+   #ifdef BOOST_MATH_HAS_NVRTC
+   if (boost::math::is_same_v<T, float>)
+   {
+      result += ::erfcf(::sqrtf(y)) / 2;
+   }
+   else
+   {
+      result += ::erfc(::sqrt(y)) / 2;
+   }
+   #else
    result += boost::math::erfc(sqrt(y), pol) / 2;
+   #endif
 
    return result;
 }
@@ -426,7 +444,7 @@ BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const s
 // (IEEE float precision, or 10^-8)
 //
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const boost::math::integral_constant<int, 24>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -470,7 +488,18 @@ BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const s
    if(x < a)
       result = -result;
 
+   #ifdef BOOST_MATH_HAS_NVRTC
+   if (boost::math::is_same_v<T, float>)
+   {
+      result += ::erfcf(::sqrtf(y)) / 2;
+   }
+   else
+   {
+      result += ::erfc(::sqrt(y)) / 2;
+   }
+   #else
    result += boost::math::erfc(sqrt(y), pol) / 2;
+   #endif
 
    return result;
 }
@@ -481,8 +510,10 @@ BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const s
 // It's use for a < 200 is not recommended, that would
 // require many more terms in the polynomials.
 //
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T, class Policy>
-T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T igamma_temme_large(T a, T x, const Policy& pol, const boost::math::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING // ADL of std functions
    T sigma = (x - a) / a;
@@ -494,7 +525,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
 
    T workspace[14];
 
-   static const T C0[] = {
+   BOOST_MATH_STATIC const T C0[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.333333333333333333333333333333333333),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.0833333333333333333333333333333333333),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.0148148148148148148148148148148148148),
@@ -529,7 +560,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[0] = tools::evaluate_polynomial(C0, z);
 
-   static const T C1[] = {
+   BOOST_MATH_STATIC const T C1[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00185185185185185185185185185185185185),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00347222222222222222222222222222222222),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.0026455026455026455026455026455026455),
@@ -562,7 +593,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[1] = tools::evaluate_polynomial(C1, z);
 
-   static const T C2[] = {
+   BOOST_MATH_STATIC const T C2[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.0041335978835978835978835978835978836),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00268132716049382716049382716049382716),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000771604938271604938271604938271604938),
@@ -593,7 +624,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[2] = tools::evaluate_polynomial(C2, z);
 
-   static const T C3[] = {
+   BOOST_MATH_STATIC const T C3[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000649434156378600823045267489711934156),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000229472093621399176954732510288065844),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000469189494395255712128140111679206329),
@@ -622,7 +653,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[3] = tools::evaluate_polynomial(C3, z);
 
-   static const T C4[] = {
+   BOOST_MATH_STATIC const T C4[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000861888290916711698604702719929057378),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00078403922172006662747403488144228885),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000299072480303190179733389609932819809),
@@ -649,7 +680,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[4] = tools::evaluate_polynomial(C4, z);
 
-   static const T C5[] = {
+   BOOST_MATH_STATIC const T C5[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000336798553366358150308767592718210002),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.697281375836585777429398828575783308e-4),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00027727532449593920787336425196507501),
@@ -670,7 +701,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[5] = tools::evaluate_polynomial(C5, z);
 
-   static const T C6[] = {
+   BOOST_MATH_STATIC const T C6[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00053130793646399222316574854297762391),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000592166437353693882864836225604401187),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000270878209671804482771279183488328692),
@@ -689,7 +720,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[6] = tools::evaluate_polynomial(C6, z);
 
-   static const T C7[] = {
+   BOOST_MATH_STATIC const T C7[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000344367606892377671254279625108523655),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.517179090826059219337057843002058823e-4),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000334931610811422363116635090580012327),
@@ -706,7 +737,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[7] = tools::evaluate_polynomial(C7, z);
 
-   static const T C8[] = {
+   BOOST_MATH_STATIC const T C8[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000652623918595309418922034919726622692),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000839498720672087279993357516764983445),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000438297098541721005061087953050560377),
@@ -721,7 +752,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[8] = tools::evaluate_polynomial(C8, z);
 
-   static const T C9[] = {
+   BOOST_MATH_STATIC const T C9[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.000596761290192746250124390067179459605),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.720489541602001055908571930225015052e-4),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000678230883766732836161951166000673426),
@@ -734,7 +765,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[9] = tools::evaluate_polynomial(C9, z);
 
-   static const T C10[] = {
+   BOOST_MATH_STATIC const T C10[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00133244544948006563712694993432717968),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00191443849856547752650089885832852254),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.0011089369134596637339607446329267522),
@@ -745,7 +776,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[10] = tools::evaluate_polynomial(C10, z);
 
-   static const T C11[] = {
+   BOOST_MATH_STATIC const T C11[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00157972766073083495908785631307733022),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.000162516262783915816898635123980270998),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00206334210355432762645284467690276817),
@@ -754,7 +785,7 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    };
    workspace[11] = tools::evaluate_polynomial(C11, z);
 
-   static const T C12[] = {
+   BOOST_MATH_STATIC const T C12[] = {
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00407251211951401664727281097914544601),
       BOOST_MATH_BIG_CONSTANT(T, 113, 0.00640336283380806979482363809026579583),
       BOOST_MATH_BIG_CONSTANT(T, 113, -0.00404101610816766177473974858518094879),
@@ -772,6 +803,8 @@ T igamma_temme_large(T a, T x, const Policy& pol, const std::integral_constant<i
    return result;
 }
 
+#endif
+
 }  // namespace detail
 }  // namespace math
 }  // namespace math
diff --git a/include/boost/math/special_functions/detail/lgamma_small.hpp b/include/boost/math/special_functions/detail/lgamma_small.hpp
index d9fa88b8ed..1ce52fac30 100644
--- a/include/boost/math/special_functions/detail/lgamma_small.hpp
+++ b/include/boost/math/special_functions/detail/lgamma_small.hpp
@@ -13,6 +13,9 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/big_constant.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/special_functions/lanczos.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -32,13 +35,13 @@ namespace boost{ namespace math{ namespace detail{
 template <class T, class Policy, class Lanczos>
 BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const Lanczos& l);
 template <class T, class Policy>
-T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos& l);
+BOOST_MATH_GPU_ENABLED T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos& l);
 
 //
 // lgamma for small arguments:
 //
 template <class T, class Policy, class Lanczos>
-BOOST_MATH_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
+BOOST_MATH_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const boost::math::integral_constant<int, 64>&, const Policy& /* l */, const Lanczos&)
 {
    // This version uses rational approximations for small
    // values of z accurate enough for 64-bit mantissas
@@ -226,8 +229,10 @@ BOOST_MATH_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const std::integral
    }
    return result;
 }
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy, class Lanczos>
-T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 113>&, const Policy& /* l */, const Lanczos&)
+T lgamma_small_imp(T z, T zm1, T zm2, const boost::math::integral_constant<int, 113>&, const Policy& /* l */, const Lanczos&)
 {
    //
    // This version uses rational approximations for small
@@ -484,7 +489,7 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 113>&, c
    return result;
 }
 template <class T, class Policy, class Lanczos>
-T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 0>&, const Policy& pol, const Lanczos& l)
+BOOST_MATH_GPU_ENABLED T lgamma_small_imp(T z, T zm1, T zm2, const boost::math::integral_constant<int, 0>&, const Policy& pol, const Lanczos& l)
 {
    //
    // No rational approximations are available because either
@@ -528,6 +533,8 @@ T lgamma_small_imp(T z, T zm1, T zm2, const std::integral_constant<int, 0>&, con
    return result;
 }
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 }}} // namespaces
 
 #endif // BOOST_MATH_SPECIAL_FUNCTIONS_DETAIL_LGAMMA_SMALL
diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 9268ba4156..186befb612 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -15,14 +15,13 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-
-#ifndef BOOST_MATH_HAS_NVRTC
-
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/fraction.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/promotion.hpp>
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/tools/assert.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
@@ -36,12 +35,12 @@
 #include <boost/math/special_functions/detail/igamma_large.hpp>
 #include <boost/math/special_functions/detail/unchecked_factorial.hpp>
 #include <boost/math/special_functions/detail/lgamma_small.hpp>
+
+// Only needed for types larger than double
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #include <boost/math/special_functions/bernoulli.hpp>
 #include <boost/math/special_functions/polygamma.hpp>
-
-#include <cmath>
-#include <algorithm>
-#include <type_traits>
+#endif
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -60,13 +59,13 @@ namespace boost{ namespace math{
 namespace detail{
 
 template <class T>
-BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const std::true_type&)
+BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const boost::math::true_type&)
 {
    int i = static_cast<int>(v);
    return i&1;
 }
 template <class T>
-BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const boost::math::false_type&)
 {
    // Oh dear can't cast T to int!
    BOOST_MATH_STD_USING
@@ -76,7 +75,7 @@ BOOST_MATH_GPU_ENABLED inline bool is_odd(T v, const std::false_type&)
 template <class T>
 BOOST_MATH_GPU_ENABLED inline bool is_odd(T v)
 {
-   return is_odd(v, ::std::is_convertible<T, int>());
+   return is_odd(v, ::boost::math::is_convertible<T, int>());
 }
 
 template <class T>
@@ -208,7 +207,7 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol
       result = -boost::math::constants::pi<T>() / result;
       if(result == 0)
          return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
-      if((boost::math::fpclassify)(result) == (int)FP_SUBNORMAL)
+      if((boost::math::fpclassify)(result) == (int)BOOST_MATH_FP_SUBNORMAL)
          return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
       BOOST_MATH_INSTRUMENT_VARIABLE(result);
       return result;
@@ -259,7 +258,7 @@ BOOST_MATH_GPU_ENABLED T lgamma_imp_final(T z, const Policy& pol, const Lanczos&
    else if(z < 15)
    {
       typedef typename policies::precision<T, Policy>::type precision_type;
-      typedef std::integral_constant<int,
+      typedef boost::math::integral_constant<int,
          precision_type::value <= 0 ? 0 :
          precision_type::value <= 64 ? 64 :
          precision_type::value <= 113 ? 113 : 0
@@ -267,7 +266,7 @@ BOOST_MATH_GPU_ENABLED T lgamma_imp_final(T z, const Policy& pol, const Lanczos&
 
       result = lgamma_small_imp<T>(z, T(z - 1), T(z - 2), tag_type(), pol, l);
    }
-   else if((z >= 3) && (z < 100) && (std::numeric_limits<T>::max_exponent >= 1024))
+   else if((z >= 3) && (z < 100) && (boost::math::numeric_limits<T>::max_exponent >= 1024))
    {
       // taking the log of tgamma reduces the error, no danger of overflow here:
       result = log(gamma_imp(z, pol, l));
@@ -349,7 +348,7 @@ struct upper_incomplete_gamma_fract
    T z, a;
    int k;
 public:
-   typedef std::pair<T,T> result_type;
+   typedef boost::math::pair<T,T> result_type;
 
    BOOST_MATH_GPU_ENABLED upper_incomplete_gamma_fract(T a1, T z1)
       : z(z1-a1+1), a(a1), k(0)
@@ -399,26 +398,28 @@ BOOST_MATH_GPU_ENABLED inline T lower_gamma_series(T a, T z, const Policy& pol,
    // lower incomplete integral. Then divide by tgamma(a)
    // to get the normalised value.
    lower_incomplete_gamma_series<T> s(a, z);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    T factor = policies::get_epsilon<T, Policy>();
    T result = boost::math::tools::sum_series(s, factor, max_iter, init_value);
    policies::check_series_iterations<T>("boost::math::detail::lower_gamma_series<%1%>(%1%)", max_iter, pol);
    return result;
 }
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 //
 // Fully generic tgamma and lgamma use Stirling's approximation
 // with Bernoulli numbers.
 //
 template<class T>
-std::size_t highest_bernoulli_index()
+boost::math::size_t highest_bernoulli_index()
 {
-   const float digits10_of_type = (std::numeric_limits<T>::is_specialized
-                                      ? static_cast<float>(std::numeric_limits<T>::digits10)
+   const float digits10_of_type = (boost::math::numeric_limits<T>::is_specialized
+                                      ? static_cast<float>(boost::math::numeric_limits<T>::digits10)
                                       : static_cast<float>(boost::math::tools::digits<T>() * 0.301F));
 
    // Find the high index n for Bn to produce the desired precision in Stirling's calculation.
-   return static_cast<std::size_t>(18.0F + (0.6F * digits10_of_type));
+   return static_cast<boost::math::size_t>(18.0F + (0.6F * digits10_of_type));
 }
 
 template<class T>
@@ -426,8 +427,8 @@ int minimum_argument_for_bernoulli_recursion()
 {
    BOOST_MATH_STD_USING
 
-   const float digits10_of_type = (std::numeric_limits<T>::is_specialized
-                                    ? (float) std::numeric_limits<T>::digits10
+   const float digits10_of_type = (boost::math::numeric_limits<T>::is_specialized
+                                    ? (float) boost::math::numeric_limits<T>::digits10
                                     : (float) (boost::math::tools::digits<T>() * 0.301F));
 
    int min_arg = (int) (digits10_of_type * 1.7F);
@@ -449,7 +450,7 @@ int minimum_argument_for_bernoulli_recursion()
       const float d2_minus_one = ((digits10_of_type / 0.301F) - 1.0F);
       const float limit        = ceil(exp((d2_minus_one * log(2.0F)) / 20.0F));
 
-      min_arg = (int) ((std::min)(digits10_of_type * 1.7F, limit));
+      min_arg = (int) (BOOST_MATH_GPU_SAFE_MIN(digits10_of_type * 1.7F, limit));
    }
 
    return min_arg;
@@ -468,7 +469,7 @@ T scaled_tgamma_no_lanczos(const T& z, const Policy& pol, bool islog = false)
 
    // Perform the Bernoulli series expansion of Stirling's approximation.
 
-   const std::size_t number_of_bernoullis_b2n = policies::get_max_series_iterations<Policy>();
+   const boost::math::size_t number_of_bernoullis_b2n = policies::get_max_series_iterations<Policy>();
 
    T one_over_x_pow_two_n_minus_one = 1 / z;
    const T one_over_x2 = one_over_x_pow_two_n_minus_one * one_over_x_pow_two_n_minus_one;
@@ -477,11 +478,11 @@ T scaled_tgamma_no_lanczos(const T& z, const Policy& pol, bool islog = false)
    const T half_ln_two_pi_over_z = sqrt(boost::math::constants::two_pi<T>() / z);
    T last_term = 2 * sum;
 
-   for (std::size_t n = 2U;; ++n)
+   for (boost::math::size_t n = 2U;; ++n)
    {
       one_over_x_pow_two_n_minus_one *= one_over_x2;
 
-      const std::size_t n2 = static_cast<std::size_t>(n * 2U);
+      const boost::math::size_t n2 = static_cast<boost::math::size_t>(n * 2U);
 
       const T term = (boost::math::bernoulli_b2n<T>(static_cast<int>(n)) * one_over_x_pow_two_n_minus_one) / (n2 * (n2 - 1U));
 
@@ -629,7 +630,7 @@ T gamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&)
       if(gamma_value == 0)
          return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
 
-      if((boost::math::fpclassify)(gamma_value) == static_cast<int>(FP_SUBNORMAL))
+      if((boost::math::fpclassify)(gamma_value) == static_cast<int>(BOOST_MATH_FP_SUBNORMAL))
          return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", gamma_value, pol);
    }
 
@@ -775,6 +776,21 @@ T lgamma_imp(T z, const Policy& pol, const lanczos::undefined_lanczos&, int* sig
    return log_gamma_value;
 }
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
+// In order for tgammap1m1_imp to compile we need a forward decl of boost::math::tgamma
+// The rub is that we can't just use math_fwd so we provide one here only in that circumstance
+#ifdef BOOST_MATH_HAS_NVRTC
+template <class RT>
+BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT> tgamma(RT z);
+
+template <class RT1, class RT2>
+BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z);
+
+template <class RT1, class RT2, class Policy>
+BOOST_MATH_GPU_ENABLED tools::promote_args_t<RT1, RT2> tgamma(RT1 a, RT2 z, const Policy& pol);
+#endif
+
 //
 // This helper calculates tgamma(dz+1)-1 without cancellation errors,
 // used by the upper incomplete gamma with z < 1:
@@ -786,7 +802,7 @@ BOOST_MATH_GPU_ENABLED T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos&
 
    typedef typename policies::precision<T,Policy>::type precision_type;
 
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 64 ? 64 :
       precision_type::value <= 113 ? 113 : 0
@@ -798,7 +814,11 @@ BOOST_MATH_GPU_ENABLED T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos&
       if(dz < T(-0.5))
       {
          // Best method is simply to subtract 1 from tgamma:
+         #ifdef BOOST_MATH_HAS_NVRTC
+         result = ::tgamma(1+dz);
+         #else
          result = boost::math::tgamma(1+dz, pol) - 1;
+         #endif
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
       else
@@ -820,7 +840,11 @@ BOOST_MATH_GPU_ENABLED T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos&
       else
       {
          // Best method is simply to subtract 1 from tgamma:
+         #ifdef BOOST_MATH_HAS_NVRTC
+         result = ::tgamma(1+dz);
+         #else
          result = boost::math::tgamma(1+dz, pol) - 1;
+         #endif
          BOOST_MATH_INSTRUMENT_CODE(result);
       }
    }
@@ -828,6 +852,8 @@ BOOST_MATH_GPU_ENABLED T tgammap1m1_imp(T dz, Policy const& pol, const Lanczos&
    return result;
 }
 
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T, class Policy>
 inline T tgammap1m1_imp(T z, Policy const& pol,
                  const ::boost::math::lanczos::undefined_lanczos&)
@@ -841,6 +867,8 @@ inline T tgammap1m1_imp(T z, Policy const& pol,
    return boost::math::expm1(boost::math::lgamma(1 + z, pol));
 }
 
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 //
 // Series representation for upper fraction when z is small:
 //
@@ -914,7 +942,7 @@ BOOST_MATH_GPU_ENABLED T full_igamma_prefix(T a, T z, const Policy& pol)
    // This error handling isn't very good: it happens after the fact
    // rather than before it...
    //
-   if((boost::math::fpclassify)(prefix) == (int)FP_INFINITE)
+   if((boost::math::fpclassify)(prefix) == (int)BOOST_MATH_FP_INFINITE)
       return policies::raise_overflow_error<T>("boost::math::detail::full_igamma_prefix<%1%>(%1%, %1%)", "Result of incomplete gamma function is too large to represent.", pol);
 
    return prefix;
@@ -971,16 +999,16 @@ BOOST_MATH_GPU_ENABLED T regularised_gamma_prefix(T a, T z, const Policy& pol, c
       //
       T alz = a * log(z / agh);
       T amz = a - z;
-      if(((std::min)(alz, amz) <= tools::log_min_value<T>()) || ((std::max)(alz, amz) >= tools::log_max_value<T>()))
+      if((BOOST_MATH_GPU_SAFE_MIN(alz, amz) <= tools::log_min_value<T>()) || (BOOST_MATH_GPU_SAFE_MAX(alz, amz) >= tools::log_max_value<T>()))
       {
          T amza = amz / a;
-         if(((std::min)(alz, amz)/2 > tools::log_min_value<T>()) && ((std::max)(alz, amz)/2 < tools::log_max_value<T>()))
+         if((BOOST_MATH_GPU_SAFE_MIN(alz, amz)/2 > tools::log_min_value<T>()) && (BOOST_MATH_GPU_SAFE_MAX(alz, amz)/2 < tools::log_max_value<T>()))
          {
             // compute square root of the result and then square it:
             T sq = pow(z / agh, a / 2) * exp(amz / 2);
             prefix = sq * sq;
          }
-         else if(((std::min)(alz, amz)/4 > tools::log_min_value<T>()) && ((std::max)(alz, amz)/4 < tools::log_max_value<T>()) && (z > a))
+         else if((BOOST_MATH_GPU_SAFE_MIN(alz, amz)/4 > tools::log_min_value<T>()) && (BOOST_MATH_GPU_SAFE_MAX(alz, amz)/4 < tools::log_max_value<T>()) && (z > a))
          {
             // compute the 4th root of the result then square it twice:
             T sq = pow(z / agh, a / 4) * exp(amz / 4);
@@ -1004,6 +1032,9 @@ BOOST_MATH_GPU_ENABLED T regularised_gamma_prefix(T a, T z, const Policy& pol, c
    prefix *= sqrt(agh / boost::math::constants::e<T>()) / Lanczos::lanczos_sum_expG_scaled(a);
    return prefix;
 }
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 //
 // And again, without Lanczos support:
 //
@@ -1073,6 +1104,9 @@ T regularised_gamma_prefix(T a, T z, const Policy& pol, const lanczos::undefined
       }
    }
 }
+
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
 //
 // Upper gamma fraction for very small a:
 //
@@ -1084,7 +1118,14 @@ BOOST_MATH_GPU_ENABLED inline T tgamma_small_upper_part(T a, T x, const Policy&
    // Compute the full upper fraction (Q) when a is very small:
    //
 
+   #ifdef BOOST_MATH_HAS_NVRTC
+   typedef typename tools::promote_args<T>::type result_type;
+   typedef typename policies::evaluation<result_type, Policy>::type value_type;
+   typedef typename lanczos::lanczos<value_type, Policy>::type evaluation_type;
+   T result {detail::tgammap1m1_imp(static_cast<value_type>(a), pol, evaluation_type())};
+   #else
    T result { boost::math::tgamma1pm1(a, pol) };
+   #endif
 
    if(pgam)
       *pgam = (result + 1) / a;
@@ -1092,7 +1133,7 @@ BOOST_MATH_GPU_ENABLED inline T tgamma_small_upper_part(T a, T x, const Policy&
    result -= p;
    result /= a;
    detail::small_gamma2_series<T> s(a, x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>() - 10;
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>() - 10;
    p += 1;
    if(pderivative)
       *pderivative = p / (*pgam * exp(x));
@@ -1141,7 +1182,21 @@ BOOST_MATH_GPU_ENABLED T finite_half_gamma_q(T a, T x, T* p_derivative, const Po
    // Calculates normalised Q when a is a half-integer:
    //
    BOOST_MATH_STD_USING
+
+   #ifdef BOOST_MATH_HAS_NVRTC
+   T e;
+   if (boost::math::is_same_v<T, float>)
+   {
+      e = ::erfcf(::sqrtf(x));
+   }
+   else
+   {
+      e = ::erfc(::sqrt(x));
+   }
+   #else
    T e = boost::math::erfc(sqrt(x), pol);
+   #endif
+
    if((e != 0) && (a > 1))
    {
       T term = exp(-x) / sqrt(constants::pi<T>() * x);
@@ -1192,7 +1247,7 @@ BOOST_MATH_GPU_ENABLED T incomplete_tgamma_large_x(const T& a, const T& x, const
 {
    BOOST_MATH_STD_USING
    incomplete_tgamma_large_x_series<T> s(a, x);
-   std::uintmax_t max_iter = boost::math::policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = boost::math::policies::get_max_series_iterations<Policy>();
    T result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<T, Policy>(), max_iter);
    boost::math::policies::check_series_iterations<T>("boost::math::tgamma<%1%>(%1%,%1%)", max_iter, pol);
    return result;
@@ -1203,7 +1258,7 @@ BOOST_MATH_GPU_ENABLED T incomplete_tgamma_large_x(const T& a, const T& x, const
 // Main incomplete gamma entry point, handles all four incomplete gamma's:
 //
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
+BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp_final(T a, T x, bool normalised, bool invert,
                        const Policy& pol, T* p_derivative)
 {
    constexpr auto function = "boost::math::gamma_p<%1%>(%1%, %1%)";
@@ -1218,70 +1273,6 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
 
    T result = 0; // Just to avoid warning C4701: potentially uninitialized local variable 'result' used
 
-   if(a >= max_factorial<T>::value && !normalised)
-   {
-      //
-      // When we're computing the non-normalized incomplete gamma
-      // and a is large the result is rather hard to compute unless
-      // we use logs.  There are really two options - if x is a long
-      // way from a in value then we can reliably use methods 2 and 4
-      // below in logarithmic form and go straight to the result.
-      // Otherwise we let the regularized gamma take the strain
-      // (the result is unlikely to underflow in the central region anyway)
-      // and combine with lgamma in the hopes that we get a finite result.
-      //
-      if(invert && (a * 4 < x))
-      {
-         // This is method 4 below, done in logs:
-         result = a * log(x) - x;
-         if(p_derivative)
-            *p_derivative = exp(result);
-         result += log(upper_gamma_fraction(a, x, policies::get_epsilon<T, Policy>()));
-      }
-      else if(!invert && (a > 4 * x))
-      {
-         // This is method 2 below, done in logs:
-         result = a * log(x) - x;
-         if(p_derivative)
-            *p_derivative = exp(result);
-         T init_value = 0;
-         result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
-      }
-      else
-      {
-         result = gamma_incomplete_imp(a, x, true, invert, pol, p_derivative);
-         if(result == 0)
-         {
-            if(invert)
-            {
-               // Try http://functions.wolfram.com/06.06.06.0039.01
-               result = 1 + 1 / (12 * a) + 1 / (288 * a * a);
-               result = log(result) - a + (a - 0.5f) * log(a) + log(boost::math::constants::root_two_pi<T>());
-               if(p_derivative)
-                  *p_derivative = exp(a * log(x) - x);
-            }
-            else
-            {
-               // This is method 2 below, done in logs, we're really outside the
-               // range of this method, but since the result is almost certainly
-               // infinite, we should probably be OK:
-               result = a * log(x) - x;
-               if(p_derivative)
-                  *p_derivative = exp(result);
-               T init_value = 0;
-               result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
-            }
-         }
-         else
-         {
-            result = log(result) + boost::math::lgamma(a, pol);
-         }
-      }
-      if(result > tools::log_max_value<T>())
-         return policies::raise_overflow_error<T>(function, nullptr, pol);
-      return exp(result);
-   }
-
    BOOST_MATH_ASSERT((p_derivative == nullptr) || normalised);
 
    bool is_int, is_half_int;
@@ -1357,7 +1348,7 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
       // series and continued fractions are slow to converge:
       //
       bool use_temme = false;
-      if(normalised && std::numeric_limits<T>::is_specialized && (a > 20))
+      if(normalised && boost::math::numeric_limits<T>::is_specialized && (a > 20))
       {
          T sigma = fabs((x-a)/a);
          if((a > 200) && (policies::digits<T, Policy>() <= 113))
@@ -1414,14 +1405,40 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
       {
          result = finite_gamma_q(a, x, pol, p_derivative);
          if(!normalised)
+         {
+            #ifdef BOOST_MATH_HAS_NVRTC
+            if (boost::math::is_same_v<T, float>)
+            {
+               result *= ::tgammaf(a);
+            }
+            else
+            {
+               result *= ::tgamma(a);
+            }
+            #else
             result *= boost::math::tgamma(a, pol);
+            #endif
+         }
          break;
       }
    case 1:
       {
          result = finite_half_gamma_q(a, x, p_derivative, pol);
          if(!normalised)
+         {
+            #ifdef BOOST_MATH_HAS_NVRTC
+            if (boost::math::is_same_v<T, float>)
+            {
+               result *= ::tgammaf(a);
+            }
+            else
+            {
+               result *= ::tgamma(a);
+            }
+            #else
             result *= boost::math::tgamma(a, pol);
+            #endif
+         }
          if(p_derivative && (*p_derivative == 0))
             *p_derivative = regularised_gamma_prefix(a, x, pol, lanczos_type());
          break;
@@ -1450,7 +1467,19 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
             bool optimised_invert = false;
             if(invert)
             {
+               #ifdef BOOST_MATH_HAS_NVRTC
+               if (boost::math::is_same_v<T, float>)
+               {
+                  init_value = (normalised ? 1 : ::tgammaf(a));
+               }
+               else
+               {
+                  init_value = (normalised ? 1 : ::tgamma(a));
+               }
+               #else
                init_value = (normalised ? 1 : boost::math::tgamma(a, pol));
+               #endif
+
                if(normalised || (result >= 1) || (tools::max_value<T>() * result > init_value))
                {
                   init_value /= result;
@@ -1507,7 +1536,7 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
          //
          typedef typename policies::precision<T, Policy>::type precision_type;
 
-         typedef std::integral_constant<int,
+         typedef boost::math::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 53 ? 53 :
             precision_type::value <= 64 ? 64 :
@@ -1533,7 +1562,18 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
             try
             {
 #endif
+               #ifdef BOOST_MATH_HAS_NVRTC
+               if (boost::math::is_same_v<T, float>)
+               {
+                  result = ::powf(x, a) / ::tgammaf(a + 1);
+               }
+               else
+               {
+                  result = ::pow(x, a) / ::tgamma(a + 1);
+               }
+               #else
                result = pow(x, a) / boost::math::tgamma(a + 1, pol);
+               #endif
 #ifndef BOOST_MATH_NO_EXCEPTIONS
             }
             catch (const std::overflow_error&)
@@ -1565,7 +1605,19 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
       result = 1;
    if(invert)
    {
+      #ifdef BOOST_MATH_HAS_NVRTC
+      T gam;
+      if (boost::math::is_same_v<T, float>)
+      {
+         gam = normalised ? 1 : ::tgammaf(a);
+      }
+      else
+      {
+         gam = normalised ? 1 : ::tgamma(a);
+      }
+      #else
       T gam = normalised ? 1 : boost::math::tgamma(a, pol);
+      #endif
       result = gam - result;
    }
    if(p_derivative)
@@ -1585,6 +1637,101 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
    return result;
 }
 
+// Need to implement this dispatch to avoid recursion for device compilers
+template <class T, class Policy>
+BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool invert,
+                       const Policy& pol, T* p_derivative)
+{
+   constexpr auto function = "boost::math::gamma_p<%1%>(%1%, %1%)";
+   if(a <= 0)
+      return policies::raise_domain_error<T>(function, "Argument a to the incomplete gamma function must be greater than zero (got a=%1%).", a, pol);
+   if(x < 0)
+      return policies::raise_domain_error<T>(function, "Argument x to the incomplete gamma function must be >= 0 (got x=%1%).", x, pol);
+
+   BOOST_MATH_STD_USING
+
+
+   T result = 0; // Just to avoid warning C4701: potentially uninitialized local variable 'result' used
+
+   if(a >= max_factorial<T>::value && !normalised)
+   {
+      //
+      // When we're computing the non-normalized incomplete gamma
+      // and a is large the result is rather hard to compute unless
+      // we use logs.  There are really two options - if x is a long
+      // way from a in value then we can reliably use methods 2 and 4
+      // below in logarithmic form and go straight to the result.
+      // Otherwise we let the regularized gamma take the strain
+      // (the result is unlikely to underflow in the central region anyway)
+      // and combine with lgamma in the hopes that we get a finite result.
+      //
+      if(invert && (a * 4 < x))
+      {
+         // This is method 4 below, done in logs:
+         result = a * log(x) - x;
+         if(p_derivative)
+            *p_derivative = exp(result);
+         result += log(upper_gamma_fraction(a, x, policies::get_epsilon<T, Policy>()));
+      }
+      else if(!invert && (a > 4 * x))
+      {
+         // This is method 2 below, done in logs:
+         result = a * log(x) - x;
+         if(p_derivative)
+            *p_derivative = exp(result);
+         T init_value = 0;
+         result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
+      }
+      else
+      {
+         result = gamma_incomplete_imp_final(T(a), T(x), true, invert, pol, p_derivative);
+         if(result == 0)
+         {
+            if(invert)
+            {
+               // Try http://functions.wolfram.com/06.06.06.0039.01
+               result = 1 + 1 / (12 * a) + 1 / (288 * a * a);
+               result = log(result) - a + (a - 0.5f) * log(a) + log(boost::math::constants::root_two_pi<T>());
+               if(p_derivative)
+                  *p_derivative = exp(a * log(x) - x);
+            }
+            else
+            {
+               // This is method 2 below, done in logs, we're really outside the
+               // range of this method, but since the result is almost certainly
+               // infinite, we should probably be OK:
+               result = a * log(x) - x;
+               if(p_derivative)
+                  *p_derivative = exp(result);
+               T init_value = 0;
+               result += log(detail::lower_gamma_series(a, x, pol, init_value) / a);
+            }
+         }
+         else
+         {
+            #ifdef BOOST_MATH_HAS_NVRTC
+            if (boost::math::is_same_v<T, float>)
+            {
+               result = ::logf(result) + ::lgammaf(a);
+            }
+            else
+            {
+               result = ::log(result) + ::lgamma(a);
+            }
+            #else
+            result = log(result) + boost::math::lgamma(a, pol);
+            #endif
+         }
+      }
+      if(result > tools::log_max_value<T>())
+         return policies::raise_overflow_error<T>(function, nullptr, pol);
+      return exp(result);
+   }
+
+   // If no special handling is required then we proceeds as normal
+   return gamma_incomplete_imp_final(T(a), T(x), normalised, invert, pol, p_derivative);
+}
+
 //
 // Ratios of two gamma functions:
 //
@@ -1612,7 +1759,18 @@ BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Poli
       }
       else
       {
+         #ifdef BOOST_MATH_HAS_NVRTC
+         if (boost::math::is_same_v<T, float>)
+         {
+            return 1 / (z * ::tgammaf(z + delta));
+         }
+         else
+         {
+            return 1 / (z * ::tgamma(z + delta));
+         }
+         #else
          return 1 / (z * boost::math::tgamma(z + delta, pol));
+         #endif
       }
    }
    T zgh = static_cast<T>(z + T(Lanczos::g()) - constants::half<T>());
@@ -1651,6 +1809,8 @@ BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Poli
 //
 // And again without Lanczos support this time:
 //
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
 template <class T, class Policy>
 T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const lanczos::undefined_lanczos& l)
 {
@@ -1707,6 +1867,8 @@ T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const lanczos:
    return ratio;
 }
 
+#endif
+
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
 {
@@ -1715,7 +1877,18 @@ BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp(T z, T delta, const Policy& pol)
    if((z <= 0) || (z + delta <= 0))
    {
       // This isn't very sophisticated, or accurate, but it does work:
+      #ifdef BOOST_MATH_HAS_NVRTC
+      if (boost::math::is_same_v<T, float>)
+      {
+         return ::tgammaf(z) / ::tgammaf(z + delta);
+      }
+      else
+      {
+         return ::tgamma(z) / ::tgamma(z + delta);
+      }
+      #else
       return boost::math::tgamma(z, pol) / boost::math::tgamma(z + delta, pol);
+      #endif
    }
 
    if(floor(delta) == delta)
@@ -1775,17 +1948,32 @@ BOOST_MATH_GPU_ENABLED T tgamma_ratio_imp(T x, T y, const Policy& pol)
    if((y <= 0) || (boost::math::isinf)(y))
       return policies::raise_domain_error<T>("boost::math::tgamma_ratio<%1%>(%1%, %1%)", "Gamma function ratios only implemented for positive arguments (got b=%1%).", y, pol);
 
+   // We don't need to worry about the denorm case on device
+   // And this has the added bonus of removing recursion
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    if(x <= tools::min_value<T>())
    {
       // Special case for denorms...Ugh.
       T shift = ldexp(T(1), tools::digits<T>());
       return shift * tgamma_ratio_imp(T(x * shift), y, pol);
    }
+   #endif
 
    if((x < max_factorial<T>::value) && (y < max_factorial<T>::value))
    {
       // Rather than subtracting values, lets just call the gamma functions directly:
+      #ifdef BOOST_MATH_HAS_NVRTC
+      if (boost::math::is_same_v<T, float>)
+      {
+         return ::tgammaf(x) / ::tgammaf(y);
+      }
+      else
+      {
+         return ::tgamma(x) / ::tgamma(y);
+      }
+      #else
       return boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
+      #endif
    }
    T prefix = 1;
    if(x < 1)
@@ -1801,12 +1989,35 @@ BOOST_MATH_GPU_ENABLED T tgamma_ratio_imp(T x, T y, const Policy& pol)
             y -= 1;
             prefix /= y;
          }
+
+         #ifdef BOOST_MATH_HAS_NVRTC
+         if (boost::math::is_same_v<T, float>)
+         {
+            return prefix * ::tgammaf(x) / ::tgammaf(y);
+         }
+         else
+         {
+            return prefix * ::tgamma(x) / ::tgamma(y);
+         }
+         #else
          return prefix * boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
+         #endif
       }
       //
       // result is almost certainly going to underflow to zero, try logs just in case:
       //
+      #ifdef BOOST_MATH_HAS_NVRTC
+      if (boost::math::is_same_v<T, float>)
+      {
+         return ::expf(::lgammaf(x) - ::lgammaf(y));
+      }
+      else
+      {
+         return ::exp(::lgamma(x) - ::lgamma(y));
+      }
+      #else
       return exp(boost::math::lgamma(x, pol) - boost::math::lgamma(y, pol));
+      #endif
    }
    if(y < 1)
    {
@@ -1821,17 +2032,44 @@ BOOST_MATH_GPU_ENABLED T tgamma_ratio_imp(T x, T y, const Policy& pol)
             x -= 1;
             prefix *= x;
          }
+
+         #ifdef BOOST_MATH_HAS_NVRTC
+         if (boost::math::is_same_v<T, float>)
+         {
+            return prefix * ::tgammaf(x) / ::tgammaf(y);
+         }
+         else
+         {
+            return prefix * ::tgamma(x) / ::tgamma(y);
+         }
+         #else
          return prefix * boost::math::tgamma(x, pol) / boost::math::tgamma(y, pol);
+         #endif
       }
       //
       // Result will almost certainly overflow, try logs just in case:
       //
+      #ifdef BOOST_MATH_HAS_NVRTC
+      if (boost::math::is_same_v<T, float>)
+      {
+         return ::expf(::lgammaf(x) - ::lgammaf(y));
+      }
+      else
+      {
+         return ::exp(::lgamma(x) - ::lgamma(y));
+      }
+      #else
       return exp(boost::math::lgamma(x, pol) - boost::math::lgamma(y, pol));
+      #endif
    }
    //
    // Regular case, x and y both large and similar in magnitude:
    //
+   #ifdef BOOST_MATH_HAS_NVRTC
+   return detail::tgamma_delta_ratio_imp(x, y - x, pol);
+   #else
    return boost::math::tgamma_delta_ratio(x, y - x, pol);
+   #endif
 }
 
 template <class T, class Policy>
@@ -1866,7 +2104,18 @@ BOOST_MATH_GPU_ENABLED T gamma_p_derivative_imp(T a, T x, const Policy& pol)
    if(f1 == 0)
    {
       // Underflow in calculation, use logs instead:
+      #ifdef BOOST_MATH_HAS_NVRTC
+      if (boost::math::is_same_v<T, float>)
+      {
+         f1 = a * ::logf(x) - x - ::lgammaf(a) - ::logf(x);
+      }
+      else
+      {
+         f1 = a * ::log(x) - x - ::lgamma(a) - ::log(x);
+      }
+      #else
       f1 = a * log(x) - x - lgamma(a, pol) - log(x);
+      #endif
       f1 = exp(f1);
    }
    else
@@ -1901,7 +2150,7 @@ struct igamma_initializer
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
 
-         typedef std::integral_constant<int,
+         typedef boost::math::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 53 ? 53 :
             precision_type::value <= 64 ? 64 :
@@ -1911,19 +2160,19 @@ struct igamma_initializer
          do_init(tag_type());
       }
       template <int N>
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, N>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, N>&)
       {
          // If std::numeric_limits<T>::digits is zero, we must not call
          // our initialization code here as the precision presumably
          // varies at runtime, and will not have been set yet.  Plus the
          // code requiring initialization isn't called when digits == 0.
-         if (std::numeric_limits<T>::digits)
+         if (boost::math::numeric_limits<T>::digits)
          {
             boost::math::gamma_p(static_cast<T>(400), static_cast<T>(400), Policy());
          }
       }
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 53>&){}
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 53>&){}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
    BOOST_MATH_STATIC const init initializer;
    BOOST_MATH_GPU_ENABLED static void force_instantiate()
@@ -1945,7 +2194,7 @@ struct lgamma_initializer
       BOOST_MATH_GPU_ENABLED init()
       {
          typedef typename policies::precision<T, Policy>::type precision_type;
-         typedef std::integral_constant<int,
+         typedef boost::math::integral_constant<int,
             precision_type::value <= 0 ? 0 :
             precision_type::value <= 64 ? 64 :
             precision_type::value <= 113 ? 113 : 0
@@ -1953,20 +2202,20 @@ struct lgamma_initializer
 
          do_init(tag_type());
       }
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
       {
          boost::math::lgamma(static_cast<T>(2.5), Policy());
          boost::math::lgamma(static_cast<T>(1.25), Policy());
          boost::math::lgamma(static_cast<T>(1.5), Policy());
          boost::math::lgamma(static_cast<T>(1.75), Policy());
       }
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 0>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 0>&)
       {
       }
       BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
@@ -2016,13 +2265,6 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 
 } // namespace detail
 
-template <class T>
-BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
-   tgamma(T z)
-{
-   return tgamma(z, policies::policy<>());
-}
-
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    lgamma(T z, int* sign, const Policy&)
@@ -2079,7 +2321,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   return policies::checked_narrowing_cast<typename std::remove_cv<result_type>::type, forwarding_policy>(detail::tgammap1m1_imp(static_cast<value_type>(z), forwarding_policy(), evaluation_type()), "boost::math::tgamma1pm1<%!%>(%1%)");
+   return policies::checked_narrowing_cast<typename boost::math::remove_cv<result_type>::type, forwarding_policy>(detail::tgammap1m1_imp(static_cast<value_type>(z), forwarding_policy(), evaluation_type()), "boost::math::tgamma1pm1<%!%>(%1%)");
 }
 
 template <class T>
@@ -2111,6 +2353,12 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
    using result_type = tools::promote_args_t<T1, T2>;
    return static_cast<result_type>(detail::tgamma(a, z, pol, boost::math::false_type()));
 }
+template <class T>
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
+   tgamma(T z)
+{
+   return tgamma(z, policies::policy<>());
+}
 //
 // Full lower incomplete gamma:
 //
@@ -2284,73 +2532,4 @@ BOOST_MATH_GPU_ENABLED inline tools::promote_args_t<T1, T2>
 #include <boost/math/special_functions/detail/gamma_inva.hpp>
 #include <boost/math/special_functions/erf.hpp>
 
-#else
-
-#include <boost/math/tools/config.hpp>
-#include <boost/math/special_functions/expm1.hpp>
-
-namespace boost {
-namespace math {
-
-inline BOOST_MATH_GPU_ENABLED float tgamma(float x) { return ::tgammaf(x); }
-inline BOOST_MATH_GPU_ENABLED double tgamma(double x) { return ::tgamma(x); }
-
-template <typename T, typename Policy>
-BOOST_MATH_GPU_ENABLED T tgamma(T x, const Policy&)
-{
-   return boost::math::tgamma(x);
-}
-
-inline BOOST_MATH_GPU_ENABLED float lgamma(float x) { return ::lgammaf(x); }
-inline BOOST_MATH_GPU_ENABLED double lgamma(double x) { return ::lgamma(x); }
-
-template <typename T, typename Policy>
-BOOST_MATH_GPU_ENABLED T lgamma(T x, const Policy&)
-{
-   return boost::math::lgamma(x);
-}
-
-template <typename T, typename Policy>
-BOOST_MATH_GPU_ENABLED T lgamma(T x, int* sign, const Policy&)
-{
-   auto res = boost::math::lgamma(x);
-   if (sign != nullptr)
-   {
-      if (res < 0)
-      {
-         *sign = -1;
-      }
-      else
-      {
-         *sign = 1;
-      }
-   }
-
-   return res;
-}
-
-template <typename T>
-BOOST_MATH_GPU_ENABLED T tgamma1pm1(T z)
-{
-   using namespace boost::math;
-
-   if (fabs(z) < T(0.55))
-   {
-      return expm1(lgamma(z));
-   }
-
-   return expm1(lgamma(1 + z));
-}
-
-template <typename T, typename Policy>
-BOOST_MATH_GPU_ENABLED T tgamma1pm1(T x, const Policy&)
-{
-   return tgamma1pm1(x);
-}
-
-} // namespace math
-} // namespace boost
-
-#endif // __CUDACC_RTC__
-
 #endif // BOOST_MATH_SF_GAMMA_HPP
diff --git a/include/boost/math/special_functions/log1p.hpp b/include/boost/math/special_functions/log1p.hpp
index cdec8ee86c..758f606687 100644
--- a/include/boost/math/special_functions/log1p.hpp
+++ b/include/boost/math/special_functions/log1p.hpp
@@ -13,15 +13,13 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
-
-#ifndef BOOST_MATH_HAS_NVRTC
-
-#include <cmath>
-#include <cstdint>
-#include <limits>
 #include <boost/math/tools/series.hpp>
 #include <boost/math/tools/rational.hpp>
 #include <boost/math/tools/big_constant.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/math/tools/precision.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/assert.hpp>
@@ -82,7 +80,7 @@ namespace detail
 // it performs no better than log(1+x): which is to say not very well at all.
 //
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const boost::math::integral_constant<int, 0>&)
 { // The function returns the natural logarithm of 1 + x.
    typedef typename tools::promote_args<T>::type result_type;
    BOOST_MATH_STD_USING
@@ -104,7 +102,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const std::in
    if(a < tools::epsilon<result_type>())
       return x;
    detail::log1p_series<result_type> s(x);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    result_type result = tools::sum_series(s, policies::get_epsilon<result_type, Policy>(), max_iter);
 
@@ -113,7 +111,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const & x, const Policy& pol, const std::in
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 53>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
@@ -166,7 +164,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::int
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 64>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
@@ -221,7 +219,7 @@ BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::int
 }
 
 template <class T, class Policy>
-BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const std::integral_constant<int, 24>&)
+BOOST_MATH_GPU_ENABLED T log1p_imp(T const& x, const Policy& pol, const boost::math::integral_constant<int, 24>&)
 { // The function returns the natural logarithm of 1 + x.
    BOOST_MATH_STD_USING
 
@@ -276,8 +274,8 @@ struct log1p_initializer
          do_init(tag());
       }
       template <int N>
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, N>&){}
-      BOOST_MATH_GPU_ENABLED static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, N>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          boost::math::log1p(static_cast<T>(0.25), Policy());
       }
@@ -286,7 +284,9 @@ struct log1p_initializer
    BOOST_MATH_STATIC const init initializer;
    BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -309,7 +309,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1p(T x, c
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 53 ? 53 :
       precision_type::value <= 64 ? 64 : 0
@@ -459,7 +459,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
       return -x * x / 2;
    boost::math::detail::log1p_series<T> s(x);
    s();
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    T result = boost::math::tools::sum_series(s, policies::get_epsilon<T, Policy>(), max_iter);
 
@@ -476,40 +476,6 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type log1pmx(T x)
 } // namespace math
 } // namespace boost
 
-#else // Special handling for NVRTC platform
-
-namespace boost {
-namespace math {
-
-template <typename T>
-BOOST_MATH_GPU_ENABLED auto log1p(T x)
-{
-   return ::log1p(x);
-}
-
-template <>
-BOOST_MATH_GPU_ENABLED auto log1p(float x)
-{
-   return ::log1pf(x);
-}
-
-template <typename T, typename Policy>
-BOOST_MATH_GPU_ENABLED auto log1p(T x, const Policy&)
-{
-   return ::log1p(x);
-}
-
-template <typename Policy>
-BOOST_MATH_GPU_ENABLED auto log1p(float x, const Policy&)
-{
-   return ::log1pf(x);
-}
-
-} // namespace math
-} // namespace boost
-
-#endif // BOOST_MATH_HAS_NVRTC
-
 #ifdef _MSC_VER
 #pragma warning(pop)
 #endif
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 21f51e5075..16ae3b61eb 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -512,28 +512,28 @@ namespace boost
 
    // gamma inverse.
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q, const Policy&);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q, const Policy&);
 
    // digamma:
    template <class T>
@@ -1447,16 +1447,16 @@ namespace boost
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_p_derivative(T1 a, T2 x){ return boost::math::gamma_p_derivative(a, x, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p){ return boost::math::gamma_p_inv(a, p, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_p_inv(T1 a, T2 p){ return boost::math::gamma_p_inv(a, p, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p){ return boost::math::gamma_p_inva(a, p, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_p_inva(T1 a, T2 p){ return boost::math::gamma_p_inva(a, p, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q){ return boost::math::gamma_q_inv(a, q, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_q_inv(T1 a, T2 q){ return boost::math::gamma_q_inv(a, q, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q){ return boost::math::gamma_q_inva(a, q, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> gamma_q_inva(T1 a, T2 q){ return boost::math::gamma_q_inva(a, q, Policy()); }\
 \
    template <class T>\
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> digamma(T x){ return boost::math::digamma(x, Policy()); }\
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 1f444c0048..a2af127630 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -677,6 +677,7 @@ namespace boost{ namespace math{
 #include <cuda/std/utility>
 #include <cuda/std/cstdint>
 #include <cuda/std/array>
+#include <cuda/std/tuple>
 
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
@@ -802,6 +803,7 @@ BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_max(const T& a, const T& b) { return
 #define BOOST_MATH_IF_CONSTEXPR if constexpr
 #define BOOST_MATH_IS_FLOAT(T) (boost::math::is_floating_point<T>::value)
 #define BOOST_MATH_CONSTEXPR_TABLE_FUNCTION constexpr
+#define BOOST_MATH_NO_EXCEPTIONS
 
 // This should be defined to nothing but since it is not specifically a math macro
 // we need to undef before proceeding
diff --git a/include/boost/math/tools/fraction.hpp b/include/boost/math/tools/fraction.hpp
index e5a31edf65..f36d024c40 100644
--- a/include/boost/math/tools/fraction.hpp
+++ b/include/boost/math/tools/fraction.hpp
@@ -18,9 +18,6 @@
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/complex.hpp>
 #include <boost/math/tools/cstdint.hpp>
-#include <type_traits>
-#include <cstdint>
-#include <cmath>
 
 namespace boost{ namespace math{ namespace tools{
 
@@ -67,7 +64,7 @@ namespace detail
 
    template <typename Gen>
    struct fraction_traits
-       : public std::conditional<
+       : public boost::math::conditional<
          is_pair<typename Gen::result_type>::value,
          fraction_traits_pair<Gen>,
          fraction_traits_simple<Gen>>::type
@@ -115,7 +112,7 @@ namespace detail {
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b_impl(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
       noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-      #ifndef BOOST_MATH_ENABLE_SYCL
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       // SYCL can not handle this condition so we only check float on that platform
       && noexcept(std::declval<Gen>()())
       #endif
@@ -167,7 +164,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-         #ifndef BOOST_MATH_ENABLE_SYCL
+         #ifndef BOOST_MATH_HAS_GPU_SUPPORT
          && noexcept(std::declval<Gen>()())
          #endif
          )
@@ -178,19 +175,19 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, const U& factor)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
 {
-   boost::math::uintmax_t max_terms = (std::numeric_limits<boost::math::uintmax_t>::max)();
+   boost::math::uintmax_t max_terms = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
@@ -201,14 +198,14 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    using result_type = typename traits::result_type;
 
    result_type factor = ldexp(1.0f, 1 - bits); // 1 / pow(result_type(2), bits);
-   boost::math::uintmax_t max_terms = (std::numeric_limits<boost::math::uintmax_t>::max)();
+   boost::math::uintmax_t max_terms = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_b_impl(g, factor, max_terms);
 }
 
 template <typename Gen>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_b(Gen& g, int bits, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
@@ -241,7 +238,7 @@ namespace detail {
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a_impl(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
@@ -294,7 +291,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
@@ -305,19 +302,19 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 template <typename Gen, typename U>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, const U& factor)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type)
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
 {
-   boost::math::uintmax_t max_iter = (std::numeric_limits<boost::math::uintmax_t>::max)();
+   boost::math::uintmax_t max_iter = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
 
 template <typename Gen>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
@@ -328,7 +325,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
    typedef typename traits::result_type result_type;
 
    result_type factor = ldexp(1.0f, 1-bits); // 1 / pow(result_type(2), bits);
-   boost::math::uintmax_t max_iter = (std::numeric_limits<boost::math::uintmax_t>::max)();
+   boost::math::uintmax_t max_iter = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
 
    return detail::continued_fraction_a_impl(g, factor, max_iter);
 }
@@ -336,7 +333,7 @@ BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type
 template <typename Gen>
 BOOST_MATH_GPU_ENABLED inline typename detail::fraction_traits<Gen>::result_type continued_fraction_a(Gen& g, int bits, boost::math::uintmax_t& max_terms)
    noexcept(BOOST_MATH_IS_FLOAT(typename detail::fraction_traits<Gen>::result_type) 
-   #ifndef BOOST_MATH_ENABLE_SYCL
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    && noexcept(std::declval<Gen>()())
    #endif
    )
diff --git a/include/boost/math/tools/precision.hpp b/include/boost/math/tools/precision.hpp
index 1e4bf58ac0..662657732c 100644
--- a/include/boost/math/tools/precision.hpp
+++ b/include/boost/math/tools/precision.hpp
@@ -290,7 +290,7 @@ template <class T, class Tag>
 BOOST_MATH_GPU_ENABLED inline T root_epsilon_imp(const T*, const Tag&)
 {
    BOOST_MATH_STD_USING
-   static const T r_eps = sqrt(tools::epsilon<T>());
+   BOOST_MATH_STATIC_LOCAL_VARIABLE const T r_eps = sqrt(tools::epsilon<T>());
    return r_eps;
 }
 
diff --git a/include/boost/math/tools/series.hpp b/include/boost/math/tools/series.hpp
index 50f2828bb4..4617ea3df7 100644
--- a/include/boost/math/tools/series.hpp
+++ b/include/boost/math/tools/series.hpp
@@ -14,6 +14,7 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/type_traits.hpp>
 
 namespace boost{ namespace math{ namespace tools{
 
diff --git a/include/boost/math/tools/toms748_solve.hpp b/include/boost/math/tools/toms748_solve.hpp
index ea93713224..dee2346853 100644
--- a/include/boost/math/tools/toms748_solve.hpp
+++ b/include/boost/math/tools/toms748_solve.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,13 +11,13 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/policies/error_handling.hpp>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/special_functions/sign.hpp>
-#include <limits>
-#include <utility>
-#include <cstdint>
 
 #ifdef BOOST_MATH_LOG_ROOT_ITERATIONS
 #  define BOOST_MATH_LOGGER_INCLUDE <boost/math/tools/iteration_logger.hpp>
@@ -32,29 +33,36 @@ template <class T>
 class eps_tolerance
 {
 public:
-   eps_tolerance() : eps(4 * tools::epsilon<T>())
+   BOOST_MATH_GPU_ENABLED eps_tolerance() : eps(4 * tools::epsilon<T>())
    {
 
    }
-   eps_tolerance(unsigned bits)
+   BOOST_MATH_GPU_ENABLED eps_tolerance(unsigned bits)
    {
       BOOST_MATH_STD_USING
-      eps = (std::max)(T(ldexp(1.0F, 1-bits)), T(4 * tools::epsilon<T>()));
+      eps = BOOST_MATH_GPU_SAFE_MAX(T(ldexp(1.0F, 1-bits)), T(4 * tools::epsilon<T>()));
    }
-   bool operator()(const T& a, const T& b)
+   BOOST_MATH_GPU_ENABLED bool operator()(const T& a, const T& b)
    {
       BOOST_MATH_STD_USING
-      return fabs(a - b) <= (eps * (std::min)(fabs(a), fabs(b)));
+      return fabs(a - b) <= (eps * BOOST_MATH_GPU_SAFE_MIN(fabs(a), fabs(b)));
    }
 private:
    T eps;
 };
 
+// CUDA warns about __host__ __device__ marker on defaulted constructor
+// but the warning is benign 
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_suppress 20012
+#endif
+
 struct equal_floor
 {
-   equal_floor()= default;
+   BOOST_MATH_GPU_ENABLED equal_floor() = default;
+   
    template <class T>
-   bool operator()(const T& a, const T& b)
+   BOOST_MATH_GPU_ENABLED bool operator()(const T& a, const T& b)
    {
       BOOST_MATH_STD_USING
       return (floor(a) == floor(b)) || (fabs((b-a)/b) < boost::math::tools::epsilon<T>() * 2);
@@ -63,9 +71,10 @@ struct equal_floor
 
 struct equal_ceil
 {
-   equal_ceil()= default;
+   BOOST_MATH_GPU_ENABLED equal_ceil() = default;
+   
    template <class T>
-   bool operator()(const T& a, const T& b)
+   BOOST_MATH_GPU_ENABLED bool operator()(const T& a, const T& b)
    {
       BOOST_MATH_STD_USING
       return (ceil(a) == ceil(b)) || (fabs((b - a) / b) < boost::math::tools::epsilon<T>() * 2);
@@ -74,19 +83,24 @@ struct equal_ceil
 
 struct equal_nearest_integer
 {
-   equal_nearest_integer()= default;
+   BOOST_MATH_GPU_ENABLED equal_nearest_integer() = default;
+   
    template <class T>
-   bool operator()(const T& a, const T& b)
+   BOOST_MATH_GPU_ENABLED bool operator()(const T& a, const T& b)
    {
       BOOST_MATH_STD_USING
       return (floor(a + 0.5f) == floor(b + 0.5f)) || (fabs((b - a) / b) < boost::math::tools::epsilon<T>() * 2);
    }
 };
 
+#ifdef BOOST_MATH_ENABLE_CUDA
+#  pragma nv_diag_default 20012
+#endif
+
 namespace detail{
 
 template <class F, class T>
-void bracket(F f, T& a, T& b, T c, T& fa, T& fb, T& d, T& fd)
+BOOST_MATH_GPU_ENABLED void bracket(F f, T& a, T& b, T c, T& fa, T& fb, T& d, T& fd)
 {
    //
    // Given a point c inside the existing enclosing interval
@@ -150,7 +164,7 @@ void bracket(F f, T& a, T& b, T c, T& fa, T& fb, T& d, T& fd)
 }
 
 template <class T>
-inline T safe_div(T num, T denom, T r)
+BOOST_MATH_GPU_ENABLED inline T safe_div(T num, T denom, T r)
 {
    //
    // return num / denom without overflow,
@@ -167,7 +181,7 @@ inline T safe_div(T num, T denom, T r)
 }
 
 template <class T>
-inline T secant_interpolate(const T& a, const T& b, const T& fa, const T& fb)
+BOOST_MATH_GPU_ENABLED inline T secant_interpolate(const T& a, const T& b, const T& fa, const T& fb)
 {
    //
    // Performs standard secant interpolation of [a,b] given
@@ -188,9 +202,9 @@ inline T secant_interpolate(const T& a, const T& b, const T& fa, const T& fb)
 }
 
 template <class T>
-T quadratic_interpolate(const T& a, const T& b, T const& d,
-                           const T& fa, const T& fb, T const& fd, 
-                           unsigned count)
+BOOST_MATH_GPU_ENABLED T quadratic_interpolate(const T& a, const T& b, T const& d,
+                                               const T& fa, const T& fb, T const& fd, 
+                                               unsigned count)
 {
    //
    // Performs quadratic interpolation to determine the next point,
@@ -244,9 +258,9 @@ T quadratic_interpolate(const T& a, const T& b, T const& d,
 }
 
 template <class T>
-T cubic_interpolate(const T& a, const T& b, const T& d, 
-                    const T& e, const T& fa, const T& fb, 
-                    const T& fd, const T& fe)
+BOOST_MATH_GPU_ENABLED T cubic_interpolate(const T& a, const T& b, const T& d, 
+                                           const T& e, const T& fa, const T& fb, 
+                                           const T& fd, const T& fe)
 {
    //
    // Uses inverse cubic interpolation of f(x) at points 
@@ -293,7 +307,7 @@ T cubic_interpolate(const T& a, const T& b, const T& d,
 } // namespace detail
 
 template <class F, class T, class Tol, class Policy>
-std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const T& fbx, Tol tol, std::uintmax_t& max_iter, const Policy& pol)
+BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const T& fbx, Tol tol, boost::math::uintmax_t& max_iter, const Policy& pol)
 {
    //
    // Main entry point and logic for Toms Algorithm 748
@@ -301,15 +315,15 @@ std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const
    //
    BOOST_MATH_STD_USING  // For ADL of std math functions
 
-   static const char* function = "boost::math::tools::toms748_solve<%1%>";
+   constexpr auto function = "boost::math::tools::toms748_solve<%1%>";
 
    //
    // Sanity check - are we allowed to iterate at all?
    //
    if (max_iter == 0)
-      return std::make_pair(ax, bx);
+      return boost::math::make_pair(ax, bx);
 
-   std::uintmax_t count = max_iter;
+   boost::math::uintmax_t count = max_iter;
    T a, b, fa, fb, c, u, fu, a0, b0, d, fd, e, fe;
    static const T mu = 0.5f;
 
@@ -330,7 +344,7 @@ std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const
          b = a;
       else if(fb == 0)
          a = b;
-      return std::make_pair(a, b);
+      return boost::math::make_pair(a, b);
    }
 
    if(boost::math::sign(fa) * boost::math::sign(fb) > 0)
@@ -472,37 +486,37 @@ std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const
       a = b;
    }
    BOOST_MATH_LOG_COUNT(max_iter)
-   return std::make_pair(a, b);
+   return boost::math::make_pair(a, b);
 }
 
 template <class F, class T, class Tol>
-inline std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const T& fbx, Tol tol, std::uintmax_t& max_iter)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, const T& fax, const T& fbx, Tol tol, boost::math::uintmax_t& max_iter)
 {
    return toms748_solve(f, ax, bx, fax, fbx, tol, max_iter, policies::policy<>());
 }
 
 template <class F, class T, class Tol, class Policy>
-inline std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, Tol tol, std::uintmax_t& max_iter, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, Tol tol, boost::math::uintmax_t& max_iter, const Policy& pol)
 {
    if (max_iter <= 2)
-      return std::make_pair(ax, bx);
+      return boost::math::make_pair(ax, bx);
    max_iter -= 2;
-   std::pair<T, T> r = toms748_solve(f, ax, bx, f(ax), f(bx), tol, max_iter, pol);
+   boost::math::pair<T, T> r = toms748_solve(f, ax, bx, f(ax), f(bx), tol, max_iter, pol);
    max_iter += 2;
    return r;
 }
 
 template <class F, class T, class Tol>
-inline std::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, Tol tol, std::uintmax_t& max_iter)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> toms748_solve(F f, const T& ax, const T& bx, Tol tol, boost::math::uintmax_t& max_iter)
 {
    return toms748_solve(f, ax, bx, tol, max_iter, policies::policy<>());
 }
 
 template <class F, class T, class Tol, class Policy>
-std::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool rising, Tol tol, std::uintmax_t& max_iter, const Policy& pol)
+BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool rising, Tol tol, boost::math::uintmax_t& max_iter, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::tools::bracket_and_solve_root<%1%>";
+   constexpr auto function = "boost::math::tools::bracket_and_solve_root<%1%>";
    //
    // Set up initial brackets:
    //
@@ -513,7 +527,7 @@ std::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool risin
    //
    // Set up invocation count:
    //
-   std::uintmax_t count = max_iter - 1;
+   boost::math::uintmax_t count = max_iter - 1;
 
    int step = 32;
 
@@ -563,7 +577,7 @@ std::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool risin
             // Escape route just in case the answer is zero!
             max_iter -= count;
             max_iter += 1;
-            return a > 0 ? std::make_pair(T(0), T(a)) : std::make_pair(T(a), T(0)); 
+            return a > 0 ? boost::math::make_pair(T(0), T(a)) : boost::math::make_pair(T(a), T(0)); 
          }
          if(count == 0)
             return boost::math::detail::pair_from_single(policies::raise_evaluation_error(function, "Unable to bracket root, last nearest value was %1%", a, pol));
@@ -592,7 +606,7 @@ std::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool risin
    }
    max_iter -= count;
    max_iter += 1;
-   std::pair<T, T> r = toms748_solve(
+   boost::math::pair<T, T> r = toms748_solve(
       f, 
       (a < 0 ? b : a), 
       (a < 0 ? a : b), 
@@ -608,7 +622,7 @@ std::pair<T, T> bracket_and_solve_root(F f, const T& guess, T factor, bool risin
 }
 
 template <class F, class T, class Tol>
-inline std::pair<T, T> bracket_and_solve_root(F f, const T& guess, const T& factor, bool rising, Tol tol, std::uintmax_t& max_iter)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> bracket_and_solve_root(F f, const T& guess, const T& factor, bool rising, Tol tol, boost::math::uintmax_t& max_iter)
 {
    return bracket_and_solve_root(f, guess, factor, rising, tol, max_iter, policies::policy<>());
 }
diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index 6a949d5e5a..82d23b8d77 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -13,6 +13,7 @@
 
 #include <boost/math/tools/type_traits.hpp>
 #include <cuda/std/utility>
+#include <cuda/std/tuple>
 
 namespace boost { 
 namespace math {
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 64fac76fba..1fb55da197 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -34,6 +34,13 @@ run test_cauchy_quan_float.cu ;
 run test_cauchy_range_support_double.cu ;
 run test_cauchy_range_support_float.cu ;
 
+run test_chi_squared_cdf_double.cu ;
+run test_chi_squared_cdf_float.cu ;
+run test_chi_squared_pdf_double.cu ;
+run test_chi_squared_pdf_float.cu ;
+run test_chi_squared_quan_double.cu ;
+run test_chi_squared_quan_float.cu ;
+
 run test_exponential_cdf_double.cu ;
 run test_exponential_cdf_float.cu ;
 run test_exponential_pdf_double.cu ;
@@ -90,6 +97,13 @@ run test_saspoint5_pdf_float.cu ;
 run test_saspoint5_quan_double.cu ;
 run test_saspoint5_quan_float.cu ;
 
+run test_weibull_cdf_double.cu ;
+run test_weibull_cdf_float.cu ;
+run test_weibull_pdf_double.cu ;
+run test_weibull_pdf_float.cu ;
+run test_weibull_quan_double.cu ;
+run test_weibull_quan_float.cu ;
+
 # Special Functions
 run test_beta_double.cu ;
 run test_beta_float.cu ;
@@ -153,6 +167,12 @@ run test_lgamma_double.cu ;
 run test_lgamma_float.cu ;
 run test_tgamma_double.cu ;
 run test_tgamma_float.cu ;
+run test_tgamma_ratio_double.cu ;
+run test_tgamma_ratio_float.cu ;
+run test_gamma_p_derivative_double.cu ;
+run test_gamma_p_derivative_float.cu ;
+run test_gamma_p_inv_double.cu ;
+run test_gamma_p_inv_float.cu ;
 
 run test_log1p_double.cu ;
 run test_log1p_float.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index de235822ef..4a37960a51 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -31,6 +31,13 @@ run test_cauchy_pdf_nvrtc_float.cpp ;
 run test_cauchy_quan_nvrtc_double.cpp ;
 run test_cauchy_quan_nvrtc_float.cpp ;
 
+run test_chi_squared_cdf_nvrtc_double.cpp ;
+run test_chi_squared_cdf_nvrtc_float.cpp ;
+run test_chi_squared_pdf_nvrtc_double.cpp ;
+run test_chi_squared_pdf_nvrtc_float.cpp ;
+run test_chi_squared_quan_nvrtc_double.cpp ;
+run test_chi_squared_quan_nvrtc_float.cpp ;
+
 run test_exponential_cdf_nvrtc_double.cpp ;
 run test_exponential_cdf_nvrtc_float.cpp ;
 run test_exponential_pdf_nvrtc_double.cpp ;
@@ -87,6 +94,13 @@ run test_saspoint5_pdf_nvrtc_float.cpp ;
 run test_saspoint5_quan_nvrtc_double.cpp ;
 run test_saspoint5_quan_nvrtc_float.cpp ;
 
+run test_weibull_cdf_nvrtc_double.cpp ;
+run test_weibull_cdf_nvrtc_float.cpp ;
+run test_weibull_pdf_nvrtc_double.cpp ;
+run test_weibull_pdf_nvrtc_float.cpp ;
+run test_weibull_quan_nvrtc_double.cpp ;
+run test_weibull_quan_nvrtc_float.cpp ;
+
 # Special Functions
 run test_beta_nvrtc_double.cpp ;
 run test_beta_nvrtc_float.cpp ;
@@ -148,6 +162,12 @@ run test_fpclassify_nvrtc_float.cpp ;
 
 run test_gamma_nvrtc_double.cpp ;
 run test_gamma_nvrtc_float.cpp ;
+run test_gamma_p_derivative_nvrtc_double.cpp ;
+run test_gamma_p_derivative_nvrtc_float.cpp ;
+run test_gamma_p_inv_nvrtc_double.cpp ;
+run test_gamma_p_inv_nvrtc_float.cpp ;
+run test_tgamma_ratio_nvrtc_double.cpp ;
+run test_tgamma_ratio_nvrtc_float.cpp ;
 
 run test_log1p_nvrtc_double.cpp ;
 run test_log1p_nvrtc_float.cpp ;
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 97c48474ca..2fd5954ae1 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -13,6 +13,7 @@ project : requirements
 run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
 run test_cauchy.cpp ;
+run test_chi_squared.cpp ;
 run test_exponential_dist.cpp ;
 run test_extreme_value.cpp ;
 run test_holtsmark.cpp ;
@@ -21,20 +22,35 @@ run test_laplace.cpp ;
 run test_logistic_dist.cpp ;
 run test_mapairy.cpp ;
 run test_saspoint5.cpp ;
+run test_weibull.cpp ;
 
 # Special Functions
 run pow_test.cpp ;
+
 run test_beta_simple.cpp ;
+
 run test_bessel_i.cpp ;
 run test_bessel_j.cpp ;
 run test_bessel_k.cpp ;
 run test_bessel_y.cpp ;
+
 run test_cbrt.cpp ;
+
 run test_sign.cpp ;
+
 run test_round.cpp ;
+
 run test_expm1_simple.cpp ;
+
 run test_log1p_simple.cpp ;
+
 run test_digamma_simple.cpp ;
+
 run test_trigamma.cpp ;
+
 run test_erf.cpp ;
+
 run test_gamma.cpp ;
+run test_igamma.cpp ;
+run test_igamma_inv.cpp ;
+run test_igamma_inva.cpp ;
diff --git a/test/test_bessel_i.cpp b/test/test_bessel_i.cpp
index 70aac91e45..09487ddf1b 100644
--- a/test/test_bessel_i.cpp
+++ b/test/test_bessel_i.cpp
@@ -10,6 +10,14 @@
 #include <boost/math/tools/config.hpp>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_bessel_i.hpp"
 
 //
diff --git a/test/test_bessel_j.cpp b/test/test_bessel_j.cpp
index 516e34c29a..31a64bc579 100644
--- a/test/test_bessel_j.cpp
+++ b/test/test_bessel_j.cpp
@@ -10,6 +10,14 @@
 #include <boost/math/tools/config.hpp>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_bessel_j.hpp"
 
 //
diff --git a/test/test_bessel_k.cpp b/test/test_bessel_k.cpp
index d4ab7721f4..84ba0830f2 100644
--- a/test/test_bessel_k.cpp
+++ b/test/test_bessel_k.cpp
@@ -17,6 +17,14 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_bessel_k.hpp"
 
 //
diff --git a/test/test_bessel_y.cpp b/test/test_bessel_y.cpp
index 0bbefba55f..232a903963 100644
--- a/test/test_bessel_y.cpp
+++ b/test/test_bessel_y.cpp
@@ -10,6 +10,14 @@
 #include <boost/math/tools/config.hpp>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_bessel_y.hpp"
 
 //
diff --git a/test/test_chi_squared.cpp b/test/test_chi_squared.cpp
index cc7747a6c0..bfd4b5f3a2 100644
--- a/test/test_chi_squared.cpp
+++ b/test/test_chi_squared.cpp
@@ -16,9 +16,13 @@
 #  pragma warning(disable: 4127) // conditional expression is constant
 #endif
 
-#include <boost/math/tools/test.hpp> // for real_concept
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
 #include <boost/math/distributions/chi_squared.hpp> // for chi_squared_distribution
 #include <boost/math/distributions/non_central_chi_squared.hpp> // for chi_squared_distribution
diff --git a/test/test_chi_squared_cdf_double.cu b/test/test_chi_squared_cdf_double.cu
new file mode 100644
index 0000000000..1b0c34ce6b
--- /dev/null
+++ b/test/test_chi_squared_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_cdf_float.cu b/test/test_chi_squared_cdf_float.cu
new file mode 100644
index 0000000000..8ca99ed2e0
--- /dev/null
+++ b/test/test_chi_squared_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_cdf_nvrtc_double.cpp b/test/test_chi_squared_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..0ad459fa67
--- /dev/null
+++ b/test/test_chi_squared_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_chi_squared_cdf_nvrtc_float.cpp b/test/test_chi_squared_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..1b26c5d6f2
--- /dev/null
+++ b/test/test_chi_squared_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_chi_squared_pdf_double.cu b/test/test_chi_squared_pdf_double.cu
new file mode 100644
index 0000000000..ed45246d3c
--- /dev/null
+++ b/test/test_chi_squared_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_pdf_float.cu b/test/test_chi_squared_pdf_float.cu
new file mode 100644
index 0000000000..5a0f97db93
--- /dev/null
+++ b/test/test_chi_squared_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_pdf_nvrtc_double.cpp b/test/test_chi_squared_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..18d14a4b0e
--- /dev/null
+++ b/test/test_chi_squared_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_chi_squared_pdf_nvrtc_float.cpp b/test/test_chi_squared_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..754cbf7fba
--- /dev/null
+++ b/test/test_chi_squared_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_chi_squared_quan_double.cu b/test/test_chi_squared_quan_double.cu
new file mode 100644
index 0000000000..3b7dad972b
--- /dev/null
+++ b/test/test_chi_squared_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_quan_float.cu b/test/test_chi_squared_quan_float.cu
new file mode 100644
index 0000000000..3e779a090f
--- /dev/null
+++ b/test/test_chi_squared_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::chi_squared_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_chi_squared_quan_nvrtc_double.cpp b/test/test_chi_squared_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..69b15b6cfd
--- /dev/null
+++ b/test/test_chi_squared_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_chi_squared_quan_nvrtc_float.cpp b/test/test_chi_squared_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..d6e1b2a9b5
--- /dev/null
+++ b/test/test_chi_squared_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/chi_squared.hpp>
+extern "C" __global__ 
+void test_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::chi_squared_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::chi_squared_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_nvrtc_double.cpp b/test/test_gamma_nvrtc_double.cpp
index 9302d1190e..9fe2933720 100644
--- a/test/test_gamma_nvrtc_double.cpp
+++ b/test/test_gamma_nvrtc_double.cpp
@@ -85,9 +85,9 @@ int main()
         nvrtcAddNameExpression(prog, "test_gamma_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
-        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #else
-        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #endif
 
         // Compile the program
diff --git a/test/test_gamma_nvrtc_float.cpp b/test/test_gamma_nvrtc_float.cpp
index 6e9ba72586..5d34b130ad 100644
--- a/test/test_gamma_nvrtc_float.cpp
+++ b/test/test_gamma_nvrtc_float.cpp
@@ -87,7 +87,7 @@ int main()
         #ifdef BOOST_MATH_NVRTC_CI_RUN
         const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/math/boost-root/libs/math/include/"};
         #else
-        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #endif
 
         // Compile the program
diff --git a/test/test_gamma_p_derivative_double.cu b/test/test_gamma_p_derivative_double.cu
new file mode 100644
index 0000000000..566bc1657f
--- /dev/null
+++ b/test/test_gamma_p_derivative_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_derivative(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::gamma_p_derivative(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gamma_p_derivative_float.cu b/test/test_gamma_p_derivative_float.cu
new file mode 100644
index 0000000000..f9fd52a50c
--- /dev/null
+++ b/test/test_gamma_p_derivative_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_derivative(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::gamma_p_derivative(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gamma_p_derivative_nvrtc_double.cpp b/test/test_gamma_p_derivative_nvrtc_double.cpp
new file mode 100644
index 0000000000..53a752c2df
--- /dev/null
+++ b/test/test_gamma_p_derivative_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_p_derivative_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_derivative(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_p_derivative_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_p_derivative_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_p_derivative_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gamma_p_derivative(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_p_derivative_nvrtc_float.cpp b/test/test_gamma_p_derivative_nvrtc_float.cpp
new file mode 100644
index 0000000000..da9c50855b
--- /dev/null
+++ b/test/test_gamma_p_derivative_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_p_derivative_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_derivative(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_p_derivative_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_p_derivative_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_p_derivative_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gamma_p_derivative(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_p_inv_double.cu b/test/test_gamma_p_inv_double.cu
new file mode 100644
index 0000000000..4392f37d38
--- /dev/null
+++ b/test/test_gamma_p_inv_double.cu
@@ -0,0 +1,108 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_inv(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 gen(42);
+    std::uniform_real_distribution<float_type> dist(0, 1);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+        input_vector2[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::gamma_p_inv(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 1000)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                      << "Error found was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gamma_p_inv_float.cu b/test/test_gamma_p_inv_float.cu
new file mode 100644
index 0000000000..70033686c1
--- /dev/null
+++ b/test/test_gamma_p_inv_float.cu
@@ -0,0 +1,107 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_inv(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 gen(42);
+    std::uniform_real_distribution<float_type> dist(0, 1);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+        input_vector2[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::gamma_p_inv(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gamma_p_inv_nvrtc_double.cpp b/test/test_gamma_p_inv_nvrtc_double.cpp
new file mode 100644
index 0000000000..d270dbf901
--- /dev/null
+++ b/test/test_gamma_p_inv_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_p_inv_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_inv(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_p_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_p_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_p_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gamma_p_inv(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_p_inv_nvrtc_float.cpp b/test/test_gamma_p_inv_nvrtc_float.cpp
new file mode 100644
index 0000000000..7c844eb682
--- /dev/null
+++ b/test/test_gamma_p_inv_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_p_inv_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gamma_p_inv(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_p_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_p_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_p_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gamma_p_inv(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index 6aa3577868..475f5400aa 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -16,6 +16,14 @@
 # include <stdfloat>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 using boost::math::holtsmark_distribution;
 
 #ifndef BOOST_MATH_HAS_GPU_SUPPORT
diff --git a/test/test_igamma.cpp b/test/test_igamma.cpp
index 8e80c772c4..0ad7019963 100644
--- a/test/test_igamma.cpp
+++ b/test/test_igamma.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif 
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_igamma.hpp"
 
 //
diff --git a/test/test_igamma.hpp b/test/test_igamma.hpp
index b434f727ee..bfe386d4de 100644
--- a/test/test_igamma.hpp
+++ b/test/test_igamma.hpp
@@ -8,11 +8,12 @@
 
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/gamma.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_igamma_inv.cpp b/test/test_igamma_inv.cpp
index eafed0e1da..a88c3666be 100644
--- a/test/test_igamma_inv.cpp
+++ b/test/test_igamma_inv.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_igamma_inv.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
@@ -89,14 +100,22 @@ void expected_results()
       "linux.*",                          // platform
       largest_type,                     // test type(s)
       "[^|]*medium[^|]*",                   // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      "[^|]*", 350, 50);
+      #else
       "[^|]*", 350, 5);                  // test function
+      #endif
    add_expected_result(
       "[^|]*",                          // compiler
       "[^|]*",                          // stdlib
       "linux.*",                          // platform
       largest_type,                     // test type(s)
       "[^|]*large[^|]*",                   // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      "[^|]*", 150, 20);                  // test function
+      #else
       "[^|]*", 150, 5);                  // test function
+      #endif
 
 
    //
diff --git a/test/test_igamma_inv.hpp b/test/test_igamma_inv.hpp
index 7330e918a7..cf481537e7 100644
--- a/test/test_igamma_inv.hpp
+++ b/test/test_igamma_inv.hpp
@@ -6,13 +6,14 @@
 
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/gamma.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/results_collector.hpp>
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_igamma_inva.cpp b/test/test_igamma_inva.cpp
index 047df11735..8d0e965962 100644
--- a/test/test_igamma_inva.cpp
+++ b/test/test_igamma_inva.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 #include "test_igamma_inva.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
diff --git a/test/test_igamma_inva.hpp b/test/test_igamma_inva.hpp
index 402ea2f8bc..d9d317da15 100644
--- a/test/test_igamma_inva.hpp
+++ b/test/test_igamma_inva.hpp
@@ -8,13 +8,14 @@
 
 #include <boost/math/concepts/real_concept.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/gamma.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/results_collector.hpp>
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_landau.cpp b/test/test_landau.cpp
index 297589bc09..1625b21777 100644
--- a/test/test_landau.cpp
+++ b/test/test_landau.cpp
@@ -15,6 +15,14 @@
 # include <stdfloat>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Wliteral-range"
+#endif
+
 using boost::math::landau_distribution;
 
 #ifndef BOOST_MATH_HAS_GPU_SUPPORT
diff --git a/test/test_log1p_nvrtc_double.cpp b/test/test_log1p_nvrtc_double.cpp
index 722194be6a..36b0771b1b 100644
--- a/test/test_log1p_nvrtc_double.cpp
+++ b/test/test_log1p_nvrtc_double.cpp
@@ -85,9 +85,9 @@ int main()
         nvrtcAddNameExpression(prog, "test_log1p_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
-        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #else
-        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #endif
 
         // Compile the program
diff --git a/test/test_log1p_nvrtc_float.cpp b/test/test_log1p_nvrtc_float.cpp
index 772c50cd10..7194ffb56a 100644
--- a/test/test_log1p_nvrtc_float.cpp
+++ b/test/test_log1p_nvrtc_float.cpp
@@ -7,6 +7,11 @@
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
 
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
 #include <iostream>
 #include <iomanip>
 #include <vector>
@@ -14,9 +19,6 @@
 #include <exception>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/special_functions/relative_difference.hpp>
-#include <cuda.h>
-#include <cuda_runtime.h>
-#include <nvrtc.h>
 
 typedef float float_type;
 
@@ -85,9 +87,9 @@ int main()
         nvrtcAddNameExpression(prog, "test_log1p_kernel");
 
         #ifdef BOOST_MATH_NVRTC_CI_RUN
-        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #else
-        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/"};
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
         #endif
 
         // Compile the program
diff --git a/test/test_round.cpp b/test/test_round.cpp
index e363efd565..e603aa510d 100644
--- a/test/test_round.cpp
+++ b/test/test_round.cpp
@@ -7,6 +7,11 @@
 #include <pch.hpp>
 #endif
 
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wimplicit-const-int-float-conversion"
+#endif
+
 #include <boost/math/concepts/real_concept.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/math/tools/config.hpp>
diff --git a/test/test_tgamma_ratio_double.cu b/test/test_tgamma_ratio_double.cu
new file mode 100644
index 0000000000..059e1c3c67
--- /dev/null
+++ b/test/test_tgamma_ratio_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma_ratio(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::tgamma_ratio(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_tgamma_ratio_float.cu b/test/test_tgamma_ratio_float.cu
new file mode 100644
index 0000000000..dc669bd7fb
--- /dev/null
+++ b/test/test_tgamma_ratio_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma_ratio(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::tgamma_ratio(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_tgamma_ratio_nvrtc_double.cpp b/test/test_tgamma_ratio_nvrtc_double.cpp
new file mode 100644
index 0000000000..5b0c3b1e67
--- /dev/null
+++ b/test/test_tgamma_ratio_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_tgamma_ratio_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma_ratio(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_tgamma_ratio_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_tgamma_ratio_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_tgamma_ratio_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::tgamma_ratio(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_tgamma_ratio_nvrtc_float.cpp b/test/test_tgamma_ratio_nvrtc_float.cpp
new file mode 100644
index 0000000000..ab1bf339b4
--- /dev/null
+++ b/test/test_tgamma_ratio_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gamma.hpp>
+extern "C" __global__ 
+void test_tgamma_ratio_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::tgamma_ratio(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_tgamma_ratio_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_tgamma_ratio_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_tgamma_ratio_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::tgamma_ratio(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull.cpp b/test/test_weibull.cpp
index 4b31a7f0b7..dc509b742b 100644
--- a/test/test_weibull.cpp
+++ b/test/test_weibull.cpp
@@ -12,15 +12,17 @@
 #  pragma warning (disable : 4127) //  conditional expression is constant.
 #endif
 
-
+#include <boost/math/tools/config.hpp>
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/weibull.hpp>
     using boost::math::weibull_distribution;
-#include <boost/math/tools/test.hpp> 
+#include "../include_private/boost/math/tools/test.hpp"
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_weibull_cdf_double.cu b/test/test_weibull_cdf_double.cu
new file mode 100644
index 0000000000..65efbe2528
--- /dev/null
+++ b/test/test_weibull_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_cdf_float.cu b/test/test_weibull_cdf_float.cu
new file mode 100644
index 0000000000..65c3ce1ffc
--- /dev/null
+++ b/test/test_weibull_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_cdf_nvrtc_double.cpp b/test/test_weibull_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..60d5ff5afb
--- /dev/null
+++ b/test/test_weibull_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull_cdf_nvrtc_float.cpp b/test/test_weibull_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..5085b2f7dd
--- /dev/null
+++ b/test/test_weibull_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull_pdf_double.cu b/test/test_weibull_pdf_double.cu
new file mode 100644
index 0000000000..645df4c0ad
--- /dev/null
+++ b/test/test_weibull_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_pdf_float.cu b/test/test_weibull_pdf_float.cu
new file mode 100644
index 0000000000..f1e6917f03
--- /dev/null
+++ b/test/test_weibull_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_pdf_nvrtc_double.cpp b/test/test_weibull_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..2e5e237b20
--- /dev/null
+++ b/test/test_weibull_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull_pdf_nvrtc_float.cpp b/test/test_weibull_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..6c3c5202c1
--- /dev/null
+++ b/test/test_weibull_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull_quan_double.cu b/test/test_weibull_quan_double.cu
new file mode 100644
index 0000000000..2f05006022
--- /dev/null
+++ b/test/test_weibull_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_quan_float.cu b/test/test_weibull_quan_float.cu
new file mode 100644
index 0000000000..3027e14dda
--- /dev/null
+++ b/test/test_weibull_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::weibull_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_weibull_quan_nvrtc_double.cpp b/test/test_weibull_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..aed31865e8
--- /dev/null
+++ b/test/test_weibull_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_weibull_quan_nvrtc_float.cpp b/test/test_weibull_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..98997b354b
--- /dev/null
+++ b/test/test_weibull_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/weibull.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/weibull.hpp>
+extern "C" __global__ 
+void test_weibull_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::weibull_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_weibull_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_weibull_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_weibull_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::weibull_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 9ed738f259302c5bc9fc869f8294b858dcbcf64a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 27 Aug 2024 17:19:37 -0400
Subject: [PATCH 363/399] Fix policy macro definition for MSVC platforms

---
 test/test_igamma_inv.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_igamma_inv.cpp b/test/test_igamma_inv.cpp
index a88c3666be..17e0bfb54f 100644
--- a/test/test_igamma_inv.cpp
+++ b/test/test_igamma_inv.cpp
@@ -14,7 +14,7 @@
 #  pragma GCC diagnostic push 
 #  pragma GCC diagnostic ignored "-Wliteral-range"
 #endif
-
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #include "test_igamma_inv.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)

From adf8abd346cbc7c11b075f47b26b2542f6d9cfba Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 13:45:53 -0400
Subject: [PATCH 364/399] Apply GPU markers to ibeta_inv_ab

Remove NVRTC workaround

Apply GPU markers to ibeta_inverse

Apply GPU markers to t_dist_inv

Fix warning suppression

Add dispatch function and remove workaround

Move disabling block

Make binomial GPU enabled

Add SYCL testing of ibeta

Add SYCL testing of ibeta_inv

Add SYCL testing of ibeta_inv_ab

Add SYCL testing of full beta suite

Add makers to fwd decls

Add special forward decls for NVRTC

Add betac nvrtc testing

Add betac CUDA testing

Add ibeta CUDA testing

Add ibeta NVRTC testing

Add ibetac NVRTC testing

Add ibeta_derviative testing to nvrtc

Add ibeta_derivative CUDA testing

Add cbrt policy overload for NVRTC

Fix NVRTC definition of BOOST_MATH_IF_CONSTEXPR

Add ibeta_inv and ibetac_inv NVRTC testing

Fix make pair helper on device

Add CUDA testing of ibeta_inv* and ibetac_inv*

Move location so that it also works on NVRTC

Add NVRTC testing of ibeta_inv* and ibetac_inv*

Fixup test sets since they ignore the policy

Make the beta dist GPU compatible

Add beta dist SYCL testing

Add beta dist CUDA testing

Add beta dist NVRTC testing
---
 include/boost/math/distributions/beta.hpp     |  87 +++----
 .../boost/math/policies/error_handling.hpp    |  31 +--
 include/boost/math/special_functions/beta.hpp |  17 +-
 .../boost/math/special_functions/binomial.hpp |  17 +-
 include/boost/math/special_functions/cbrt.hpp |  28 ++-
 .../special_functions/detail/ibeta_inv_ab.hpp |  42 ++--
 .../detail/ibeta_inverse.hpp                  |  90 +++----
 .../detail/t_distribution_inv.hpp             |  31 +--
 .../boost/math/special_functions/gamma.hpp    |  77 +++---
 .../boost/math/special_functions/math_fwd.hpp |  58 +++--
 include/boost/math/tools/config.hpp           |   2 +-
 test/cuda_jamfile                             |  25 ++
 test/nvrtc_jamfile                            |  27 +++
 test/sycl_jamfile                             |   5 +
 test/test_bessel_i.cpp                        |   2 +-
 test/test_bessel_j.cpp                        |   2 +-
 test/test_bessel_k.cpp                        |   2 +-
 test/test_bessel_y.cpp                        |   2 +-
 test/test_beta.cpp                            |  12 +-
 test/test_beta.hpp                            |   6 +-
 test/test_beta_dist.cpp                       |  10 +-
 test/test_beta_dist_cdf_double.cu             | 109 +++++++++
 test/test_beta_dist_cdf_float.cu              | 109 +++++++++
 test/test_beta_dist_cdf_nvrtc_double.cpp      | 191 +++++++++++++++
 test/test_beta_dist_cdf_nvrtc_float.cpp       | 191 +++++++++++++++
 test/test_beta_dist_pdf_double.cu             | 109 +++++++++
 test/test_beta_dist_pdf_float.cu              | 109 +++++++++
 test/test_beta_dist_pdf_nvrtc_double.cpp      | 191 +++++++++++++++
 test/test_beta_dist_pdf_nvrtc_float.cpp       | 191 +++++++++++++++
 test/test_beta_dist_quan_double.cu            | 109 +++++++++
 test/test_beta_dist_quan_float.cu             | 109 +++++++++
 test/test_beta_dist_quan_nvrtc_double.cpp     | 191 +++++++++++++++
 test/test_beta_dist_quan_nvrtc_float.cpp      | 191 +++++++++++++++
 test/test_betac_double.cu                     | 146 ++++++++++++
 test/test_betac_float.cu                      | 146 ++++++++++++
 test/test_betac_nvrtc_double.cpp              | 196 ++++++++++++++++
 test/test_betac_nvrtc_float.cpp               | 196 ++++++++++++++++
 test/test_erf.cpp                             |   2 +-
 test/test_holtsmark.cpp                       |   2 +-
 test/test_ibeta.cpp                           |  11 +
 test/test_ibeta.hpp                           |   3 +-
 test/test_ibeta_derivative.cpp                |   2 +-
 test/test_ibeta_derivative_double.cu          | 149 ++++++++++++
 test/test_ibeta_derivative_float.cu           | 149 ++++++++++++
 test/test_ibeta_derivative_nvrtc_double.cpp   | 207 ++++++++++++++++
 test/test_ibeta_derivative_nvrtc_float.cpp    | 207 ++++++++++++++++
 test/test_ibeta_double.cu                     | 149 ++++++++++++
 test/test_ibeta_float.cu                      | 149 ++++++++++++
 test/test_ibeta_inv.cpp                       |  11 +
 test/test_ibeta_inv.hpp                       |   5 +-
 test/test_ibeta_inv_ab.cpp                    |  11 +
 test/test_ibeta_inv_ab.hpp                    |   3 +-
 test/test_ibeta_inv_double.cu                 | 149 ++++++++++++
 test/test_ibeta_inv_float.cu                  | 149 ++++++++++++
 test/test_ibeta_inv_nvrtc_double.cpp          | 207 ++++++++++++++++
 test/test_ibeta_inv_nvrtc_float.cpp           | 207 ++++++++++++++++
 test/test_ibeta_inva_double.cu                | 149 ++++++++++++
 test/test_ibeta_inva_float.cu                 | 149 ++++++++++++
 test/test_ibeta_inva_nvrtc_double.cpp         | 220 ++++++++++++++++++
 test/test_ibeta_inva_nvrtc_float.cpp          | 220 ++++++++++++++++++
 test/test_ibeta_invb_double.cu                | 149 ++++++++++++
 test/test_ibeta_invb_float.cu                 | 149 ++++++++++++
 test/test_ibeta_invb_nvrtc_double.cpp         | 220 ++++++++++++++++++
 test/test_ibeta_invb_nvrtc_float.cpp          | 220 ++++++++++++++++++
 test/test_ibeta_nvrtc_double.cpp              | 207 ++++++++++++++++
 test/test_ibeta_nvrtc_float.cpp               | 207 ++++++++++++++++
 test/test_ibetac_inv_double.cu                | 149 ++++++++++++
 test/test_ibetac_inv_float.cu                 | 149 ++++++++++++
 test/test_ibetac_inv_nvrtc_double.cpp         | 207 ++++++++++++++++
 test/test_ibetac_inv_nvrtc_float.cpp          | 207 ++++++++++++++++
 test/test_ibetac_inva_double.cu               | 149 ++++++++++++
 test/test_ibetac_inva_float.cu                | 149 ++++++++++++
 test/test_ibetac_inva_nvrtc_double.cpp        | 220 ++++++++++++++++++
 test/test_ibetac_inva_nvrtc_float.cpp         | 220 ++++++++++++++++++
 test/test_ibetac_invb_double.cu               | 149 ++++++++++++
 test/test_ibetac_invb_float.cu                | 149 ++++++++++++
 test/test_ibetac_invb_nvrtc_double.cpp        | 220 ++++++++++++++++++
 test/test_ibetac_invb_nvrtc_float.cpp         | 220 ++++++++++++++++++
 test/test_ibetac_nvrtc_double.cpp             | 207 ++++++++++++++++
 test/test_ibetac_nvrtc_float.cpp              | 207 ++++++++++++++++
 test/test_igamma.cpp                          |   2 +-
 test/test_igamma_inv.cpp                      |   2 +-
 test/test_igamma_inva.cpp                     |   2 +-
 test/test_landau.cpp                          |   2 +-
 test/test_mapairy.cpp                         |   2 +-
 85 files changed, 9093 insertions(+), 238 deletions(-)
 create mode 100644 test/test_beta_dist_cdf_double.cu
 create mode 100644 test/test_beta_dist_cdf_float.cu
 create mode 100644 test/test_beta_dist_cdf_nvrtc_double.cpp
 create mode 100644 test/test_beta_dist_cdf_nvrtc_float.cpp
 create mode 100644 test/test_beta_dist_pdf_double.cu
 create mode 100644 test/test_beta_dist_pdf_float.cu
 create mode 100644 test/test_beta_dist_pdf_nvrtc_double.cpp
 create mode 100644 test/test_beta_dist_pdf_nvrtc_float.cpp
 create mode 100644 test/test_beta_dist_quan_double.cu
 create mode 100644 test/test_beta_dist_quan_float.cu
 create mode 100644 test/test_beta_dist_quan_nvrtc_double.cpp
 create mode 100644 test/test_beta_dist_quan_nvrtc_float.cpp
 create mode 100644 test/test_betac_double.cu
 create mode 100644 test/test_betac_float.cu
 create mode 100644 test/test_betac_nvrtc_double.cpp
 create mode 100644 test/test_betac_nvrtc_float.cpp
 create mode 100644 test/test_ibeta_derivative_double.cu
 create mode 100644 test/test_ibeta_derivative_float.cu
 create mode 100644 test/test_ibeta_derivative_nvrtc_double.cpp
 create mode 100644 test/test_ibeta_derivative_nvrtc_float.cpp
 create mode 100644 test/test_ibeta_double.cu
 create mode 100644 test/test_ibeta_float.cu
 create mode 100644 test/test_ibeta_inv_double.cu
 create mode 100644 test/test_ibeta_inv_float.cu
 create mode 100644 test/test_ibeta_inv_nvrtc_double.cpp
 create mode 100644 test/test_ibeta_inv_nvrtc_float.cpp
 create mode 100644 test/test_ibeta_inva_double.cu
 create mode 100644 test/test_ibeta_inva_float.cu
 create mode 100644 test/test_ibeta_inva_nvrtc_double.cpp
 create mode 100644 test/test_ibeta_inva_nvrtc_float.cpp
 create mode 100644 test/test_ibeta_invb_double.cu
 create mode 100644 test/test_ibeta_invb_float.cu
 create mode 100644 test/test_ibeta_invb_nvrtc_double.cpp
 create mode 100644 test/test_ibeta_invb_nvrtc_float.cpp
 create mode 100644 test/test_ibeta_nvrtc_double.cpp
 create mode 100644 test/test_ibeta_nvrtc_float.cpp
 create mode 100644 test/test_ibetac_inv_double.cu
 create mode 100644 test/test_ibetac_inv_float.cu
 create mode 100644 test/test_ibetac_inv_nvrtc_double.cpp
 create mode 100644 test/test_ibetac_inv_nvrtc_float.cpp
 create mode 100644 test/test_ibetac_inva_double.cu
 create mode 100644 test/test_ibetac_inva_float.cu
 create mode 100644 test/test_ibetac_inva_nvrtc_double.cpp
 create mode 100644 test/test_ibetac_inva_nvrtc_float.cpp
 create mode 100644 test/test_ibetac_invb_double.cu
 create mode 100644 test/test_ibetac_invb_float.cu
 create mode 100644 test/test_ibetac_invb_nvrtc_double.cpp
 create mode 100644 test/test_ibetac_invb_nvrtc_float.cpp
 create mode 100644 test/test_ibetac_nvrtc_double.cpp
 create mode 100644 test/test_ibetac_nvrtc_float.cpp

diff --git a/include/boost/math/distributions/beta.hpp b/include/boost/math/distributions/beta.hpp
index 6c17ffa1a2..fef991a870 100644
--- a/include/boost/math/distributions/beta.hpp
+++ b/include/boost/math/distributions/beta.hpp
@@ -25,12 +25,15 @@
 #ifndef BOOST_MATH_DIST_BETA_HPP
 #define BOOST_MATH_DIST_BETA_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for beta.
 #include <boost/math/distributions/complement.hpp> // complements.
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
 #include <boost/math/tools/roots.hpp> // for root finding.
+#include <boost/math/policies/error_handling.hpp>
 
 #if defined (BOOST_MSVC)
 #  pragma warning(push)
@@ -38,8 +41,6 @@
 // in domain_error_imp in error_handling
 #endif
 
-#include <utility>
-
 namespace boost
 {
   namespace math
@@ -48,7 +49,7 @@ namespace boost
     {
       // Common error checking routines for beta distribution functions:
       template <class RealType, class Policy>
-      inline bool check_alpha(const char* function, const RealType& alpha, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_alpha(const char* function, const RealType& alpha, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(alpha) || (alpha <= 0))
         {
@@ -61,7 +62,7 @@ namespace boost
       } // bool check_alpha
 
       template <class RealType, class Policy>
-      inline bool check_beta(const char* function, const RealType& beta, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_beta(const char* function, const RealType& beta, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(beta) || (beta <= 0))
         {
@@ -74,7 +75,7 @@ namespace boost
       } // bool check_beta
 
       template <class RealType, class Policy>
-      inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         if((p < 0) || (p > 1) || !(boost::math::isfinite)(p))
         {
@@ -87,7 +88,7 @@ namespace boost
       } // bool check_prob
 
       template <class RealType, class Policy>
-      inline bool check_x(const char* function, const RealType& x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_x(const char* function, const RealType& x, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(x) || (x < 0) || (x > 1))
         {
@@ -100,28 +101,28 @@ namespace boost
       } // bool check_x
 
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& alpha, const RealType& beta, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& alpha, const RealType& beta, RealType* result, const Policy& pol)
       { // Check both alpha and beta.
         return check_alpha(function, alpha, result, pol)
           && check_beta(function, beta, result, pol);
       } // bool check_dist
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_x(const char* function, const RealType& alpha, const RealType& beta, RealType x, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_x(const char* function, const RealType& alpha, const RealType& beta, RealType x, RealType* result, const Policy& pol)
       {
         return check_dist(function, alpha, beta, result, pol)
           && beta_detail::check_x(function, x, result, pol);
       } // bool check_dist_and_x
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, const RealType& alpha, const RealType& beta, RealType p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& alpha, const RealType& beta, RealType p, RealType* result, const Policy& pol)
       {
         return check_dist(function, alpha, beta, result, pol)
           && check_prob(function, p, result, pol);
       } // bool check_dist_and_prob
 
       template <class RealType, class Policy>
-      inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(mean) || (mean <= 0))
         {
@@ -133,7 +134,7 @@ namespace boost
         return true;
       } // bool check_mean
       template <class RealType, class Policy>
-      inline bool check_variance(const char* function, const RealType& variance, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_variance(const char* function, const RealType& variance, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(variance) || (variance <= 0))
         {
@@ -157,7 +158,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      beta_distribution(RealType l_alpha = 1, RealType l_beta = 1) : m_alpha(l_alpha), m_beta(l_beta)
+      BOOST_MATH_GPU_ENABLED beta_distribution(RealType l_alpha = 1, RealType l_beta = 1) : m_alpha(l_alpha), m_beta(l_beta)
       {
         RealType result;
         beta_detail::check_dist(
@@ -167,11 +168,11 @@ namespace boost
           &result, Policy());
       } // beta_distribution constructor.
       // Accessor functions:
-      RealType alpha() const
+      BOOST_MATH_GPU_ENABLED RealType alpha() const
       {
         return m_alpha;
       }
-      RealType beta() const
+      BOOST_MATH_GPU_ENABLED RealType beta() const
       { // .
         return m_beta;
       }
@@ -183,11 +184,11 @@ namespace boost
       // http://www.itl.nist.gov/div898/handbook/eda/section3/eda366h.htm
       // http://www.epi.ucdavis.edu/diagnostictests/betabuster.html
 
-      static RealType find_alpha(
+      BOOST_MATH_GPU_ENABLED static RealType find_alpha(
         RealType mean, // Expected value of mean.
         RealType variance) // Expected value of variance.
       {
-        static const char* function = "boost::math::beta_distribution<%1%>::find_alpha";
+        constexpr auto function = "boost::math::beta_distribution<%1%>::find_alpha";
         RealType result = 0; // of error checks.
         if(false ==
             (
@@ -201,11 +202,11 @@ namespace boost
         return mean * (( (mean * (1 - mean)) / variance)- 1);
       } // RealType find_alpha
 
-      static RealType find_beta(
+      BOOST_MATH_GPU_ENABLED static RealType find_beta(
         RealType mean, // Expected value of mean.
         RealType variance) // Expected value of variance.
       {
-        static const char* function = "boost::math::beta_distribution<%1%>::find_beta";
+        constexpr auto function = "boost::math::beta_distribution<%1%>::find_beta";
         RealType result = 0; // of error checks.
         if(false ==
             (
@@ -223,12 +224,12 @@ namespace boost
       // Estimate alpha & beta from either alpha or beta, and x and probability.
       // Uses for these parameter estimators are unclear.
 
-      static RealType find_alpha(
+      BOOST_MATH_GPU_ENABLED static RealType find_alpha(
         RealType beta, // from beta.
         RealType x, //  x.
         RealType probability) // cdf
       {
-        static const char* function = "boost::math::beta_distribution<%1%>::find_alpha";
+        constexpr auto function = "boost::math::beta_distribution<%1%>::find_alpha";
         RealType result = 0; // of error checks.
         if(false ==
             (
@@ -245,13 +246,13 @@ namespace boost
         return static_cast<RealType>(ibeta_inva(beta, x, probability, Policy()));
       } // RealType find_alpha(beta, a, probability)
 
-      static RealType find_beta(
+      BOOST_MATH_GPU_ENABLED static RealType find_beta(
         // ibeta_invb(T b, T x, T p); (alpha, x, cdf,)
         RealType alpha, // alpha.
         RealType x, // probability x.
         RealType probability) // probability cdf.
       {
-        static const char* function = "boost::math::beta_distribution<%1%>::find_beta";
+        constexpr auto function = "boost::math::beta_distribution<%1%>::find_beta";
         RealType result = 0; // of error checks.
         if(false ==
             (
@@ -281,27 +282,27 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const beta_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const beta_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const beta_distribution<RealType, Policy>&  /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const beta_distribution<RealType, Policy>&  /* dist */)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-      return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const beta_distribution<RealType, Policy>& dist)
     { // Mean of beta distribution = np.
       return  dist.alpha() / (dist.alpha() + dist.beta());
     } // mean
 
     template <class RealType, class Policy>
-    inline RealType variance(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const beta_distribution<RealType, Policy>& dist)
     { // Variance of beta distribution = np(1-p).
       RealType a = dist.alpha();
       RealType b = dist.beta();
@@ -309,9 +310,9 @@ namespace boost
     } // variance
 
     template <class RealType, class Policy>
-    inline RealType mode(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const beta_distribution<RealType, Policy>& dist)
     {
-      static const char* function = "boost::math::mode(beta_distribution<%1%> const&)";
+      constexpr auto function = "boost::math::mode(beta_distribution<%1%> const&)";
 
       RealType result;
       if ((dist.alpha() <= 1))
@@ -343,7 +344,7 @@ namespace boost
     //But WILL be provided by the derived accessor as quantile(0.5).
 
     template <class RealType, class Policy>
-    inline RealType skewness(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const beta_distribution<RealType, Policy>& dist)
     {
       BOOST_MATH_STD_USING // ADL of std functions.
       RealType a = dist.alpha();
@@ -352,7 +353,7 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const beta_distribution<RealType, Policy>& dist)
     {
       RealType a = dist.alpha();
       RealType b = dist.beta();
@@ -363,17 +364,17 @@ namespace boost
     } // kurtosis_excess
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const beta_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const beta_distribution<RealType, Policy>& dist)
     {
       return 3 + kurtosis_excess(dist);
     } // kurtosis
 
     template <class RealType, class Policy>
-    inline RealType pdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)
     { // Probability Density/Mass Function.
       BOOST_FPU_EXCEPTION_GUARD
 
-      static const char* function = "boost::math::pdf(beta_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::pdf(beta_distribution<%1%> const&, %1%)";
 
       BOOST_MATH_STD_USING // for ADL of std functions
 
@@ -428,11 +429,11 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const beta_distribution<RealType, Policy>& dist, const RealType& x)
     { // Cumulative Distribution Function beta.
       BOOST_MATH_STD_USING // for ADL of std functions
 
-      static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";
 
       RealType a = dist.alpha();
       RealType b = dist.beta();
@@ -459,12 +460,12 @@ namespace boost
     } // beta cdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function beta.
 
       BOOST_MATH_STD_USING // for ADL of std functions
 
-      static const char* function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::cdf(beta_distribution<%1%> const&, %1%)";
 
       RealType const& x = c.param;
       beta_distribution<RealType, Policy> const& dist = c.dist;
@@ -495,7 +496,7 @@ namespace boost
     } // beta cdf
 
     template <class RealType, class Policy>
-    inline RealType quantile(const beta_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const beta_distribution<RealType, Policy>& dist, const RealType& p)
     { // Quantile or Percent Point beta function or
       // Inverse Cumulative probability distribution function CDF.
       // Return x (0 <= x <= 1),
@@ -505,7 +506,7 @@ namespace boost
       // will be less than or equal to that value
       // is whatever probability you supplied as an argument.
 
-      static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";
 
       RealType result = 0; // of argument checks:
       RealType a = dist.alpha();
@@ -530,12 +531,12 @@ namespace boost
     } // quantile
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<beta_distribution<RealType, Policy>, RealType>& c)
     { // Complement Quantile or Percent Point beta function .
       // Return the number of expected x for a given
       // complement of the probability q.
 
-      static const char* function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";
+      constexpr auto function = "boost::math::quantile(beta_distribution<%1%> const&, %1%)";
 
       //
       // Error checks:
diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index ce3f1e7ccd..559e70a2f4 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -12,6 +12,7 @@
 #include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/type_traits.hpp>
 #include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/tuple.hpp>
 
 #ifndef BOOST_MATH_HAS_NVRTC
 
@@ -877,20 +878,6 @@ BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, s
 
 } //namespace policies
 
-namespace detail{
-
-//
-// Simple helper function to assist in returning a pair from a single value,
-// that value usually comes from one of the error handlers above:
-//
-template <class T>
-BOOST_MATH_GPU_ENABLED std::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
-{
-   return std::make_pair(val, val);
-}
-
-}
-
 #ifdef _MSC_VER
 #  pragma warning(pop)
 #endif
@@ -1039,7 +1026,21 @@ BOOST_MATH_GPU_ENABLED inline void check_root_iterations(const char* function, b
 } // namespace math
 } // namespace boost
 
-#endif
+#endif // BOOST_MATH_HAS_NVRTC
+
+namespace boost { namespace math { namespace detail {
+
+//
+// Simple helper function to assist in returning a pair from a single value,
+// that value usually comes from one of the error handlers above:
+//
+template <class T>
+BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> pair_from_single(const T& val) BOOST_MATH_NOEXCEPT(T)
+{
+   return boost::math::make_pair(val, val);
+}
+
+}}} // boost::math::detail
 
 #endif // BOOST_MATH_POLICY_ERROR_HANDLING_HPP
 
diff --git a/include/boost/math/special_functions/beta.hpp b/include/boost/math/special_functions/beta.hpp
index 00b8e45bf2..27901a1131 100644
--- a/include/boost/math/special_functions/beta.hpp
+++ b/include/boost/math/special_functions/beta.hpp
@@ -28,14 +28,10 @@
 #include <boost/math/policies/policy.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/constants/constants.hpp>
-
-#ifndef BOOST_MATH_HAS_NVRTC
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/binomial.hpp>
 #include <boost/math/special_functions/factorials.hpp>
 #include <boost/math/tools/roots.hpp>
-#include <cmath>
-#endif
 
 namespace boost{ namespace math{
 
@@ -800,7 +796,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_series(T a, T b, T x, T s0, const boost::math::la
    policies::check_series_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%) in ibeta_series (without lanczos)", max_iter, pol);
    return result;
 }
-
+#endif
 //
 // Continued fraction for the incomplete beta:
 //
@@ -884,7 +880,7 @@ BOOST_MATH_GPU_ENABLED T ibeta_a_step(T a, T b, T x, T y, int k, const Policy& p
 
    return prefix;
 }
-#endif
+
 //
 // This function is only needed for the non-regular incomplete beta,
 // it computes the delta in:
@@ -958,7 +954,6 @@ struct Pn_size<long double>
 #endif
 };
 
-#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Policy& pol, bool normalised)
 {
@@ -1060,7 +1055,7 @@ BOOST_MATH_GPU_ENABLED T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T
    }
    return sum;
 } // template <class T, class Lanczos>T beta_small_b_large_a_series(T a, T b, T x, T y, T s0, T mult, const Lanczos& l, bool normalised)
-#endif
+
 //
 // For integer arguments we can relate the incomplete beta to the
 // complement of the binomial distribution cdf and use this finite sum.
@@ -1130,6 +1125,7 @@ BOOST_MATH_GPU_ENABLED T binomial_ccdf(T n, T k, T x, T y, const Policy& pol)
 // input range and select the right implementation method for
 // each domain:
 //
+
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED T ibeta_imp(T a, T b, T x, const Policy& pol, bool inv, bool normalised, T* p_derivative)
 {
@@ -1749,12 +1745,7 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
 } // namespace math
 } // namespace boost
 
-// TODO(mborland): Get the ibeta_inv working on NVRTC
-#ifndef BOOST_MATH_HAS_NVRTC
-
 #include <boost/math/special_functions/detail/ibeta_inverse.hpp>
 #include <boost/math/special_functions/detail/ibeta_inv_ab.hpp>
 
-#endif
-
 #endif // BOOST_MATH_SPECIAL_BETA_HPP
diff --git a/include/boost/math/special_functions/binomial.hpp b/include/boost/math/special_functions/binomial.hpp
index e776a90bb8..3c49ff30d5 100644
--- a/include/boost/math/special_functions/binomial.hpp
+++ b/include/boost/math/special_functions/binomial.hpp
@@ -10,20 +10,21 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/factorials.hpp>
 #include <boost/math/special_functions/beta.hpp>
 #include <boost/math/policies/error_handling.hpp>
-#include <type_traits>
 
 namespace boost{ namespace math{
 
 template <class T, class Policy>
-T binomial_coefficient(unsigned n, unsigned k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T binomial_coefficient(unsigned n, unsigned k, const Policy& pol)
 {
-   static_assert(!std::is_integral<T>::value, "Type T must not be an integral type");
+   static_assert(!boost::math::is_integral<T>::value, "Type T must not be an integral type");
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::binomial_coefficient<%1%>(unsigned, unsigned)";
+   constexpr auto function = "boost::math::binomial_coefficient<%1%>(unsigned, unsigned)";
    if(k > n)
       return policies::raise_domain_error<T>(function, "The binomial coefficient is undefined for k > n, but got k = %1%.", static_cast<T>(k), pol);
    T result;  // LCOV_EXCL_LINE
@@ -43,9 +44,9 @@ T binomial_coefficient(unsigned n, unsigned k, const Policy& pol)
    {
       // Use the beta function:
       if(k < n - k)
-         result = static_cast<T>(k * beta(static_cast<T>(k), static_cast<T>(n-k+1), pol));
+         result = static_cast<T>(k * boost::math::beta(static_cast<T>(k), static_cast<T>(n-k+1), pol));
       else
-         result = static_cast<T>((n - k) * beta(static_cast<T>(k+1), static_cast<T>(n-k), pol));
+         result = static_cast<T>((n - k) * boost::math::beta(static_cast<T>(k+1), static_cast<T>(n-k), pol));
       if(result == 0)
          return policies::raise_overflow_error<T>(function, nullptr, pol);
       result = 1 / result;
@@ -59,7 +60,7 @@ T binomial_coefficient(unsigned n, unsigned k, const Policy& pol)
 // we'll promote to double:
 //
 template <>
-inline float binomial_coefficient<float, policies::policy<> >(unsigned n, unsigned k, const policies::policy<>&)
+BOOST_MATH_GPU_ENABLED inline float binomial_coefficient<float, policies::policy<> >(unsigned n, unsigned k, const policies::policy<>&)
 {
    typedef policies::normalise<
        policies::policy<>,
@@ -71,7 +72,7 @@ inline float binomial_coefficient<float, policies::policy<> >(unsigned n, unsign
 }
 
 template <class T>
-inline T binomial_coefficient(unsigned n, unsigned k)
+BOOST_MATH_GPU_ENABLED inline T binomial_coefficient(unsigned n, unsigned k)
 {
    return binomial_coefficient<T>(n, k, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/cbrt.hpp b/include/boost/math/special_functions/cbrt.hpp
index fb05996cf1..7fdf78d014 100644
--- a/include/boost/math/special_functions/cbrt.hpp
+++ b/include/boost/math/special_functions/cbrt.hpp
@@ -11,15 +11,16 @@
 #pragma once
 #endif
 
-#ifndef __CUDACC_RTC__
-
 #include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <boost/math/tools/rational.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
-#include <type_traits>
-#include <cstdint>
 
 namespace boost{ namespace math{
 
@@ -174,19 +175,30 @@ BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type cbrt(T z)
 } // namespace math
 } // namespace boost
 
-#else
+#else // Special NVRTC handling
 
 namespace boost {
 namespace math {
 
 template <typename T>
-__host__ __device__ T cbrt(T x)
+BOOST_MATH_GPU_ENABLED double cbrt(T x)
+{
+   return ::cbrt(x);
+}
+
+BOOST_MATH_GPU_ENABLED inline float cbrt(float x)
+{
+   return ::cbrtf(x);
+}
+
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED double cbrt(T x, const Policy&)
 {
    return ::cbrt(x);
 }
 
-template <>
-__host__ __device__ float cbrt(float x)
+template <typename Policy>
+BOOST_MATH_GPU_ENABLED float cbrt(float x, const Policy&)
 {
    return ::cbrtf(x);
 }
diff --git a/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp b/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
index 9e30db2a37..aab18f50f1 100644
--- a/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
+++ b/include/boost/math/special_functions/detail/ibeta_inv_ab.hpp
@@ -17,17 +17,19 @@
 #pragma once
 #endif
 
-#include <cstdint>
-#include <utility>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/toms748_solve.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
 template <class T, class Policy>
 struct beta_inv_ab_t
 {
-   beta_inv_ab_t(T b_, T z_, T p_, bool invert_, bool swap_ab_) : b(b_), z(z_), p(p_), invert(invert_), swap_ab(swap_ab_) {}
-   T operator()(T a)
+   BOOST_MATH_GPU_ENABLED beta_inv_ab_t(T b_, T z_, T p_, bool invert_, bool swap_ab_) : b(b_), z(z_), p(p_), invert(invert_), swap_ab(swap_ab_) {}
+   BOOST_MATH_GPU_ENABLED T operator()(T a)
    {
       return invert ? 
          p - boost::math::ibetac(swap_ab ? b : a, swap_ab ? a : b, z, Policy()) 
@@ -39,7 +41,7 @@ struct beta_inv_ab_t
 };
 
 template <class T, class Policy>
-T inverse_negative_binomial_cornish_fisher(T n, T sf, T sfc, T p, T q, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T inverse_negative_binomial_cornish_fisher(T n, T sf, T sfc, T p, T q, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    // mean:
@@ -72,7 +74,7 @@ T inverse_negative_binomial_cornish_fisher(T n, T sf, T sfc, T p, T q, const Pol
 }
 
 template <class T, class Policy>
-T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab, const Policy& pol)
 {
    BOOST_MATH_STD_USING  // for ADL of std lib math functions
    //
@@ -121,11 +123,11 @@ T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab,
       //
       if((p < q) != swap_ab)
       {
-         guess = (std::min)(T(b * 2), T(1));
+         guess = BOOST_MATH_GPU_SAFE_MIN(T(b * 2), T(1));
       }
       else
       {
-         guess = (std::min)(T(b / 2), T(1));
+         guess = BOOST_MATH_GPU_SAFE_MIN(T(b / 2), T(1));
       }
    }
    if(n * n * n * u * sf > 0.005)
@@ -138,11 +140,11 @@ T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab,
       //
       if((p < q) != swap_ab)
       {
-         guess = (std::min)(T(b * 2), T(10));
+         guess = BOOST_MATH_GPU_SAFE_MIN(T(b * 2), T(10));
       }
       else
       {
-         guess = (std::min)(T(b / 2), T(10));
+         guess = BOOST_MATH_GPU_SAFE_MIN(T(b / 2), T(10));
       }
    }
    else
@@ -151,8 +153,8 @@ T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab,
    //
    // Max iterations permitted:
    //
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
-   std::pair<T, T> r = bracket_and_solve_root(f, guess, factor, swap_ab ? true : false, tol, max_iter, pol);
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::pair<T, T> r = bracket_and_solve_root(f, guess, factor, swap_ab ? true : false, tol, max_iter, pol);
    if(max_iter >= policies::get_max_root_iterations<Policy>())
       return policies::raise_evaluation_error<T>("boost::math::ibeta_invab_imp<%1%>(%1%,%1%,%1%)", "Unable to locate the root within a reasonable number of iterations, closest approximation so far was %1%", r.first, pol);
    return (r.first + r.second) / 2;
@@ -161,7 +163,7 @@ T ibeta_inv_ab_imp(const T& b, const T& z, const T& p, const T& q, bool swap_ab,
 } // namespace detail
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type 
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<RT1, RT2, RT3>::type 
       ibeta_inva(RT1 b, RT2 x, RT3 p, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
@@ -194,7 +196,7 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<RT1, RT2, RT3>::type
       ibetac_inva(RT1 b, RT2 x, RT3 q, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
@@ -227,7 +229,7 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<RT1, RT2, RT3>::type
       ibeta_invb(RT1 a, RT2 x, RT3 p, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
@@ -260,7 +262,7 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<RT1, RT2, RT3>::type
       ibetac_invb(RT1 a, RT2 x, RT3 q, const Policy& pol)
 {
    constexpr auto function = "boost::math::ibeta_invb<%1%>(%1%, %1%, %1%)";
@@ -293,28 +295,28 @@ typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type 
          ibeta_inva(RT1 b, RT2 x, RT3 p)
 {
    return boost::math::ibeta_inva(b, x, p, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type 
          ibetac_inva(RT1 b, RT2 x, RT3 q)
 {
    return boost::math::ibetac_inva(b, x, q, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type 
          ibeta_invb(RT1 a, RT2 x, RT3 p)
 {
    return boost::math::ibeta_invb(a, x, p, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type 
          ibetac_invb(RT1 a, RT2 x, RT3 q)
 {
    return boost::math::ibetac_invb(a, x, q, policies::policy<>());
diff --git a/include/boost/math/special_functions/detail/ibeta_inverse.hpp b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
index 9e4fb08d4e..90f6e90705 100644
--- a/include/boost/math/special_functions/detail/ibeta_inverse.hpp
+++ b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
@@ -11,12 +11,14 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/roots.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/special_functions/beta.hpp>
 #include <boost/math/special_functions/erf.hpp>
-#include <boost/math/tools/roots.hpp>
 #include <boost/math/special_functions/detail/t_distribution_inv.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
-#include <boost/math/tools/precision.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
@@ -27,12 +29,12 @@ namespace boost{ namespace math{ namespace detail{
 template <class T>
 struct temme_root_finder
 {
-   temme_root_finder(const T t_, const T a_) : t(t_), a(a_) {
+   BOOST_MATH_GPU_ENABLED temme_root_finder(const T t_, const T a_) : t(t_), a(a_) {
       BOOST_MATH_ASSERT(
          math::tools::epsilon<T>() <= a && !(boost::math::isinf)(a));
    }
 
-   boost::math::tuple<T, T> operator()(T x)
+   BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T> operator()(T x)
    {
       BOOST_MATH_STD_USING // ADL of std names
 
@@ -52,7 +54,7 @@ struct temme_root_finder
 // Section 2.
 //
 template <class T, class Policy>
-T temme_method_1_ibeta_inverse(T a, T b, T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T temme_method_1_ibeta_inverse(T a, T b, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -138,7 +140,7 @@ T temme_method_1_ibeta_inverse(T a, T b, T z, const Policy& pol)
 // Section 3.
 //
 template <class T, class Policy>
-T temme_method_2_ibeta_inverse(T /*a*/, T /*b*/, T z, T r, T theta, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T temme_method_2_ibeta_inverse(T /*a*/, T /*b*/, T z, T r, T theta, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -315,7 +317,7 @@ T temme_method_2_ibeta_inverse(T /*a*/, T /*b*/, T z, T r, T theta, const Policy
 // Section 4.
 //
 template <class T, class Policy>
-T temme_method_3_ibeta_inverse(T a, T b, T p, T q, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T temme_method_3_ibeta_inverse(T a, T b, T p, T q, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names
 
@@ -420,10 +422,10 @@ T temme_method_3_ibeta_inverse(T a, T b, T p, T q, const Policy& pol)
 template <class T, class Policy>
 struct ibeta_roots
 {
-   ibeta_roots(T _a, T _b, T t, bool inv = false)
+   BOOST_MATH_GPU_ENABLED ibeta_roots(T _a, T _b, T t, bool inv = false)
       : a(_a), b(_b), target(t), invert(inv) {}
 
-   boost::math::tuple<T, T, T> operator()(T x)
+   BOOST_MATH_GPU_ENABLED boost::math::tuple<T, T, T> operator()(T x)
    {
       BOOST_MATH_STD_USING // ADL of std names
 
@@ -457,7 +459,7 @@ struct ibeta_roots
 };
 
 template <class T, class Policy>
-T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
+BOOST_MATH_GPU_ENABLED T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
 {
    BOOST_MATH_STD_USING  // For ADL of math functions.
 
@@ -487,8 +489,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
          return p;
       }
       // Change things around so we can handle as b == 1 special case below:
-      std::swap(a, b);
-      std::swap(p, q);
+      BOOST_MATH_GPU_SAFE_SWAP(a, b);
+      BOOST_MATH_GPU_SAFE_SWAP(p, q);
       invert = true;
    }
    //
@@ -524,8 +526,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
       }
       else if(b > 0.5f)
       {
-         std::swap(a, b);
-         std::swap(p, q);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(p, q);
          invert = !invert;
       }
    }
@@ -559,7 +561,7 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
          y = -boost::math::expm1(boost::math::log1p(-q, pol) / a, pol);
       }
       if(invert)
-         std::swap(x, y);
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
       if(py)
          *py = y;
       return x;
@@ -574,12 +576,12 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
       //
       if(p > 0.5)
       {
-         std::swap(a, b);
-         std::swap(p, q);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(p, q);
          invert = !invert;
       }
-      T minv = (std::min)(a, b);
-      T maxv = (std::max)(a, b);
+      T minv = BOOST_MATH_GPU_SAFE_MIN(a, b);
+      T maxv = BOOST_MATH_GPU_SAFE_MAX(a, b);
       if((sqrt(minv) > (maxv - minv)) && (minv > 5))
       {
          //
@@ -630,8 +632,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
             //
             if(a < b)
             {
-               std::swap(a, b);
-               std::swap(p, q);
+               BOOST_MATH_GPU_SAFE_SWAP(a, b);
+               BOOST_MATH_GPU_SAFE_SWAP(p, q);
                invert = !invert;
             }
             //
@@ -694,8 +696,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
       }
       if(fs < 0)
       {
-         std::swap(a, b);
-         std::swap(p, q);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(p, q);
          invert = !invert;
          xs = 1 - xs;
       }
@@ -758,9 +760,9 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
 
       if(ps < 0)
       {
-         std::swap(a, b);
-         std::swap(p, q);
-         std::swap(xs, xs2);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(p, q);
+         BOOST_MATH_GPU_SAFE_SWAP(xs, xs2);
          invert = !invert;
       }
       //
@@ -823,8 +825,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
       //
       if(b < a)
       {
-         std::swap(a, b);
-         std::swap(p, q);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(p, q);
          invert = !invert;
       }
       if (a < tools::min_value<T>())
@@ -890,9 +892,9 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
    //
    if(x > 0.5)
    {
-      std::swap(a, b);
-      std::swap(p, q);
-      std::swap(x, y);
+      BOOST_MATH_GPU_SAFE_SWAP(a, b);
+      BOOST_MATH_GPU_SAFE_SWAP(p, q);
+      BOOST_MATH_GPU_SAFE_SWAP(x, y);
       invert = !invert;
       T l = 1 - upper;
       T u = 1 - lower;
@@ -922,8 +924,8 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
       if(x < lower)
          x = lower;
    }
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
-   std::uintmax_t max_iter_used = 0;
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::uintmax_t max_iter_used = 0;
    //
    // Figure out how many digits to iterate towards:
    //
@@ -946,7 +948,13 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
    // Now iterate, we can use either p or q as the target here
    // depending on which is smaller:
    //
+   // Since we can't use halley_iterate on device we use newton raphson
+   //
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    x = boost::math::tools::halley_iterate(
+   #else
+   x = boost::math::tools::newton_raphson_iterate(
+   #endif
       boost::math::detail::ibeta_roots<T, Policy>(a, b, (p < q ? p : q), (p < q ? false : true)), x, lower, upper, digits, max_iter);
    policies::check_root_iterations<T>("boost::math::ibeta<%1%>(%1%, %1%, %1%)", max_iter + max_iter_used, pol);
    //
@@ -968,7 +976,7 @@ T ibeta_inv_imp(T a, T b, T p, T q, const Policy& pol, T* py)
 } // namespace detail
 
 template <class T1, class T2, class T3, class T4, class Policy>
-inline typename tools::promote_args<T1, T2, T3, T4>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibeta_inv(T1 a, T2 b, T3 p, T4* py, const Policy& pol)
 {
    constexpr auto function = "boost::math::ibeta_inv<%1%>(%1%,%1%,%1%)";
@@ -1003,14 +1011,14 @@ inline typename tools::promote_args<T1, T2, T3, T4>::type
 }
 
 template <class T1, class T2, class T3, class T4>
-inline typename tools::promote_args<T1, T2, T3, T4>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibeta_inv(T1 a, T2 b, T3 p, T4* py)
 {
    return ibeta_inv(a, b, p, py, policies::policy<>());
 }
 
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type
    ibeta_inv(T1 a, T2 b, T3 p)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
@@ -1018,7 +1026,7 @@ inline typename tools::promote_args<T1, T2, T3>::type
 }
 
 template <class T1, class T2, class T3, class Policy>
-inline typename tools::promote_args<T1, T2, T3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type
    ibeta_inv(T1 a, T2 b, T3 p, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
@@ -1026,7 +1034,7 @@ inline typename tools::promote_args<T1, T2, T3>::type
 }
 
 template <class T1, class T2, class T3, class T4, class Policy>
-inline typename tools::promote_args<T1, T2, T3, T4>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibetac_inv(T1 a, T2 b, T3 q, T4* py, const Policy& pol)
 {
    constexpr auto function = "boost::math::ibetac_inv<%1%>(%1%,%1%,%1%)";
@@ -1061,14 +1069,14 @@ inline typename tools::promote_args<T1, T2, T3, T4>::type
 }
 
 template <class T1, class T2, class T3, class T4>
-inline typename tools::promote_args<T1, T2, T3, T4>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type
    ibetac_inv(T1 a, T2 b, T3 q, T4* py)
 {
    return ibetac_inv(a, b, q, py, policies::policy<>());
 }
 
 template <class RT1, class RT2, class RT3>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibetac_inv(RT1 a, RT2 b, RT3 q)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
@@ -1076,7 +1084,7 @@ inline typename tools::promote_args<RT1, RT2, RT3>::type
 }
 
 template <class RT1, class RT2, class RT3, class Policy>
-inline typename tools::promote_args<RT1, RT2, RT3>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, RT3>::type
    ibetac_inv(RT1 a, RT2 b, RT3 q, const Policy& pol)
 {
    typedef typename tools::promote_args<RT1, RT2, RT3>::type result_type;
diff --git a/include/boost/math/special_functions/detail/t_distribution_inv.hpp b/include/boost/math/special_functions/detail/t_distribution_inv.hpp
index 9209b6d405..22e1d11f02 100644
--- a/include/boost/math/special_functions/detail/t_distribution_inv.hpp
+++ b/include/boost/math/special_functions/detail/t_distribution_inv.hpp
@@ -11,6 +11,9 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/special_functions/cbrt.hpp>
 #include <boost/math/special_functions/round.hpp>
 #include <boost/math/special_functions/trunc.hpp>
@@ -24,7 +27,7 @@ namespace boost{ namespace math{ namespace detail{
 // Communications of the ACM, 13(10): 619-620, Oct., 1970.
 //
 template <class T, class Policy>
-T inverse_students_t_hill(T ndf, T u, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T inverse_students_t_hill(T ndf, T u, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    BOOST_MATH_ASSERT(u <= 0.5);
@@ -74,7 +77,7 @@ T inverse_students_t_hill(T ndf, T u, const Policy& pol)
 // Journal of Computational Finance, Vol 9 Issue 4, pp 37-73, Summer 2006
 //
 template <class T, class Policy>
-T inverse_students_t_tail_series(T df, T v, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T inverse_students_t_tail_series(T df, T v, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    // Tail series expansion, see section 6 of Shaw's paper.
@@ -125,7 +128,7 @@ T inverse_students_t_tail_series(T df, T v, const Policy& pol)
 }
 
 template <class T, class Policy>
-T inverse_students_t_body_series(T df, T u, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T inverse_students_t_body_series(T df, T u, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    //
@@ -204,7 +207,7 @@ T inverse_students_t_body_series(T df, T u, const Policy& pol)
 }
 
 template <class T, class Policy>
-T inverse_students_t(T df, T u, T v, const Policy& pol, bool* pexact = nullptr)
+BOOST_MATH_GPU_ENABLED T inverse_students_t(T df, T u, T v, const Policy& pol, bool* pexact = nullptr)
 {
    //
    // df = number of degrees of freedom.
@@ -220,7 +223,7 @@ T inverse_students_t(T df, T u, T v, const Policy& pol, bool* pexact = nullptr)
    if(u > v)
    {
       // function is symmetric, invert it:
-      std::swap(u, v);
+      BOOST_MATH_GPU_SAFE_SWAP(u, v);
       invert = true;
    }
    if((floor(df) == df) && (df < 20))
@@ -416,7 +419,7 @@ T inverse_students_t(T df, T u, T v, const Policy& pol, bool* pexact = nullptr)
 }
 
 template <class T, class Policy>
-inline T find_ibeta_inv_from_t_dist(T a, T p, T /*q*/, T* py, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T find_ibeta_inv_from_t_dist(T a, T p, T /*q*/, T* py, const Policy& pol)
 {
    T u = p / 2;
    T v = 1 - u;
@@ -427,7 +430,7 @@ inline T find_ibeta_inv_from_t_dist(T a, T p, T /*q*/, T* py, const Policy& pol)
 }
 
 template <class T, class Policy>
-inline T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const std::false_type*)
+BOOST_MATH_GPU_ENABLED inline T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const boost::math::false_type*)
 {
    BOOST_MATH_STD_USING
    //
@@ -450,12 +453,12 @@ inline T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const std::f
 }
 
 template <class T, class Policy>
-T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const std::true_type*)
+BOOST_MATH_GPU_ENABLED T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const boost::math::true_type*)
 {
    BOOST_MATH_STD_USING
    bool invert = false;
    if((df < 2) && (floor(df) != df))
-      return boost::math::detail::fast_students_t_quantile_imp(df, p, pol, static_cast<std::false_type*>(nullptr));
+      return boost::math::detail::fast_students_t_quantile_imp(df, p, pol, static_cast<boost::math::false_type*>(nullptr));
    if(p > 0.5)
    {
       p = 1 - p;
@@ -521,7 +524,7 @@ T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const std::true_typ
 }
 
 template <class T, class Policy>
-inline T fast_students_t_quantile(T df, T p, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T fast_students_t_quantile(T df, T p, const Policy& pol)
 {
    typedef typename policies::evaluation<T, Policy>::type value_type;
    typedef typename policies::normalise<
@@ -531,12 +534,12 @@ inline T fast_students_t_quantile(T df, T p, const Policy& pol)
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   typedef std::integral_constant<bool,
-      (std::numeric_limits<T>::digits <= 53)
+   typedef boost::math::integral_constant<bool,
+      (boost::math::numeric_limits<T>::digits <= 53)
        &&
-      (std::numeric_limits<T>::is_specialized)
+      (boost::math::numeric_limits<T>::is_specialized)
        &&
-      (std::numeric_limits<T>::radix == 2)
+      (boost::math::numeric_limits<T>::radix == 2)
    > tag_type;
    return policies::checked_narrowing_cast<T, forwarding_policy>(fast_students_t_quantile_imp(static_cast<value_type>(df), static_cast<value_type>(p), pol, static_cast<tag_type*>(nullptr)), "boost::math::students_t_quantile<%1%>(%1%,%1%,%1%)");
 }
diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 186befb612..41c85936dd 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -1735,10 +1735,50 @@ BOOST_MATH_GPU_ENABLED T gamma_incomplete_imp(T a, T x, bool normalised, bool in
 //
 // Ratios of two gamma functions:
 //
+template <class T, class Policy, class Lanczos>
+BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos_final(T z, T delta, const Policy& pol, const Lanczos&)
+{
+   BOOST_MATH_STD_USING
+
+   T zgh = static_cast<T>(z + T(Lanczos::g()) - constants::half<T>());
+   T result;
+   if(z + delta == z)
+   {
+      if (fabs(delta / zgh) < boost::math::tools::epsilon<T>())
+      {
+         // We have:
+         // result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
+         // 0.5 - z == -z
+         // log1p(delta / zgh) = delta / zgh = delta / z
+         // multiplying we get -delta.
+         result = exp(-delta);
+      }
+      else
+         // from the pow formula below... but this may actually be wrong, we just can't really calculate it :(
+         result = 1;
+   }
+   else
+   {
+      if(fabs(delta) < 10)
+      {
+         result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
+      }
+      else
+      {
+         result = pow(T(zgh / (zgh + delta)), T(z - constants::half<T>()));
+      }
+      // Split the calculation up to avoid spurious overflow:
+      result *= Lanczos::lanczos_sum(z) / Lanczos::lanczos_sum(T(z + delta));
+   }
+   result *= pow(T(constants::e<T>() / (zgh + delta)), delta);
+   return result;
+}
+
 template <class T, class Policy, class Lanczos>
 BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Policy& pol, const Lanczos& l)
 {
    BOOST_MATH_STD_USING
+
    if(z < tools::epsilon<T>())
    {
       //
@@ -1752,7 +1792,7 @@ BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Poli
       //
       if(boost::math::max_factorial<T>::value < delta)
       {
-         T ratio = tgamma_delta_ratio_imp_lanczos(delta, T(boost::math::max_factorial<T>::value - delta), pol, l);
+         T ratio = tgamma_delta_ratio_imp_lanczos_final(T(delta), T(boost::math::max_factorial<T>::value - delta), pol, l);
          ratio *= z;
          ratio *= boost::math::unchecked_factorial<T>(boost::math::max_factorial<T>::value - 1);
          return 1 / ratio;
@@ -1773,39 +1813,10 @@ BOOST_MATH_GPU_ENABLED T tgamma_delta_ratio_imp_lanczos(T z, T delta, const Poli
          #endif
       }
    }
-   T zgh = static_cast<T>(z + T(Lanczos::g()) - constants::half<T>());
-   T result;
-   if(z + delta == z)
-   {
-      if (fabs(delta / zgh) < boost::math::tools::epsilon<T>())
-      {
-         // We have:
-         // result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
-         // 0.5 - z == -z
-         // log1p(delta / zgh) = delta / zgh = delta / z
-         // multiplying we get -delta.
-         result = exp(-delta);
-      }
-      else
-         // from the pow formula below... but this may actually be wrong, we just can't really calculate it :(
-         result = 1;
-   }
-   else
-   {
-      if(fabs(delta) < 10)
-      {
-         result = exp((constants::half<T>() - z) * boost::math::log1p(delta / zgh, pol));
-      }
-      else
-      {
-         result = pow(T(zgh / (zgh + delta)), T(z - constants::half<T>()));
-      }
-      // Split the calculation up to avoid spurious overflow:
-      result *= Lanczos::lanczos_sum(z) / Lanczos::lanczos_sum(T(z + delta));
-   }
-   result *= pow(T(constants::e<T>() / (zgh + delta)), delta);
-   return result;
+
+   return tgamma_delta_ratio_imp_lanczos_final(T(z), T(delta), pol, l);
 }
+
 //
 // And again without Lanczos support this time:
 //
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 16ae3b61eb..e3a2722c3d 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -26,7 +26,19 @@
 
 #include <boost/math/tools/config.hpp>
 
-#ifndef BOOST_MATH_HAS_NVRTC
+#ifdef BOOST_MATH_HAS_NVRTC
+
+namespace boost {
+namespace math {
+
+template <class RT1, class RT2, class A>
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, A>::type
+beta(RT1 a, RT2 b, A arg);
+
+} // namespace math
+} // namespace boost
+
+#else
 
 #include <vector>
 #include <complex>
@@ -154,9 +166,9 @@ namespace boost
 
    // Binomial:
    template <class T, class Policy>
-   T binomial_coefficient(unsigned n, unsigned k, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED T binomial_coefficient(unsigned n, unsigned k, const Policy& pol);
    template <class T>
-   T binomial_coefficient(unsigned n, unsigned k);
+   BOOST_MATH_GPU_ENABLED T binomial_coefficient(unsigned n, unsigned k);
 
    // erf & erfc error functions.
    template <class RT> // Error function.
@@ -874,19 +886,19 @@ namespace boost
    BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> cos_pi(T x);
 
    template <class T>
-   int fpclassify BOOST_NO_MACRO_EXPAND(T t);
+   BOOST_MATH_GPU_ENABLED int fpclassify BOOST_NO_MACRO_EXPAND(T t);
 
    template <class T>
-   bool isfinite BOOST_NO_MACRO_EXPAND(T z);
+   BOOST_MATH_GPU_ENABLED bool isfinite BOOST_NO_MACRO_EXPAND(T z);
 
    template <class T>
-   bool isinf BOOST_NO_MACRO_EXPAND(T t);
+   BOOST_MATH_GPU_ENABLED bool isinf BOOST_NO_MACRO_EXPAND(T t);
 
    template <class T>
-   bool isnan BOOST_NO_MACRO_EXPAND(T t);
+   BOOST_MATH_GPU_ENABLED bool isnan BOOST_NO_MACRO_EXPAND(T t);
 
    template <class T>
-   bool isnormal BOOST_NO_MACRO_EXPAND(T t);
+   BOOST_MATH_GPU_ENABLED bool isnormal BOOST_NO_MACRO_EXPAND(T t);
 
    template<class T>
    BOOST_MATH_GPU_ENABLED int signbit BOOST_NO_MACRO_EXPAND(T x);
@@ -1218,62 +1230,62 @@ namespace boost
    BOOST_MATH_DETAIL_11_FUNC(Policy)\
    \
    template <class RT1, class RT2>\
-   inline boost::math::tools::promote_args_t<RT1, RT2> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2> \
    beta(RT1 a, RT2 b) { return ::boost::math::beta(a, b, Policy()); }\
 \
    template <class RT1, class RT2, class A>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, A> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, A> \
    beta(RT1 a, RT2 b, A x){ return ::boost::math::beta(a, b, x, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    betac(RT1 a, RT2 b, RT3 x) { return ::boost::math::betac(a, b, x, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibeta(RT1 a, RT2 b, RT3 x){ return ::boost::math::ibeta(a, b, x, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibetac(RT1 a, RT2 b, RT3 x){ return ::boost::math::ibetac(a, b, x, Policy()); }\
 \
    template <class T1, class T2, class T3, class T4>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3, T4>  \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3, T4>  \
    ibeta_inv(T1 a, T2 b, T3 p, T4* py){ return ::boost::math::ibeta_inv(a, b, p, py, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibeta_inv(RT1 a, RT2 b, RT3 p){ return ::boost::math::ibeta_inv(a, b, p, Policy()); }\
 \
    template <class T1, class T2, class T3, class T4>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3, T4> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3, T4> \
    ibetac_inv(T1 a, T2 b, T3 q, T4* py){ return ::boost::math::ibetac_inv(a, b, q, py, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibeta_inva(RT1 a, RT2 b, RT3 p){ return ::boost::math::ibeta_inva(a, b, p, Policy()); }\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> \
    ibetac_inva(T1 a, T2 b, T3 q){ return ::boost::math::ibetac_inva(a, b, q, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibeta_invb(RT1 a, RT2 b, RT3 p){ return ::boost::math::ibeta_invb(a, b, p, Policy()); }\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> \
    ibetac_invb(T1 a, T2 b, T3 q){ return ::boost::math::ibetac_invb(a, b, q, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibetac_inv(RT1 a, RT2 b, RT3 q){ return ::boost::math::ibetac_inv(a, b, q, Policy()); }\
 \
    template <class RT1, class RT2, class RT3>\
-   inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT1, RT2, RT3> \
    ibeta_derivative(RT1 a, RT2 b, RT3 x){ return ::boost::math::ibeta_derivative(a, b, x, Policy()); }\
 \
-   template <class T> T binomial_coefficient(unsigned n, unsigned k){ return ::boost::math::binomial_coefficient<T, Policy>(n, k, Policy()); }\
+   template <class T> BOOST_MATH_GPU_ENABLED T binomial_coefficient(unsigned n, unsigned k){ return ::boost::math::binomial_coefficient<T, Policy>(n, k, Policy()); }\
 \
    template <class RT>\
    BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<RT> erf(RT z) { return ::boost::math::erf(z, Policy()); }\
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index a2af127630..fac8f84db0 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -800,7 +800,7 @@ BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_max(const T& a, const T& b) { return
 #define BOOST_MATH_BIG_CONSTANT(T, N, V) static_cast<T>(V)
 #define BOOST_MATH_FORCEINLINE __forceinline__
 #define BOOST_MATH_STD_USING  
-#define BOOST_MATH_IF_CONSTEXPR if constexpr
+#define BOOST_MATH_IF_CONSTEXPR if
 #define BOOST_MATH_IS_FLOAT(T) (boost::math::is_floating_point<T>::value)
 #define BOOST_MATH_CONSTEXPR_TABLE_FUNCTION constexpr
 #define BOOST_MATH_NO_EXCEPTIONS
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 1fb55da197..c9a70e8a99 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -25,6 +25,13 @@ run test_bernoulli_pdf_float.cu ;
 run test_bernoulli_range_support_double.cu ;
 run test_bernoulli_range_support_float.cu ;
 
+run test_beta_dist_cdf_double.cu ;
+run test_beta_dist_cdf_float.cu ;
+run test_beta_dist_pdf_double.cu ;
+run test_beta_dist_pdf_float.cu ;
+run test_beta_dist_quan_double.cu ;
+run test_beta_dist_quan_float.cu ;
+
 run test_cauchy_cdf_double.cu ;
 run test_cauchy_cdf_float.cu ;
 run test_cauchy_pdf_double.cu ;
@@ -107,6 +114,24 @@ run test_weibull_quan_float.cu ;
 # Special Functions
 run test_beta_double.cu ;
 run test_beta_float.cu ;
+run test_betac_double.cu ;
+run test_betac_float.cu ;
+run test_ibeta_double.cu ;
+run test_ibeta_float.cu ;
+run test_ibeta_derivative_double.cu ;
+run test_ibeta_derivative_float.cu ;
+run test_ibeta_inv_double.cu ;
+run test_ibeta_inv_float.cu ;
+run test_ibeta_inva_double.cu ;
+run test_ibeta_inva_float.cu ;
+run test_ibeta_invb_double.cu ;
+run test_ibeta_invb_float.cu ;
+run test_ibetac_inv_double.cu ;
+run test_ibetac_inv_float.cu ;
+run test_ibetac_inva_double.cu ;
+run test_ibetac_inva_float.cu ;
+run test_ibetac_invb_double.cu ;
+run test_ibetac_invb_float.cu ;
 
 run test_bessel_i0_double.cu ;
 run test_bessel_i0_float.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 4a37960a51..1fc2746a1f 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -24,6 +24,13 @@ run test_bernoulli_pdf_nvrtc_float.cpp ;
 run test_bernoulli_quan_nvrtc_double.cpp ;
 run test_bernoulli_quan_nvrtc_float.cpp ;
 
+run test_beta_dist_cdf_nvrtc_double.cpp ;
+run test_beta_dist_cdf_nvrtc_float.cpp ;
+run test_beta_dist_pdf_nvrtc_double.cpp ;
+run test_beta_dist_pdf_nvrtc_float.cpp ;
+run test_beta_dist_quan_nvrtc_double.cpp ;
+run test_beta_dist_quan_nvrtc_float.cpp ;
+
 run test_cauchy_cdf_nvrtc_double.cpp ;
 run test_cauchy_cdf_nvrtc_float.cpp ;
 run test_cauchy_pdf_nvrtc_double.cpp ;
@@ -104,6 +111,26 @@ run test_weibull_quan_nvrtc_float.cpp ;
 # Special Functions
 run test_beta_nvrtc_double.cpp ;
 run test_beta_nvrtc_float.cpp ;
+run test_betac_nvrtc_double.cpp ;
+run test_betac_nvrtc_float.cpp ;
+run test_ibeta_nvrtc_double.cpp ;
+run test_ibeta_nvrtc_float.cpp ;
+run test_ibetac_nvrtc_double.cpp ;
+run test_ibetac_nvrtc_float.cpp ;
+run test_ibeta_derivative_nvrtc_double.cpp ;
+run test_ibeta_derivative_nvrtc_float.cpp ;
+run test_ibeta_inv_nvrtc_double.cpp ;
+run test_ibeta_inv_nvrtc_float.cpp ;
+run test_ibeta_inva_nvrtc_double.cpp ;
+run test_ibeta_inva_nvrtc_float.cpp ;
+run test_ibeta_invb_nvrtc_double.cpp ;
+run test_ibeta_invb_nvrtc_float.cpp ;
+run test_ibetac_inv_nvrtc_double.cpp ;
+run test_ibetac_inv_nvrtc_float.cpp ;
+run test_ibetac_inva_nvrtc_double.cpp ;
+run test_ibetac_inva_nvrtc_float.cpp ;
+run test_ibetac_invb_nvrtc_double.cpp ;
+run test_ibetac_invb_nvrtc_float.cpp ;
 
 run test_bessel_i0_nvrtc_double.cpp ;
 run test_bessel_i0_nvrtc_float.cpp ;
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 2fd5954ae1..5d3d85cd8f 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -12,6 +12,7 @@ project : requirements
 # Distributions
 run test_arcsine.cpp ;
 run test_bernoulli.cpp ;
+run test_beta_dist.cpp ;
 run test_cauchy.cpp ;
 run test_chi_squared.cpp ;
 run test_exponential_dist.cpp ;
@@ -28,6 +29,10 @@ run test_weibull.cpp ;
 run pow_test.cpp ;
 
 run test_beta_simple.cpp ;
+run test_beta.cpp ;
+run test_ibeta.cpp ;
+run test_ibeta_inv.cpp ;
+run test_ibeta_inv_ab.cpp ;
 
 run test_bessel_i.cpp ;
 run test_bessel_j.cpp ;
diff --git a/test/test_bessel_i.cpp b/test/test_bessel_i.cpp
index 09487ddf1b..817569760a 100644
--- a/test/test_bessel_i.cpp
+++ b/test/test_bessel_i.cpp
@@ -15,7 +15,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_bessel_i.hpp"
diff --git a/test/test_bessel_j.cpp b/test/test_bessel_j.cpp
index 31a64bc579..1dd63a68a5 100644
--- a/test/test_bessel_j.cpp
+++ b/test/test_bessel_j.cpp
@@ -15,7 +15,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_bessel_j.hpp"
diff --git a/test/test_bessel_k.cpp b/test/test_bessel_k.cpp
index 84ba0830f2..6c31f5ab05 100644
--- a/test/test_bessel_k.cpp
+++ b/test/test_bessel_k.cpp
@@ -22,7 +22,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_bessel_k.hpp"
diff --git a/test/test_bessel_y.cpp b/test/test_bessel_y.cpp
index 232a903963..8251920c5b 100644
--- a/test/test_bessel_y.cpp
+++ b/test/test_bessel_y.cpp
@@ -15,7 +15,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_bessel_y.hpp"
diff --git a/test/test_beta.cpp b/test/test_beta.cpp
index b24cb32c07..4e27b71353 100644
--- a/test/test_beta.cpp
+++ b/test/test_beta.cpp
@@ -5,7 +5,17 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
-#include "pch_light.hpp"
+#ifndef SYCL_LANGUAGE_VERSION
+#include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Woverflow"
+#endif
 
 #include "test_beta.hpp"
 
diff --git a/test/test_beta.hpp b/test/test_beta.hpp
index e633935a3c..3019c17e71 100644
--- a/test/test_beta.hpp
+++ b/test/test_beta.hpp
@@ -18,9 +18,10 @@
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
+#include <boost/math/special_functions/beta.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
@@ -109,9 +110,12 @@ void test_spots(T)
       // Inexact input, so disable for ultra precise long doubles:
       BOOST_CHECK_CLOSE(::boost::math::beta(static_cast<T>(0.0125L), static_cast<T>(0.000023L)), static_cast<T>(43558.24045647538375006349016083320744662L), tolerance * 2);
    }
+
+   #ifndef BOOST_MATH_NO_EXCEPTIONS
    BOOST_CHECK_THROW(boost::math::beta(static_cast<T>(0), static_cast<T>(1)), std::domain_error);
    BOOST_CHECK_THROW(boost::math::beta(static_cast<T>(-1), static_cast<T>(1)), std::domain_error);
    BOOST_CHECK_THROW(boost::math::beta(static_cast<T>(1), static_cast<T>(-1)), std::domain_error);
    BOOST_CHECK_THROW(boost::math::beta(static_cast<T>(1), static_cast<T>(0)), std::domain_error);
+   #endif
 }
 
diff --git a/test/test_beta_dist.cpp b/test/test_beta_dist.cpp
index 943718a39f..1652309eb7 100644
--- a/test/test_beta_dist.cpp
+++ b/test/test_beta_dist.cpp
@@ -32,9 +32,14 @@
 # pragma warning (disable : 4224) // nonstandard extension used : formal parameter 'arg' was previously defined as a type.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
-#include <boost/math/tools/test.hpp>
+#endif
+
+#include "../include_private/boost/math/tools/test.hpp"
 
 #include <boost/math/distributions/beta.hpp> // for beta_distribution
 using boost::math::beta_distribution;
@@ -634,12 +639,13 @@ BOOST_AUTO_TEST_CASE( test_main )
    BOOST_CHECK_CLOSE_FRACTION(mybeta22.find_alpha(mybeta22.beta(), 0.8, cdf(mybeta22, 0.8)), mybeta22.alpha(), tol);
    BOOST_CHECK_CLOSE_FRACTION(mybeta22.find_beta(mybeta22.alpha(), 0.8, cdf(mybeta22, 0.8)), mybeta22.beta(), tol);
 
-
+   #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
    beta_distribution<real_concept> rcbeta22(2, 2); // Using RealType real_concept.
    cout << "numeric_limits<real_concept>::is_specialized " << numeric_limits<real_concept>::is_specialized << endl;
    cout << "numeric_limits<real_concept>::digits " << numeric_limits<real_concept>::digits << endl;
    cout << "numeric_limits<real_concept>::digits10 " << numeric_limits<real_concept>::digits10 << endl;
    cout << "numeric_limits<real_concept>::epsilon " << numeric_limits<real_concept>::epsilon() << endl;
+   #endif
 
    // (Parameter value, arbitrarily zero, only communicates the floating point type).
    test_spots(0.0F); // Test float.
diff --git a/test/test_beta_dist_cdf_double.cu b/test/test_beta_dist_cdf_double.cu
new file mode 100644
index 0000000000..fa460244a3
--- /dev/null
+++ b/test/test_beta_dist_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_cdf_float.cu b/test/test_beta_dist_cdf_float.cu
new file mode 100644
index 0000000000..321c844205
--- /dev/null
+++ b/test/test_beta_dist_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_cdf_nvrtc_double.cpp b/test/test_beta_dist_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4f5913c108
--- /dev/null
+++ b/test/test_beta_dist_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_dist_cdf_nvrtc_float.cpp b/test/test_beta_dist_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..f5b031c5a9
--- /dev/null
+++ b/test/test_beta_dist_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_dist_pdf_double.cu b/test/test_beta_dist_pdf_double.cu
new file mode 100644
index 0000000000..c0ee9272ae
--- /dev/null
+++ b/test/test_beta_dist_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_pdf_float.cu b/test/test_beta_dist_pdf_float.cu
new file mode 100644
index 0000000000..75e4fa27b4
--- /dev/null
+++ b/test/test_beta_dist_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_pdf_nvrtc_double.cpp b/test/test_beta_dist_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..c9870e2ce4
--- /dev/null
+++ b/test/test_beta_dist_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_dist_pdf_nvrtc_float.cpp b/test/test_beta_dist_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..0b4fd83488
--- /dev/null
+++ b/test/test_beta_dist_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_dist_quan_double.cu b/test/test_beta_dist_quan_double.cu
new file mode 100644
index 0000000000..101526afae
--- /dev/null
+++ b/test/test_beta_dist_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_quan_float.cu b/test/test_beta_dist_quan_float.cu
new file mode 100644
index 0000000000..77696c6393
--- /dev/null
+++ b/test/test_beta_dist_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::beta_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_beta_dist_quan_nvrtc_double.cpp b/test/test_beta_dist_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..9726bf019e
--- /dev/null
+++ b/test/test_beta_dist_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_beta_dist_quan_nvrtc_float.cpp b/test/test_beta_dist_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..d2476cb2ac
--- /dev/null
+++ b/test/test_beta_dist_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/beta.hpp>
+extern "C" __global__ 
+void test_beta_dist_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::beta_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_dist_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_dist_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_dist_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::beta_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_betac_double.cu b/test/test_betac_double.cu
new file mode 100644
index 0000000000..8bb31d3219
--- /dev/null
+++ b/test/test_betac_double.cu
@@ -0,0 +1,146 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::betac(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+       v3.push_back(beta_med_data[i][2]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+       v3.push_back(beta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::betac(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_betac_float.cu b/test/test_betac_float.cu
new file mode 100644
index 0000000000..7070c567cc
--- /dev/null
+++ b/test/test_betac_float.cu
@@ -0,0 +1,146 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::betac(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "beta_med_data.ipp"
+#include "beta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < beta_med_data.size(); ++i)
+    {
+       v1.push_back(beta_med_data[i][0]);
+       v2.push_back(beta_med_data[i][1]);
+       v3.push_back(beta_med_data[i][2]);
+    }
+    for(unsigned i = 0; i < beta_small_data.size(); ++i)
+    {
+       v1.push_back(beta_small_data[i][0]);
+       v2.push_back(beta_small_data[i][1]);
+       v3.push_back(beta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::betac(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_betac_nvrtc_double.cpp b/test/test_betac_nvrtc_double.cpp
new file mode 100644
index 0000000000..0667cfe0d4
--- /dev/null
+++ b/test/test_betac_nvrtc_double.cpp
@@ -0,0 +1,196 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_beta_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::betac(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+            h_in3[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::betac(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_betac_nvrtc_float.cpp b/test/test_betac_nvrtc_float.cpp
new file mode 100644
index 0000000000..0667cfe0d4
--- /dev/null
+++ b/test/test_betac_nvrtc_float.cpp
@@ -0,0 +1,196 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_beta_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::betac(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+            h_in3[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::betac(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_erf.cpp b/test/test_erf.cpp
index 5044847114..2232c1c759 100644
--- a/test/test_erf.cpp
+++ b/test/test_erf.cpp
@@ -13,7 +13,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
diff --git a/test/test_holtsmark.cpp b/test/test_holtsmark.cpp
index 475f5400aa..93a40924d6 100644
--- a/test/test_holtsmark.cpp
+++ b/test/test_holtsmark.cpp
@@ -21,7 +21,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 using boost::math::holtsmark_distribution;
diff --git a/test/test_ibeta.cpp b/test/test_ibeta.cpp
index e026ac6c52..987b361105 100644
--- a/test/test_ibeta.cpp
+++ b/test/test_ibeta.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Woverflow"
+#endif
+
 #include "test_ibeta.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
diff --git a/test/test_ibeta.hpp b/test/test_ibeta.hpp
index 7c951d614f..cfd5d78cd1 100644
--- a/test/test_ibeta.hpp
+++ b/test/test_ibeta.hpp
@@ -8,9 +8,10 @@
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
+#include <boost/math/special_functions/beta.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_ibeta_derivative.cpp b/test/test_ibeta_derivative.cpp
index c899c94bf5..5d6a312754 100644
--- a/test/test_ibeta_derivative.cpp
+++ b/test/test_ibeta_derivative.cpp
@@ -4,7 +4,7 @@
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 #if defined(__GNUC__) && __GNUC__ <= 12
 #pragma GCC diagnostic push
-#pragma GCC diagnostic ignored "-Wliteral-range"
+#pragma GCC diagnostic ignored "-Woverflow"
 #endif
 #include <pch_light.hpp>
 #include "test_ibeta_derivative.hpp"
diff --git a/test/test_ibeta_derivative_double.cu b/test/test_ibeta_derivative_double.cu
new file mode 100644
index 0000000000..e5f7f340ba
--- /dev/null
+++ b/test/test_ibeta_derivative_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_derivative(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_derivative(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_derivative_float.cu b/test/test_ibeta_derivative_float.cu
new file mode 100644
index 0000000000..36a79665d4
--- /dev/null
+++ b/test/test_ibeta_derivative_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_derivative(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_derivative(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_derivative_nvrtc_double.cpp b/test/test_ibeta_derivative_nvrtc_double.cpp
new file mode 100644
index 0000000000..f15d21db00
--- /dev/null
+++ b/test/test_ibeta_derivative_nvrtc_double.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_derivative_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_derivative(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_derivative_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_derivative_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_derivative_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta_derivative(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_derivative_nvrtc_float.cpp b/test/test_ibeta_derivative_nvrtc_float.cpp
new file mode 100644
index 0000000000..17443e0bdc
--- /dev/null
+++ b/test/test_ibeta_derivative_nvrtc_float.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_derivative_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_derivative(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_derivative_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_derivative_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_derivative_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta_derivative(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_double.cu b/test/test_ibeta_double.cu
new file mode 100644
index 0000000000..20384bf25f
--- /dev/null
+++ b/test/test_ibeta_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_float.cu b/test/test_ibeta_float.cu
new file mode 100644
index 0000000000..be17813ee4
--- /dev/null
+++ b/test/test_ibeta_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_inv.cpp b/test/test_ibeta_inv.cpp
index 218c1625e8..ab1f4267fc 100644
--- a/test/test_ibeta_inv.cpp
+++ b/test/test_ibeta_inv.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Woverflow"
+#endif
+
 #include"test_ibeta_inv.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
diff --git a/test/test_ibeta_inv.hpp b/test/test_ibeta_inv.hpp
index ba98901773..fa765b2ef8 100644
--- a/test/test_ibeta_inv.hpp
+++ b/test/test_ibeta_inv.hpp
@@ -8,10 +8,11 @@
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
+#include <boost/math/special_functions/beta.hpp>
 #include <boost/math/special_functions/next.hpp>  // for has_denorm_now
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
@@ -306,6 +307,7 @@ void test_spots(T)
       BOOST_MATH_CHECK_THROW(::boost::math::ibeta_inv(static_cast<T>(2.125), -n, static_cast<T>(0.125)), std::domain_error);
       BOOST_MATH_CHECK_THROW(::boost::math::ibeta_inv(static_cast<T>(2.125), static_cast<T>(1.125), -n), std::domain_error);
    }
+   #ifndef SYCL_LANGUAGE_VERSION
    if (boost::math::detail::has_denorm_now<T>())
    {
       T m = std::numeric_limits<T>::denorm_min();
@@ -317,5 +319,6 @@ void test_spots(T)
       BOOST_CHECK((boost::math::isfinite)(boost::math::ibeta_inv(static_cast<T>(12.125), m, static_cast<T>(0.125))));
       BOOST_CHECK((boost::math::isfinite)(boost::math::ibeta_inv(m, m, static_cast<T>(0.125))));
    }
+   #endif
 }
 
diff --git a/test/test_ibeta_inv_ab.cpp b/test/test_ibeta_inv_ab.cpp
index c1acb2d1ca..fdf735ef1e 100644
--- a/test/test_ibeta_inv_ab.cpp
+++ b/test/test_ibeta_inv_ab.cpp
@@ -3,7 +3,18 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifdef __clang__
+#  pragma clang diagnostic push 
+#  pragma clang diagnostic ignored "-Wliteral-range"
+#elif defined(__GNUC__)
+#  pragma GCC diagnostic push 
+#  pragma GCC diagnostic ignored "-Woverflow"
+#endif
+
 #include "test_ibeta_inv_ab.hpp"
 
 #if !defined(TEST_FLOAT) && !defined(TEST_DOUBLE) && !defined(TEST_LDOUBLE) && !defined(TEST_REAL_CONCEPT)
diff --git a/test/test_ibeta_inv_ab.hpp b/test/test_ibeta_inv_ab.hpp
index c378d15287..b91ab5261d 100644
--- a/test/test_ibeta_inv_ab.hpp
+++ b/test/test_ibeta_inv_ab.hpp
@@ -10,9 +10,10 @@
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
+#include <boost/math/special_functions/beta.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_ibeta_inv_double.cu b/test/test_ibeta_inv_double.cu
new file mode 100644
index 0000000000..ef62c5e162
--- /dev/null
+++ b/test/test_ibeta_inv_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inv(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_inv(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_inv_float.cu b/test/test_ibeta_inv_float.cu
new file mode 100644
index 0000000000..a0d48bfbda
--- /dev/null
+++ b/test/test_ibeta_inv_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inv(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_inv(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_inv_nvrtc_double.cpp b/test/test_ibeta_inv_nvrtc_double.cpp
new file mode 100644
index 0000000000..2f01012bbe
--- /dev/null
+++ b/test/test_ibeta_inv_nvrtc_double.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_inv_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inv(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta_inv(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_inv_nvrtc_float.cpp b/test/test_ibeta_inv_nvrtc_float.cpp
new file mode 100644
index 0000000000..5d804398cb
--- /dev/null
+++ b/test/test_ibeta_inv_nvrtc_float.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_inv_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inv(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta_inv(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_inva_double.cu b/test/test_ibeta_inva_double.cu
new file mode 100644
index 0000000000..7783eb21bb
--- /dev/null
+++ b/test/test_ibeta_inva_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inva(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_inva(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_inva_float.cu b/test/test_ibeta_inva_float.cu
new file mode 100644
index 0000000000..ff918f9436
--- /dev/null
+++ b/test/test_ibeta_inva_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inva(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_inva(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_inva_nvrtc_double.cpp b/test/test_ibeta_inva_nvrtc_double.cpp
new file mode 100644
index 0000000000..a392eaea65
--- /dev/null
+++ b/test/test_ibeta_inva_nvrtc_double.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_inva_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inva(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_inva_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_inva_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_inva_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibeta_inva(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_inva_nvrtc_float.cpp b/test/test_ibeta_inva_nvrtc_float.cpp
new file mode 100644
index 0000000000..ba5745c321
--- /dev/null
+++ b/test/test_ibeta_inva_nvrtc_float.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_inva_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_inva(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_inva_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_inva_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_inva_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibeta_inva(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_invb_double.cu b/test/test_ibeta_invb_double.cu
new file mode 100644
index 0000000000..562f5349dd
--- /dev/null
+++ b/test/test_ibeta_invb_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_invb(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_invb(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_invb_float.cu b/test/test_ibeta_invb_float.cu
new file mode 100644
index 0000000000..86f5615c36
--- /dev/null
+++ b/test/test_ibeta_invb_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_invb(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibeta_invb(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibeta_invb_nvrtc_double.cpp b/test/test_ibeta_invb_nvrtc_double.cpp
new file mode 100644
index 0000000000..6f046f09f3
--- /dev/null
+++ b/test/test_ibeta_invb_nvrtc_double.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_invb_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_invb(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_invb_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_invb_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_invb_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibeta_invb(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_invb_nvrtc_float.cpp b/test/test_ibeta_invb_nvrtc_float.cpp
new file mode 100644
index 0000000000..f2d17b8447
--- /dev/null
+++ b/test/test_ibeta_invb_nvrtc_float.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_invb_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta_invb(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_invb_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_invb_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_invb_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibeta_invb(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_nvrtc_double.cpp b/test/test_ibeta_nvrtc_double.cpp
new file mode 100644
index 0000000000..bc920b6368
--- /dev/null
+++ b/test/test_ibeta_nvrtc_double.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibeta_nvrtc_float.cpp b/test/test_ibeta_nvrtc_float.cpp
new file mode 100644
index 0000000000..ee15748628
--- /dev/null
+++ b/test/test_ibeta_nvrtc_float.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibeta_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibeta(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibeta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibeta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibeta_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibeta(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_inv_double.cu b/test/test_ibetac_inv_double.cu
new file mode 100644
index 0000000000..a983d16677
--- /dev/null
+++ b/test/test_ibetac_inv_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inv(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_inv(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_inv_float.cu b/test/test_ibetac_inv_float.cu
new file mode 100644
index 0000000000..94583b45e2
--- /dev/null
+++ b/test/test_ibetac_inv_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inv(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_inv(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_inv_nvrtc_double.cpp b/test/test_ibetac_inv_nvrtc_double.cpp
new file mode 100644
index 0000000000..a99d53b3cd
--- /dev/null
+++ b/test/test_ibetac_inv_nvrtc_double.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_inv_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inv(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibetac_inv(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_inv_nvrtc_float.cpp b/test/test_ibetac_inv_nvrtc_float.cpp
new file mode 100644
index 0000000000..47e89db4c1
--- /dev/null
+++ b/test/test_ibetac_inv_nvrtc_float.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_inv_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inv(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_inv_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_inv_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_inv_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibetac_inv(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_inva_double.cu b/test/test_ibetac_inva_double.cu
new file mode 100644
index 0000000000..2efbee265d
--- /dev/null
+++ b/test/test_ibetac_inva_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inva(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_inva(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_inva_float.cu b/test/test_ibetac_inva_float.cu
new file mode 100644
index 0000000000..9bd1a29a07
--- /dev/null
+++ b/test/test_ibetac_inva_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inva(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_inva(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_inva_nvrtc_double.cpp b/test/test_ibetac_inva_nvrtc_double.cpp
new file mode 100644
index 0000000000..7c7bf992b3
--- /dev/null
+++ b/test/test_ibetac_inva_nvrtc_double.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_inva_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inva(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_inva_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_inva_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_inva_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibetac_inva(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_inva_nvrtc_float.cpp b/test/test_ibetac_inva_nvrtc_float.cpp
new file mode 100644
index 0000000000..c79b8b02f1
--- /dev/null
+++ b/test/test_ibetac_inva_nvrtc_float.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_inva_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_inva(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_inva_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_inva_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_inva_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibetac_inva(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_invb_double.cu b/test/test_ibetac_invb_double.cu
new file mode 100644
index 0000000000..fddd655af2
--- /dev/null
+++ b/test/test_ibetac_invb_double.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_invb(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_invb(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_invb_float.cu b/test/test_ibetac_invb_float.cu
new file mode 100644
index 0000000000..fddd655af2
--- /dev/null
+++ b/test/test_ibetac_invb_float.cu
@@ -0,0 +1,149 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// floating-point value does not fit in required floating-point type
+#pragma nv_diag_suppress 221
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/array.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_invb(in1[i], in2[i], in3[i]);
+    }
+}
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+    // Consolidate the test data:
+    std::vector<float_type> v1, v2, v3;
+
+    for(unsigned i = 0; i < ibeta_data.size(); ++i)
+    {
+       v1.push_back(ibeta_data[i][0]);
+       v2.push_back(ibeta_data[i][1]);
+       v3.push_back(ibeta_data[i][2]);
+    }
+    for(unsigned i = 0; i < ibeta_small_data.size(); ++i)
+    {
+       v1.push_back(ibeta_small_data[i][0]);
+       v2.push_back(ibeta_small_data[i][1]);
+       v3.push_back(ibeta_small_data[i][2]);
+    }
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+    cuda_managed_ptr<float_type> input_vector3(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        int table_id = i % v1.size();
+        input_vector1[i] = v1[table_id];
+        input_vector2[i] = v2[table_id];
+        input_vector3[i] = v3[table_id];
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), input_vector3.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ibetac_invb(input_vector1[i], input_vector2[i], input_vector3[i]));
+    double t = w.elapsed();
+    bool failed = false;
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::isfinite(output_vector[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+                failed = true;
+            }
+        }
+    }
+
+    if (failed)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
+
+
diff --git a/test/test_ibetac_invb_nvrtc_double.cpp b/test/test_ibetac_invb_nvrtc_double.cpp
new file mode 100644
index 0000000000..76f6318901
--- /dev/null
+++ b/test/test_ibetac_invb_nvrtc_double.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_invb_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_invb(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_invb_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_invb_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_invb_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibetac_invb(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_invb_nvrtc_float.cpp b/test/test_ibetac_invb_nvrtc_float.cpp
new file mode 100644
index 0000000000..48d0a31eec
--- /dev/null
+++ b/test/test_ibetac_invb_nvrtc_float.cpp
@@ -0,0 +1,220 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_invb_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac_invb(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_invb_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_invb_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_invb_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            // Sometimes the ignore error policy is ignored so the below throws
+            // Rather than terminating we can continue to process through our results array
+            double res;
+            try
+            {
+                res = boost::math::ibetac_invb(h_in1[i], h_in2[i], h_in3[i]);
+            }
+            catch (...)
+            {
+                continue;
+            }
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_nvrtc_double.cpp b/test/test_ibetac_nvrtc_double.cpp
new file mode 100644
index 0000000000..6a59473e18
--- /dev/null
+++ b/test/test_ibetac_nvrtc_double.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibetac(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ibetac_nvrtc_float.cpp b/test/test_ibetac_nvrtc_float.cpp
new file mode 100644
index 0000000000..a989191e51
--- /dev/null
+++ b/test/test_ibetac_nvrtc_float.cpp
@@ -0,0 +1,207 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/beta.hpp>
+extern "C" __global__ 
+void test_ibetac_kernel(const float_type *in1, const float_type *in2, const float_type *in3, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ibetac(in1[i], in2[i], in3[i]);
+    }
+}
+)";
+
+template <class T> struct table_type { typedef T type; };
+typedef float_type T;
+#define SC_(x) static_cast<T>(x)
+
+#include "ibeta_data.ipp"
+#include "ibeta_small_data.ipp"
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ibetac_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ibetac_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ibetac_kernel"), "Failed to get kernel function");
+
+        int numElements = ibeta_data.size() + ibeta_small_data.size();
+        float_type *h_in1, *h_in2, *h_in3, *h_out;
+        float_type *d_in1, *d_in2, *d_in3, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_in3 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        for (int i = 0; i < ibeta_data.size(); ++i) 
+        {
+            h_in1[i] = ibeta_data[i][0];
+            h_in2[i] = ibeta_data[i][1];
+            h_in3[i] = ibeta_data[i][2];
+        }
+        for (int i = 0; i < ibeta_small_data.size(); ++i)
+        {
+            h_in1[i + ibeta_data.size()] = ibeta_small_data[i][0];
+            h_in2[i + ibeta_data.size()] = ibeta_small_data[i][1];
+            h_in3[i + ibeta_data.size()] = ibeta_small_data[i][2];
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_in3, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+        checkCUDAError(cudaMemcpy(d_in3, h_in3, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in3");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_in3, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ibetac(h_in1[i], h_in2[i], h_in3[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_in3);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_in3;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_igamma.cpp b/test/test_igamma.cpp
index 0ad7019963..6e034f3c60 100644
--- a/test/test_igamma.cpp
+++ b/test/test_igamma.cpp
@@ -12,7 +12,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_igamma.hpp"
diff --git a/test/test_igamma_inv.cpp b/test/test_igamma_inv.cpp
index 17e0bfb54f..80a553427c 100644
--- a/test/test_igamma_inv.cpp
+++ b/test/test_igamma_inv.cpp
@@ -12,7 +12,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #include "test_igamma_inv.hpp"
diff --git a/test/test_igamma_inva.cpp b/test/test_igamma_inva.cpp
index 8d0e965962..443ad7bbc6 100644
--- a/test/test_igamma_inva.cpp
+++ b/test/test_igamma_inva.cpp
@@ -12,7 +12,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #include "test_igamma_inva.hpp"
diff --git a/test/test_landau.cpp b/test/test_landau.cpp
index 1625b21777..c69c208177 100644
--- a/test/test_landau.cpp
+++ b/test/test_landau.cpp
@@ -20,7 +20,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 using boost::math::landau_distribution;
diff --git a/test/test_mapairy.cpp b/test/test_mapairy.cpp
index ee8e43bf00..ca3b415d76 100644
--- a/test/test_mapairy.cpp
+++ b/test/test_mapairy.cpp
@@ -9,7 +9,7 @@
 #  pragma clang diagnostic ignored "-Wliteral-range"
 #elif defined(__GNUC__)
 #  pragma GCC diagnostic push 
-#  pragma GCC diagnostic ignored "-Wliteral-range"
+#  pragma GCC diagnostic ignored "-Woverflow"
 #endif
 
 #define BOOST_TEST_MAIN

From 814cb6e49f909cae34c666b605e79a15e584764f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 15:46:17 -0400
Subject: [PATCH 365/399] Add overview

---
 doc/math.qbk         |  1 +
 doc/overview/gpu.qbk | 59 ++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 60 insertions(+)
 create mode 100644 doc/overview/gpu.qbk

diff --git a/doc/math.qbk b/doc/math.qbk
index d6b90efb0b..385c93a5e8 100644
--- a/doc/math.qbk
+++ b/doc/math.qbk
@@ -557,6 +557,7 @@ and as a CD ISBN 0-9504833-2-X  978-0-9504833-2-0, Classification 519.2-dc22.
 [include overview/standalone.qbk]
 [include overview/result_type_calc.qbk]
 [include overview/error_handling.qbk]
+[include overview/gpu.qbk]
 
 [section:compilers_overview Compilers]
 [compilers_overview]
diff --git a/doc/overview/gpu.qbk b/doc/overview/gpu.qbk
new file mode 100644
index 0000000000..70f0164e0a
--- /dev/null
+++ b/doc/overview/gpu.qbk
@@ -0,0 +1,59 @@
+[section:gpu Support for GPU programming in Boost.Math]
+
+[h4 GPU Support]
+
+Selected functions, distributions, tools, etc. support running on both host and devices.
+These functions will have the annotation `BOOST_MATH_GPU_ENABLED` next to their individual documentation.
+We test using CUDA (both NVCC and NVRTC) as well as SYCL to provide a wide range of support.
+
+[h4 How to build with device support]
+
+When compiling with CUDA or SYCL you will have to ensure that your code is being run inside of a kernel function.
+It is not enough to simply compile existing code with the NVCC compiler to run the code on the device.
+A simple CUDA kernel to run the Beta Distribution CDF on NVCC would be:
+
+    __global__ void cuda_beta_dist(const double* in, double* out, int num_elements)
+    {
+        const int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+        if (i < num_elements)
+        {
+            out[i] = cdf(boost::math::beta_distribution<double>(), in[i]);
+        }
+    }
+
+And on CUDA on NVRTC:
+
+    const char* cuda_kernel = R"(
+    #include <boost/math/distributions/beta.hpp>
+    extern "C" __global__ 
+    void test_beta_dist_kernel(const double* in, double* out, int num_elements)
+    {
+        const int i = blockDim.x * blockIdx.x + threadIdx.x;
+        if (i < num_elements)
+        {
+            out[i] = boost::math::cdf(boost::math::beta_distribution<double>(), in[i]);
+        }
+    }
+    )";
+
+And lastly on SYCL:
+
+    void sycl_beta_dist(const double* in, double* out, int num_elements, sycl::queue& q)
+    {
+        q.submit([&](sycl::handler& h) {
+            h.parallel_for(sycl::range<1>(num_elements), [=](sycl::id<1> i) {
+                out[i] = boost::math::cdf(boost::math::beta_distribution<double>(), in[i]);
+            });
+        });
+    }
+
+Once your kernel function has been written then use the framework mechanism for launching the kernel.
+
+[/ 
+  Copyright 2024. Matt Borland
+  Distributed under the Boost Software License, Version 1.0.
+  (See accompanying file LICENSE_1_0.txt or copy at
+  http://www.boost.org/LICENSE_1_0.txt).
+]
+

From 82adb328e7df3d449b17c236699cb9a3a96e5aff Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 15:46:33 -0400
Subject: [PATCH 366/399] Annotate GPU markers in constants doc with type
 caveat

---
 doc/constants/constants.qbk | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/doc/constants/constants.qbk b/doc/constants/constants.qbk
index 24092adf56..9cce152da1 100644
--- a/doc/constants/constants.qbk
+++ b/doc/constants/constants.qbk
@@ -227,6 +227,11 @@ either construct from a decimal digit string or calculate on the fly depending u
 [[Any other value ['N]][Sets the compile time precision to ['N] bits.]]
 ]
 
+[h5 GPU Support]
+
+All Boost.Math constants are marked with `BOOST_MATH_GPU_ENABLED` and can be used on both host and device.
+Note that when running on device you are limited to using only `float` and `double` types.
+
 [h5 Custom Specializing a constant]
 
 In addition, for user-defined types that need special handling, it's possible to partially-specialize

From a3adb94aca47372c1023ad69fbce82dfb6aeba14 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 15:46:47 -0400
Subject: [PATCH 367/399] Add GPU markers to supported dists docs

---
 doc/distributions/arcsine.qbk       | 12 +++++++-----
 doc/distributions/bernoulli.qbk     | 10 ++++++----
 doc/distributions/beta.qbk          | 22 ++++++++++++----------
 doc/distributions/cauchy.qbk        | 14 ++++++++------
 doc/distributions/chi_squared.qbk   |  8 +++++---
 doc/distributions/exponential.qbk   | 10 ++++++----
 doc/distributions/extreme_value.qbk | 14 ++++++++------
 doc/distributions/holtsmark.qbk     | 14 ++++++++------
 doc/distributions/landau.qbk        | 18 ++++++++++--------
 doc/distributions/laplace.qbk       | 14 ++++++++------
 doc/distributions/logistic.qbk      | 14 ++++++++------
 doc/distributions/mapairy.qbk       | 14 ++++++++------
 doc/distributions/saspoint5.qbk     | 14 ++++++++------
 doc/distributions/weibull.qbk       | 14 ++++++++------
 14 files changed, 110 insertions(+), 82 deletions(-)

diff --git a/doc/distributions/arcsine.qbk b/doc/distributions/arcsine.qbk
index fbd6e86b1e..7930f97d5a 100644
--- a/doc/distributions/arcsine.qbk
+++ b/doc/distributions/arcsine.qbk
@@ -21,11 +21,11 @@
       typedef Policy    policy_type;
 
       // Constructor from two range parameters, x_min and x_max:
-      arcsine_distribution(RealType x_min = 0, RealType x_max = 1);
+      BOOST_MATH_GPU_ENABLED arcsine_distribution(RealType x_min = 0, RealType x_max = 1);
 
       // Range Parameter accessors:
-      RealType x_min() const;
-      RealType x_max() const;
+      BOOST_MATH_GPU_ENABLED RealType x_min() const;
+      BOOST_MATH_GPU_ENABLED RealType x_max() const;
    };
    }} // namespaces
 
@@ -103,8 +103,8 @@ constructs a 'Standard 01' arcsine distribution.
 
 [h5 Parameter Accessors]
 
-   RealType x_min() const;
-   RealType x_max() const;
+   BOOST_MATH_GPU_ENABLED RealType x_min() const;
+   BOOST_MATH_GPU_ENABLED RealType x_max() const;
 
 Return the parameter ['x_min] or  ['x_max] from which this distribution was constructed.
 
@@ -116,6 +116,8 @@ So, for example:
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The formulae for calculating these are shown in the table below, and at
 [@http://mathworld.wolfram.com/arcsineDistribution.html Wolfram Mathworld].
diff --git a/doc/distributions/bernoulli.qbk b/doc/distributions/bernoulli.qbk
index 4a2fc7b618..719c42cd9e 100644
--- a/doc/distributions/bernoulli.qbk
+++ b/doc/distributions/bernoulli.qbk
@@ -16,9 +16,9 @@
        typedef RealType  value_type;
        typedef Policy    policy_type;
 
-       bernoulli_distribution(RealType p); // Constructor.
+       BOOST_MATH_GPU_ENABLED bernoulli_distribution(RealType p); // Constructor.
        // Accessor function.
-       RealType success_fraction() const
+       BOOST_MATH_GPU_ENABLED RealType success_fraction() const
        // Probability of success (as a fraction).
     };
    }} // namespaces
@@ -51,12 +51,12 @@ and the [@http://en.wikipedia.org/wiki/Cumulative_Distribution_Function Cumulati
 
 [h4 Member Functions]
 
-   bernoulli_distribution(RealType p);
+   BOOST_MATH_GPU_ENABLED bernoulli_distribution(RealType p);
 
 Constructs a [@http://en.wikipedia.org/wiki/bernoulli_distribution
 bernoulli distribution] with success_fraction /p/.
 
-   RealType success_fraction() const
+   BOOST_MATH_GPU_ENABLED RealType success_fraction() const
 
 Returns the /success_fraction/ parameter of this distribution.
 
@@ -64,6 +64,8 @@ Returns the /success_fraction/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is 0 and 1,
 and the useful supported range is only 0 or 1.
diff --git a/doc/distributions/beta.qbk b/doc/distributions/beta.qbk
index 95943f715d..5ba1a6d1cc 100644
--- a/doc/distributions/beta.qbk
+++ b/doc/distributions/beta.qbk
@@ -19,30 +19,30 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
       // Constructor from two shape parameters, alpha & beta:
-      beta_distribution(RealType a, RealType b);
+      BOOST_MATH_GPU_ENABLED beta_distribution(RealType a, RealType b);
       
       // Parameter accessors:
-      RealType alpha() const;
-      RealType beta() const;
+      BOOST_MATH_GPU_ENABLED RealType alpha() const;
+      BOOST_MATH_GPU_ENABLED RealType beta() const;
       
       // Parameter estimators of alpha or beta from mean and variance.
-      static RealType find_alpha(
+      BOOST_MATH_GPU_ENABLED static RealType find_alpha(
         RealType mean, // Expected value of mean.
         RealType variance); // Expected value of variance.
       
-      static RealType find_beta(
+      BOOST_MATH_GPU_ENABLED static RealType find_beta(
         RealType mean, // Expected value of mean.
         RealType variance); // Expected value of variance.
   
       // Parameter estimators from
       // either alpha or beta, and x and probability.
       
-      static RealType find_alpha(
+      BOOST_MATH_GPU_ENABLED static RealType find_alpha(
         RealType beta, // from beta.
         RealType x, //  x.
         RealType probability); // cdf
       
-      static RealType find_beta(
+      BOOST_MATH_GPU_ENABLED static RealType find_beta(
         RealType alpha, // alpha.
         RealType x, // probability x.
         RealType probability); // probability cdf.
@@ -98,7 +98,7 @@ whose apex is away from the centre (where x = half).
 
 [h5 Constructor]
 
-   beta_distribution(RealType alpha, RealType beta);
+   BOOST_MATH_GPU_ENABLED beta_distribution(RealType alpha, RealType beta);
 
 Constructs a beta distribution with shape parameters /alpha/ and /beta/.
 
@@ -117,11 +117,11 @@ in the graph above).
 
 [h5 Parameter Accessors]
 
-   RealType alpha() const;
+   BOOST_MATH_GPU_ENABLED RealType alpha() const;
    
 Returns the parameter /alpha/ from which this distribution was constructed.
    
-   RealType beta() const;
+   BOOST_MATH_GPU_ENABLED RealType beta() const;
    
 Returns the parameter /beta/ from which this distribution was constructed.
 
@@ -182,6 +182,8 @@ Returns the value of [beta] that gives:
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The formulae for calculating these are shown in the table below, and at
 [@http://mathworld.wolfram.com/BetaDistribution.html Wolfram Mathworld].
diff --git a/doc/distributions/cauchy.qbk b/doc/distributions/cauchy.qbk
index 2d388740a3..e59e3760ed 100644
--- a/doc/distributions/cauchy.qbk
+++ b/doc/distributions/cauchy.qbk
@@ -15,10 +15,10 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
 
-      cauchy_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED cauchy_distribution(RealType location = 0, RealType scale = 1);
       
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
    
 The [@http://en.wikipedia.org/wiki/Cauchy_distribution Cauchy-Lorentz distribution]
@@ -53,7 +53,7 @@ the distribution:
 
 [h4 Member Functions]
 
-   cauchy_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED cauchy_distribution(RealType location = 0, RealType scale = 1);
    
 Constructs a Cauchy distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
@@ -62,11 +62,11 @@ then the result is a Standard Cauchy Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
    
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
    
 Returns the location parameter of the distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
    
 Returns the scale parameter of the distribution.
 
@@ -74,6 +74,8 @@ Returns the scale parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Note however that the Cauchy distribution does not have a mean,
 standard deviation, etc. See __math_undefined
diff --git a/doc/distributions/chi_squared.qbk b/doc/distributions/chi_squared.qbk
index 753e1f401d..b52d4d392d 100644
--- a/doc/distributions/chi_squared.qbk
+++ b/doc/distributions/chi_squared.qbk
@@ -18,13 +18,13 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      chi_squared_distribution(RealType i);
+      BOOST_MATH_GPU_ENABLED chi_squared_distribution(RealType i);
 
       // Accessor to parameter:
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
       // Parameter estimation:
-      static RealType find_degrees_of_freedom(
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(
          RealType difference_from_mean,
          RealType alpha,
          RealType beta,
@@ -104,6 +104,8 @@ See also section on Sample sizes required in
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 (We have followed the usual restriction of the mode to degrees of freedom >= 2,
 but note that the maximum of the pdf is actually zero for degrees of freedom from 2 down to 0,
diff --git a/doc/distributions/exponential.qbk b/doc/distributions/exponential.qbk
index b47f0b8bcd..3c90a96483 100644
--- a/doc/distributions/exponential.qbk
+++ b/doc/distributions/exponential.qbk
@@ -15,9 +15,9 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      exponential_distribution(RealType lambda = 1);
+      BOOST_MATH_GPU_ENABLED exponential_distribution(RealType lambda = 1);
 
-      RealType lambda()const;
+      BOOST_MATH_GPU_ENABLED RealType lambda()const;
    };
 
 
@@ -37,7 +37,7 @@ values of the rate parameter lambda:
 
 [h4 Member Functions]
 
-   exponential_distribution(RealType lambda = 1);
+   BOOST_MATH_GPU_ENABLED exponential_distribution(RealType lambda = 1);
    
 Constructs an
 [@http://en.wikipedia.org/wiki/Exponential_distribution Exponential distribution]
@@ -46,7 +46,7 @@ Lambda is defined as the reciprocal of the scale parameter.
 
 Requires lambda > 0, otherwise calls __domain_error.
 
-   RealType lambda()const;
+   BOOST_MATH_GPU_ENABLED RealType lambda()const;
    
 Accessor function returns the lambda parameter of the distribution.
    
@@ -54,6 +54,8 @@ Accessor function returns the lambda parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 
diff --git a/doc/distributions/extreme_value.qbk b/doc/distributions/extreme_value.qbk
index 43f68546f9..f47467d2bd 100644
--- a/doc/distributions/extreme_value.qbk
+++ b/doc/distributions/extreme_value.qbk
@@ -14,10 +14,10 @@
    public:
       typedef RealType value_type;
 
-      extreme_value_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED extreme_value_distribution(RealType location = 0, RealType scale = 1);
 
-      RealType scale()const;
-      RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
    };
 
 There are various
@@ -59,18 +59,18 @@ And this graph illustrates how the PDF varies with the shape parameter:
 
 [h4 Member Functions]
 
-   extreme_value_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED extreme_value_distribution(RealType location = 0, RealType scale = 1);
    
 Constructs an Extreme Value distribution with the specified location and scale
 parameters.
 
 Requires `scale > 0`, otherwise calls __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
    
 Returns the location parameter of the distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
    
 Returns the scale parameter of the distribution.
    
@@ -78,6 +78,8 @@ Returns the scale parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random parameter is \[-[infin], +[infin]\].
 
diff --git a/doc/distributions/holtsmark.qbk b/doc/distributions/holtsmark.qbk
index 49149ab929..39c42ff133 100644
--- a/doc/distributions/holtsmark.qbk
+++ b/doc/distributions/holtsmark.qbk
@@ -15,10 +15,10 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
 
-      holtsmark_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED holtsmark_distribution(RealType location = 0, RealType scale = 1);
 
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
 The [@http://en.wikipedia.org/wiki/holtsmark_distribution Holtsmark distribution]
@@ -51,7 +51,7 @@ the distribution:
 
 [h4 Member Functions]
 
-   holtsmark_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED holtsmark_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a holtsmark distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
@@ -60,11 +60,11 @@ then the result is a Standard holtsmark Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the location parameter of the distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the scale parameter of the distribution.
 
@@ -72,6 +72,8 @@ Returns the scale parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Note however that the holtsmark distribution does not have a skewness,
 kurtosis, etc. See __math_undefined
diff --git a/doc/distributions/landau.qbk b/doc/distributions/landau.qbk
index b734505047..90dced0aa8 100644
--- a/doc/distributions/landau.qbk
+++ b/doc/distributions/landau.qbk
@@ -15,11 +15,11 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
 
-      landau_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED landau_distribution(RealType location = 0, RealType scale = 1);
 
-      RealType location()const;
-      RealType scale()const;
-      RealType bias()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType bias()const;
    };
 
 The [@http://en.wikipedia.org/wiki/landau_distribution Landau distribution]
@@ -54,7 +54,7 @@ the distribution:
 
 [h4 Member Functions]
 
-   landau_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED landau_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a landau distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
@@ -63,15 +63,15 @@ then the result is a Standard landau Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the location parameter of the distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the scale parameter of the distribution.
 
-   RealType bias()const;
+   BOOST_MATH_GPU_ENABLED RealType bias()const;
 
 Returns the amount of translation by the scale parameter.
 [expression bias = - 2 / [pi] log(c)]
@@ -80,6 +80,8 @@ Returns the amount of translation by the scale parameter.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Note however that the landau distribution does not have a mean,
 standard deviation, etc. See __math_undefined
diff --git a/doc/distributions/laplace.qbk b/doc/distributions/laplace.qbk
index 1afa7f4e1e..6115efcb8b 100644
--- a/doc/distributions/laplace.qbk
+++ b/doc/distributions/laplace.qbk
@@ -17,10 +17,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      laplace_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED laplace_distribution(RealType location = 0, RealType scale = 1);
       // Accessors:
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
    }} // namespaces
@@ -49,7 +49,7 @@ Note that the domain of the random variable remains
 
 [h4 Member Functions]
 
-   laplace_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED laplace_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a laplace distribution with location /location/ and
 scale /scale/.
@@ -61,11 +61,11 @@ The scale parameter is proportional to the standard deviation of the random vari
 Requires that the scale parameter is greater than zero, otherwise calls
 __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the /location/ parameter of this distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the /scale/ parameter of this distribution.
 
@@ -73,6 +73,8 @@ Returns the /scale/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[-[infin],+[infin]\].
 
diff --git a/doc/distributions/logistic.qbk b/doc/distributions/logistic.qbk
index 84b3a24f1d..dc42a5d8b3 100644
--- a/doc/distributions/logistic.qbk
+++ b/doc/distributions/logistic.qbk
@@ -15,10 +15,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      logistic_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED logistic_distribution(RealType location = 0, RealType scale = 1);
       // Accessors:
-      RealType location()const; // location.
-      RealType scale()const; // scale.
+      BOOST_MATH_GPU_ENABLED RealType location()const; // location.
+      BOOST_MATH_GPU_ENABLED RealType scale()const; // scale.
       
    };
 
@@ -39,17 +39,17 @@ parameters change:
 
 [h4 Member Functions]
 
-   logistic_distribution(RealType u = 0, RealType s = 1);
+   BOOST_MATH_GPU_ENABLED logistic_distribution(RealType u = 0, RealType s = 1);
 
 Constructs a logistic distribution with location /u/ and scale /s/.
 
 Requires `scale > 0`, otherwise a __domain_error is raised.
 
-   RealType location()const;   
+   BOOST_MATH_GPU_ENABLED RealType location()const;   
 
 Returns the location of this distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the scale of this distribution. 
 
@@ -57,6 +57,8 @@ Returns the scale of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[-\[max_value\], +\[min_value\]\]. 
 However, the pdf and cdf support inputs of +[infin] and -[infin]
diff --git a/doc/distributions/mapairy.qbk b/doc/distributions/mapairy.qbk
index 97d624a932..817fb980da 100644
--- a/doc/distributions/mapairy.qbk
+++ b/doc/distributions/mapairy.qbk
@@ -15,10 +15,10 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
 
-      mapairy_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED mapairy_distribution(RealType location = 0, RealType scale = 1);
 
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
 It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
@@ -50,7 +50,7 @@ the distribution:
 
 [h4 Member Functions]
 
-   mapairy_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED mapairy_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a mapairy distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
@@ -59,11 +59,11 @@ then the result is a Standard map-airy Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the location parameter of the distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the scale parameter of the distribution.
 
@@ -71,6 +71,8 @@ Returns the scale parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Note however that the map-airy distribution does not have a skewness,
 kurtosis, etc. See __math_undefined
diff --git a/doc/distributions/saspoint5.qbk b/doc/distributions/saspoint5.qbk
index 1421b5bac2..06efbd32e5 100644
--- a/doc/distributions/saspoint5.qbk
+++ b/doc/distributions/saspoint5.qbk
@@ -15,10 +15,10 @@
       typedef RealType  value_type;
       typedef Policy    policy_type;
 
-      saspoint5_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED saspoint5_distribution(RealType location = 0, RealType scale = 1);
 
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
 It is special case of a [@http://en.wikipedia.org/wiki/Stable_distribution stable distribution]
@@ -49,7 +49,7 @@ the distribution:
 
 [h4 Member Functions]
 
-   saspoint5_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED saspoint5_distribution(RealType location = 0, RealType scale = 1);
 
 Constructs a S[alpha]S Point5 distribution, with location parameter /location/
 and scale parameter /scale/.  When these parameters take their default
@@ -58,11 +58,11 @@ then the result is a Standard S[alpha]S Point5 Distribution.
 
 Requires scale > 0, otherwise calls __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 Returns the location parameter of the distribution.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the scale parameter of the distribution.
 
@@ -70,6 +70,8 @@ Returns the scale parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Note however that the S[alpha]S Point5 distribution does not have a mean,
 standard deviation, etc. See __math_undefined
diff --git a/doc/distributions/weibull.qbk b/doc/distributions/weibull.qbk
index 3ec18b18d9..37139ab2c6 100644
--- a/doc/distributions/weibull.qbk
+++ b/doc/distributions/weibull.qbk
@@ -17,10 +17,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      weibull_distribution(RealType shape, RealType scale = 1)
+      BOOST_MATH_GPU_ENABLED weibull_distribution(RealType shape, RealType scale = 1)
       // Accessors:
-      RealType shape()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType shape()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
    
    }} // namespaces
@@ -65,7 +65,7 @@ Samuel Kotz & Saralees Nadarajah].
    
 [h4 Member Functions]
 
-   weibull_distribution(RealType shape, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED weibull_distribution(RealType shape, RealType scale = 1);
    
 Constructs a [@http://en.wikipedia.org/wiki/Weibull_distribution 
 Weibull distribution] with shape /shape/ and scale /scale/.
@@ -73,11 +73,11 @@ Weibull distribution] with shape /shape/ and scale /scale/.
 Requires that the /shape/ and /scale/ parameters are both greater than zero, 
 otherwise calls __domain_error.
 
-   RealType shape()const;
+   BOOST_MATH_GPU_ENABLED RealType shape()const;
    
 Returns the /shape/ parameter of this distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
       
 Returns the /scale/ parameter of this distribution.
 
@@ -85,6 +85,8 @@ Returns the /scale/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, [infin]\].
 

From 846b7a60d14c44e8803c8d61d769a91a98fc9a73 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 16:08:41 -0400
Subject: [PATCH 368/399] Add markers to special functions

---
 doc/overview/gpu.qbk         |  5 +++
 doc/sf/bessel_ik.qbk         |  8 ++---
 doc/sf/bessel_jy.qbk         |  8 ++---
 doc/sf/bessel_spherical.qbk  |  8 ++---
 doc/sf/beta.qbk              |  4 +--
 doc/sf/beta_derivative.qbk   |  4 +--
 doc/sf/digamma.qbk           |  4 +--
 doc/sf/erf.qbk               | 16 ++++-----
 doc/sf/erf_inv.qbk           | 16 ++++-----
 doc/sf/gamma_derivatives.qbk |  4 +--
 doc/sf/gamma_ratios.qbk      | 16 ++++-----
 doc/sf/ibeta.qbk             | 32 +++++++++---------
 doc/sf/ibeta_inv.qbk         | 64 ++++++++++++++++++------------------
 doc/sf/igamma.qbk            | 32 +++++++++---------
 doc/sf/igamma_inv.qbk        | 32 +++++++++---------
 doc/sf/lgamma.qbk            |  8 ++---
 doc/sf/pow.qbk               |  4 +--
 doc/sf/sinc.qbk              | 12 +++----
 doc/sf/tgamma.qbk            | 16 ++++-----
 doc/sf/trigamma.qbk          |  4 +--
 20 files changed, 151 insertions(+), 146 deletions(-)

diff --git a/doc/overview/gpu.qbk b/doc/overview/gpu.qbk
index 70f0164e0a..18ebaba2a4 100644
--- a/doc/overview/gpu.qbk
+++ b/doc/overview/gpu.qbk
@@ -6,6 +6,11 @@ Selected functions, distributions, tools, etc. support running on both host and
 These functions will have the annotation `BOOST_MATH_GPU_ENABLED` next to their individual documentation.
 We test using CUDA (both NVCC and NVRTC) as well as SYCL to provide a wide range of support.
 
+[h4 Policies]
+
+The default policy on all devices is ignore error due to the lack of throwing ability.
+A user can specify their own policy like usual, but when the code is run on device it will be ignored.
+
 [h4 How to build with device support]
 
 When compiling with CUDA or SYCL you will have to ensure that your code is being run inside of a kernel function.
diff --git a/doc/sf/bessel_ik.qbk b/doc/sf/bessel_ik.qbk
index d044ac7b80..9fa4e63a74 100644
--- a/doc/sf/bessel_ik.qbk
+++ b/doc/sf/bessel_ik.qbk
@@ -5,16 +5,16 @@
 `#include <boost/math/special_functions/bessel.hpp>`
 
    template <class T1, class T2>
-   ``__sf_result`` cyl_bessel_i(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_i(T1 v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` cyl_bessel_i(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_i(T1 v, T2 x, const ``__Policy``&);
 
    template <class T1, class T2>
-   ``__sf_result`` cyl_bessel_k(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_k(T1 v, T2 x);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` cyl_bessel_k(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_k(T1 v, T2 x, const ``__Policy``&);
    
    
 [h4 Description]
diff --git a/doc/sf/bessel_jy.qbk b/doc/sf/bessel_jy.qbk
index 1f43bc7580..faf8788500 100644
--- a/doc/sf/bessel_jy.qbk
+++ b/doc/sf/bessel_jy.qbk
@@ -5,16 +5,16 @@
 `#include <boost/math/special_functions/bessel.hpp>`
 
    template <class T1, class T2>
-   ``__sf_result`` cyl_bessel_j(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_j(T1 v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` cyl_bessel_j(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_bessel_j(T1 v, T2 x, const ``__Policy``&);
 
    template <class T1, class T2>
-   ``__sf_result`` cyl_neumann(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_neumann(T1 v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` cyl_neumann(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` cyl_neumann(T1 v, T2 x, const ``__Policy``&);
 
 
 [h4 Description]
diff --git a/doc/sf/bessel_spherical.qbk b/doc/sf/bessel_spherical.qbk
index e9cda89c70..eb1fa69154 100644
--- a/doc/sf/bessel_spherical.qbk
+++ b/doc/sf/bessel_spherical.qbk
@@ -5,16 +5,16 @@
 `#include <boost/math/special_functions/bessel.hpp>`
 
    template <class T1, class T2>
-   ``__sf_result`` sph_bessel(unsigned v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sph_bessel(unsigned v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` sph_bessel(unsigned v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sph_bessel(unsigned v, T2 x, const ``__Policy``&);
 
    template <class T1, class T2>
-   ``__sf_result`` sph_neumann(unsigned v, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sph_neumann(unsigned v, T2 x);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` sph_neumann(unsigned v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sph_neumann(unsigned v, T2 x, const ``__Policy``&);
    
 [h4 Description]
 
diff --git a/doc/sf/beta.qbk b/doc/sf/beta.qbk
index e332fa5030..7e1904c254 100644
--- a/doc/sf/beta.qbk
+++ b/doc/sf/beta.qbk
@@ -9,10 +9,10 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2>
-   ``__sf_result`` beta(T1 a, T2 b);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` beta(T1 a, T2 b, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b, const ``__Policy``&);
    
    }} // namespaces
 
diff --git a/doc/sf/beta_derivative.qbk b/doc/sf/beta_derivative.qbk
index 8606d6f2b3..5d3b9a13ef 100644
--- a/doc/sf/beta_derivative.qbk
+++ b/doc/sf/beta_derivative.qbk
@@ -9,10 +9,10 @@
    namespace boost{ namespace math{ 
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_derivative(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_derivative(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_derivative(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_derivative(T1 a, T2 b, T3 x, const ``__Policy``&);
    
    }} // namespaces
    
diff --git a/doc/sf/digamma.qbk b/doc/sf/digamma.qbk
index c88c5fe7b0..78b68403d8 100644
--- a/doc/sf/digamma.qbk
+++ b/doc/sf/digamma.qbk
@@ -9,10 +9,10 @@
   namespace boost{ namespace math{
   
   template <class T>
-  ``__sf_result`` digamma(T z);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` digamma(T z);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` digamma(T z, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` digamma(T z, const ``__Policy``&);
   
   }} // namespaces
   
diff --git a/doc/sf/erf.qbk b/doc/sf/erf.qbk
index 3207b66c07..5f6bdf9fa5 100644
--- a/doc/sf/erf.qbk
+++ b/doc/sf/erf.qbk
@@ -9,16 +9,16 @@
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` erf(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erf(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf(T z, const ``__Policy``&);
    
    template <class T>
-   ``__sf_result`` erfc(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erfc(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc(T z, const ``__Policy``&);
    
    }} // namespaces
    
@@ -30,10 +30,10 @@ the return type is `double` if T is an integer type, and T otherwise.
 [h4 Description]
 
    template <class T>
-   ``__sf_result`` erf(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erf(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf(T z, const ``__Policy``&);
    
 Returns the [@http://en.wikipedia.org/wiki/Error_function error function]
 [@http://functions.wolfram.com/GammaBetaErf/Erf/ erf] of z:
@@ -43,10 +43,10 @@ Returns the [@http://en.wikipedia.org/wiki/Error_function error function]
 [graph erf]
 
    template <class T>
-   ``__sf_result`` erfc(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erfc(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc(T z, const ``__Policy``&);
    
 Returns the complement of the [@http://functions.wolfram.com/GammaBetaErf/Erfc/ error function] of z:
 
diff --git a/doc/sf/erf_inv.qbk b/doc/sf/erf_inv.qbk
index 729ec22d28..e8f7464e09 100644
--- a/doc/sf/erf_inv.qbk
+++ b/doc/sf/erf_inv.qbk
@@ -9,16 +9,16 @@
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` erf_inv(T p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf_inv(T p);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erf_inv(T p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf_inv(T p, const ``__Policy``&);
    
    template <class T>
-   ``__sf_result`` erfc_inv(T p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc_inv(T p);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erfc_inv(T p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc_inv(T p, const ``__Policy``&);
    
    }} // namespaces
    
@@ -30,10 +30,10 @@ the return type is `double` if T is an integer type, and T otherwise.
 [h4 Description]
 
    template <class T>
-   ``__sf_result`` erf_inv(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf_inv(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erf_inv(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erf_inv(T z, const ``__Policy``&);
    
 Returns the [@http://functions.wolfram.com/GammaBetaErf/InverseErf/ inverse error function]
 of z, that is a value x such that:
@@ -43,10 +43,10 @@ of z, that is a value x such that:
 [graph erf_inv]
 
    template <class T>
-   ``__sf_result`` erfc_inv(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc_inv(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` erfc_inv(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` erfc_inv(T z, const ``__Policy``&);
    
 Returns the inverse of the complement of the error function of z, that is a
 value x such that:
diff --git a/doc/sf/gamma_derivatives.qbk b/doc/sf/gamma_derivatives.qbk
index c7dd248799..1b578d8d98 100644
--- a/doc/sf/gamma_derivatives.qbk
+++ b/doc/sf/gamma_derivatives.qbk
@@ -9,10 +9,10 @@
    namespace boost{ namespace math{ 
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_p_derivative(T1 a, T2 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_derivative(T1 a, T2 x);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p_derivative(T1 a, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_derivative(T1 a, T2 x, const ``__Policy``&);
    
    }} // namespaces
    
diff --git a/doc/sf/gamma_ratios.qbk b/doc/sf/gamma_ratios.qbk
index a3fcf864cb..0d076890d3 100644
--- a/doc/sf/gamma_ratios.qbk
+++ b/doc/sf/gamma_ratios.qbk
@@ -7,26 +7,26 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2>
-   ``__sf_result`` tgamma_ratio(T1 a, T2 b);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_ratio(T1 a, T2 b);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma_ratio(T1 a, T2 b, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_ratio(T1 a, T2 b, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta);
    
    template <class T1, class T2, class Policy>
-   ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta, const ``__Policy``&);
    
    }} // namespaces
    
 [h4 Description]
 
    template <class T1, class T2> 
-   ``__sf_result`` tgamma_ratio(T1 a, T2 b);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_ratio(T1 a, T2 b);
    
    template <class T1, class T2, class ``__Policy``> 
-   ``__sf_result`` tgamma_ratio(T1 a, T2 b, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_ratio(T1 a, T2 b, const ``__Policy``&);
    
 Returns the ratio of gamma functions:
 
@@ -37,10 +37,10 @@ Returns the ratio of gamma functions:
 Internally this just calls `tgamma_delta_ratio(a, b-a)`.
    
    template <class T1, class T2>
-   ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_delta_ratio(T1 a, T2 delta, const ``__Policy``&);
    
 Returns the ratio of gamma functions:
 
diff --git a/doc/sf/ibeta.qbk b/doc/sf/ibeta.qbk
index b4a20f9286..5227b2d342 100644
--- a/doc/sf/ibeta.qbk
+++ b/doc/sf/ibeta.qbk
@@ -9,28 +9,28 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta(T1 a, T2 b, T3 x, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac(T1 a, T2 b, T3 x, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` beta(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` beta(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b, T3 x, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` betac(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` betac(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` betac(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` betac(T1 a, T2 b, T3 x, const ``__Policy``&);
    
    }} // namespaces
    
@@ -57,10 +57,10 @@ when T1, T2 and T3 are different types.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta(T1 a, T2 b, T3 x);
 
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta(T1 a, T2 b, T3 x, const ``__Policy``&);
 
 Returns the normalised incomplete beta function of a, b and x:
 
@@ -69,30 +69,30 @@ Returns the normalised incomplete beta function of a, b and x:
 [graph ibeta]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac(T1 a, T2 b, T3 x);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac(T1 a, T2 b, T3 x, const ``__Policy``&);
    
 Returns the normalised complement of the incomplete beta function of a, b and x:
 
 [equation ibeta4]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` beta(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b, T3 x);
 
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` beta(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` beta(T1 a, T2 b, T3 x, const ``__Policy``&);
 
 Returns the full (non-normalised) incomplete beta function of a, b and x:
 
 [equation ibeta1]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` betac(T1 a, T2 b, T3 x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` betac(T1 a, T2 b, T3 x);
 
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` betac(T1 a, T2 b, T3 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` betac(T1 a, T2 b, T3 x, const ``__Policy``&);
 
 Returns the full (non-normalised) complement of the incomplete beta function of a, b and x:
 
diff --git a/doc/sf/ibeta_inv.qbk b/doc/sf/ibeta_inv.qbk
index 83c2b00086..60049db465 100644
--- a/doc/sf/ibeta_inv.qbk
+++ b/doc/sf/ibeta_inv.qbk
@@ -7,52 +7,52 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, const ``__Policy``&);
    
    template <class T1, class T2, class T3, class T4>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py);
    
    template <class T1, class T2, class T3, class T4, class ``__Policy``>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, const ``__Policy``&);
    
    template <class T1, class T2, class T3, class T4>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py);
    
    template <class T1, class T2, class T3, class T4, class ``__Policy``>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 q);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 q, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_invb(T1 a, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_invb(T1 a, T2 x, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_invb(T1 a, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_invb(T1 a, T2 x, T3 p, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_invb(T1 a, T2 x, T3 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_invb(T1 a, T2 x, T3 q);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_invb(T1 a, T2 x, T3 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_invb(T1 a, T2 x, T3 q, const ``__Policy``&);
    
    }} // namespaces
    
@@ -81,16 +81,16 @@ The return type of these functions is computed using the __arg_promotion_rules
 when called with arguments T1...TN of different types.
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, const ``__Policy``&);
    
    template <class T1, class T2, class T3, class T4>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py);
    
    template <class T1, class T2, class T3, class T4, class ``__Policy``>
-   ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibeta_inv(T1 a, T2 b, T3 p, T4* py, const ``__Policy``&);
    
 Returns a value /x/ such that: `p = ibeta(a, b, x);` 
 and sets `*py = 1 - x` when the `py` parameter is provided and is non-null.  
@@ -104,16 +104,16 @@ Requires:  /a,b > 0/ and /0 <= p <= 1/.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, const ``__Policy``&);
    
    template <class T1, class T2, class T3, class T4>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py);
    
    template <class T1, class T2, class T3, class T4, class ``__Policy``>
-   ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_inv(T1 a, T2 b, T3 q, T4* py, const ``__Policy``&);
    
 Returns a value /x/ such that: `q = ibetac(a, b, x);`
 and sets `*py = 1 - x` when the `py` parameter is provided and is non-null.  
@@ -127,10 +127,10 @@ Requires:  /a,b > 0/ and /0 <= q <= 1/.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p);
 
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibeta_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
 
 Returns a value /a/ such that: `p = ibeta(a, b, x);`
 
@@ -139,10 +139,10 @@ Requires:  /b > 0/, /0 < x < 1/ and /0 <= p <= 1/.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibetac_inva(T1 b, T2 x, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibetac_inva(T1 b, T2 x, T3 p, const ``__Policy``&);
    
 Returns a value /a/ such that: `q = ibetac(a, b, x);`
 
@@ -151,10 +151,10 @@ Requires:  /b > 0/, /0 < x < 1/ and /0 <= q <= 1/.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibeta_invb(T1 b, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibeta_invb(T1 b, T2 x, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibeta_invb(T1 b, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibeta_invb(T1 b, T2 x, T3 p, const ``__Policy``&);
 
 Returns a value /b/ such that: `p = ibeta(a, b, x);`
 
@@ -163,10 +163,10 @@ Requires:  /a > 0/, /0 < x < 1/ and /0 <= p <= 1/.
 [optional_policy]
 
    template <class T1, class T2, class T3>
-   ``__sf_result`` ibetac_invb(T1 b, T2 x, T3 p);
+   BOOST_MATH_GPU_ENABLED``__sf_result`` ibetac_invb(T1 b, T2 x, T3 p);
    
    template <class T1, class T2, class T3, class ``__Policy``>
-   ``__sf_result`` ibetac_invb(T1 b, T2 x, T3 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` ibetac_invb(T1 b, T2 x, T3 p, const ``__Policy``&);
    
 Returns a value /b/ such that: `q = ibetac(a, b, x);`
 
diff --git a/doc/sf/igamma.qbk b/doc/sf/igamma.qbk
index ca354ad10f..4675928e63 100644
--- a/doc/sf/igamma.qbk
+++ b/doc/sf/igamma.qbk
@@ -9,28 +9,28 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_p(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p(T1 a, T2 z);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p(T1 a, T2 z, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_q(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q(T1 a, T2 z);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q(T1 a, T2 z, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` tgamma_lower(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_lower(T1 a, T2 z);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma_lower(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_lower(T1 a, T2 z, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` tgamma(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T1 a, T2 z);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T1 a, T2 z, const ``__Policy``&);
    
    }} // namespaces
    
@@ -53,10 +53,10 @@ The return type of these functions is computed using the __arg_promotion_rules
 when T1 and T2 are different types, otherwise the return type is simply T1.
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_p(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p(T1 a, T2 z);
    
    template <class T1, class T2, class Policy>
-   ``__sf_result`` gamma_p(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p(T1 a, T2 z, const ``__Policy``&);
    
 Returns the normalised lower incomplete gamma function of a and z:
 
@@ -67,10 +67,10 @@ This function changes rapidly from 0 to 1 around the point z == a:
 [graph gamma_p]
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_q(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q(T1 a, T2 z);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q(T1 a, T2 z, const ``__Policy``&);
 
 Returns the normalised upper incomplete gamma function of a and z:
 
@@ -81,20 +81,20 @@ This function changes rapidly from 1 to 0 around the point z == a:
 [graph gamma_q]
 
    template <class T1, class T2>
-   ``__sf_result`` tgamma_lower(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_lower(T1 a, T2 z);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma_lower(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma_lower(T1 a, T2 z, const ``__Policy``&);
 
 Returns the full (non-normalised) lower incomplete gamma function of a and z:
 
 [equation igamma2]
 
    template <class T1, class T2>
-   ``__sf_result`` tgamma(T1 a, T2 z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T1 a, T2 z);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` tgamma(T1 a, T2 z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T1 a, T2 z, const ``__Policy``&);
 
 Returns the full (non-normalised) upper incomplete gamma function of a and z:
 
diff --git a/doc/sf/igamma_inv.qbk b/doc/sf/igamma_inv.qbk
index 593c92141b..55fe76e6e8 100644
--- a/doc/sf/igamma_inv.qbk
+++ b/doc/sf/igamma_inv.qbk
@@ -9,28 +9,28 @@
    namespace boost{ namespace math{
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_q_inv(T1 a, T2 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inv(T1 a, T2 q);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q_inv(T1 a, T2 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inv(T1 a, T2 q, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_p_inv(T1 a, T2 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inv(T1 a, T2 p);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p_inv(T1 a, T2 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inv(T1 a, T2 p, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_q_inva(T1 x, T2 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inva(T1 x, T2 q);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q_inva(T1 x, T2 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inva(T1 x, T2 q, const ``__Policy``&);
    
    template <class T1, class T2>
-   ``__sf_result`` gamma_p_inva(T1 x, T2 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inva(T1 x, T2 p);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p_inva(T1 x, T2 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inva(T1 x, T2 p, const ``__Policy``&);
    
    }} // namespaces
    
@@ -58,40 +58,40 @@ These are implemented here as `gamma_p_inva` and `gamma_q_inva`.]
 
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_q_inv(T1 a, T2 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inv(T1 a, T2 q);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q_inv(T1 a, T2 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inv(T1 a, T2 q, const ``__Policy``&);
 
 Returns a value x such that: `q = gamma_q(a, x);`
 
 Requires: /a > 0/ and /1 >= p,q >= 0/.
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_p_inv(T1 a, T2 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inv(T1 a, T2 p);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p_inv(T1 a, T2 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inv(T1 a, T2 p, const ``__Policy``&);
    
 Returns a value x such that: `p = gamma_p(a, x);`
 
 Requires: /a > 0/ and /1 >= p,q >= 0/.
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_q_inva(T1 x, T2 q);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inva(T1 x, T2 q);
 
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_q_inva(T1 x, T2 q, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_q_inva(T1 x, T2 q, const ``__Policy``&);
 
 Returns a value a such that: `q = gamma_q(a, x);`
 
 Requires: /x > 0/ and /1 >= p,q >= 0/.
 
    template <class T1, class T2>
-   ``__sf_result`` gamma_p_inva(T1 x, T2 p);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inva(T1 x, T2 p);
    
    template <class T1, class T2, class ``__Policy``>
-   ``__sf_result`` gamma_p_inva(T1 x, T2 p, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` gamma_p_inva(T1 x, T2 p, const ``__Policy``&);
    
 Returns a value a such that: `p = gamma_p(a, x);`
 
diff --git a/doc/sf/lgamma.qbk b/doc/sf/lgamma.qbk
index 5ea1a4e091..544485c7ca 100644
--- a/doc/sf/lgamma.qbk
+++ b/doc/sf/lgamma.qbk
@@ -9,16 +9,16 @@
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` lgamma(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` lgamma(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` lgamma(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` lgamma(T z, const ``__Policy``&);
    
    template <class T>
-   ``__sf_result`` lgamma(T z, int* sign);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` lgamma(T z, int* sign);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` lgamma(T z, int* sign, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` lgamma(T z, int* sign, const ``__Policy``&);
    
    }} // namespaces
 
diff --git a/doc/sf/pow.qbk b/doc/sf/pow.qbk
index db021978e2..ecb762d711 100644
--- a/doc/sf/pow.qbk
+++ b/doc/sf/pow.qbk
@@ -10,10 +10,10 @@ power of a run-time base.
     namespace boost { namespace math {
 
     template <int N, typename T>
-    constexpr ``__sf_result`` pow(T base);
+    BOOST_MATH_GPU_ENABLED constexpr ``__sf_result`` pow(T base);
 
     template <int N, typename T, class Policy>
-    constexpr ``__sf_result`` pow(T base, const Policy& policy);
+    BOOST_MATH_GPU_ENABLED constexpr ``__sf_result`` pow(T base, const Policy& policy);
 
     }}
 
diff --git a/doc/sf/sinc.qbk b/doc/sf/sinc.qbk
index b345c08cd7..a6042a7171 100644
--- a/doc/sf/sinc.qbk
+++ b/doc/sf/sinc.qbk
@@ -43,16 +43,16 @@ and [@http://mathworld.wolfram.com/Octonion.html octonions].
 ``
 
    template<class T> 
-   ``__sf_result`` sinc_pi(const T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sinc_pi(const T x);
 
    template<class T, class ``__Policy``> 
-   ``__sf_result`` sinc_pi(const T x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sinc_pi(const T x, const ``__Policy``&);
 
    template<class T, template<typename> class U> 
-   U<T> sinc_pi(const U<T> x);
+   BOOST_MATH_GPU_ENABLED U<T> sinc_pi(const U<T> x);
 
    template<class T, template<typename> class U, class ``__Policy``> 
-   U<T> sinc_pi(const U<T> x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED U<T> sinc_pi(const U<T> x, const ``__Policy``&);
 
 Computes 
 [link math_toolkit.sinc.sinc_overview 
@@ -78,10 +78,10 @@ to ensure accuracy.
 ``
 
    template<class T> 
-   ``__sf_result`` sinhc_pi(const T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sinhc_pi(const T x);
 
    template<class T, class ``__Policy``> 
-   ``__sf_result`` sinhc_pi(const T x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` sinhc_pi(const T x, const ``__Policy``&);
 
    template<typename T, template<typename> class U> 
    U<T> sinhc_pi(const U<T> x);
diff --git a/doc/sf/tgamma.qbk b/doc/sf/tgamma.qbk
index 7eb535ec3a..23baad2cb8 100644
--- a/doc/sf/tgamma.qbk
+++ b/doc/sf/tgamma.qbk
@@ -9,26 +9,26 @@
   namespace boost{ namespace math{
   
   template <class T>
-  ``__sf_result`` tgamma(T z);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T z);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` tgamma(T z, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T z, const ``__Policy``&);
   
   template <class T>
-  ``__sf_result`` tgamma1pm1(T dz);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma1pm1(T dz);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&);
   
   }} // namespaces
   
 [h4 Description]
 
   template <class T>
-  ``__sf_result`` tgamma(T z);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T z);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` tgamma(T z, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma(T z, const ``__Policy``&);
   
 Returns the "true gamma" (hence name tgamma) of value z:
 
@@ -42,10 +42,10 @@ The return type of this function is computed using the __arg_promotion_rules:
 the result is `double` when T is an integer type, and T otherwise.
 
   template <class T>
-  ``__sf_result`` tgamma1pm1(T dz);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma1pm1(T dz);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` tgamma1pm1(T dz, const ``__Policy``&);
   
 Returns `tgamma(dz + 1) - 1`.  Internally the implementation does not make
 use of the addition and subtraction implied by the definition, leading to
diff --git a/doc/sf/trigamma.qbk b/doc/sf/trigamma.qbk
index 137a148d83..a358c85713 100644
--- a/doc/sf/trigamma.qbk
+++ b/doc/sf/trigamma.qbk
@@ -9,10 +9,10 @@
   namespace boost{ namespace math{
   
   template <class T>
-  ``__sf_result`` trigamma(T x);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` trigamma(T x);
   
   template <class T, class ``__Policy``>
-  ``__sf_result`` trigamma(T x, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` trigamma(T x, const ``__Policy``&);
   
   }} // namespaces
   

From e6db32aa0a06ad2069b07e92938887d8b37a0df7 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 16:11:45 -0400
Subject: [PATCH 369/399] Add markers to Newton-Rhapson

---
 doc/roots/roots.qbk | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/doc/roots/roots.qbk b/doc/roots/roots.qbk
index a229300690..ee3619f4f0 100644
--- a/doc/roots/roots.qbk
+++ b/doc/roots/roots.qbk
@@ -10,10 +10,10 @@
    namespace tools { // Note namespace boost::math::tools.
    // Newton-Raphson
    template <class F, class T>
-   T newton_raphson_iterate(F f, T guess, T min, T max, int digits);
+   BOOST_MATH_GPU_ENABLED T newton_raphson_iterate(F f, T guess, T min, T max, int digits);
 
    template <class F, class T>
-   T newton_raphson_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t& max_iter);
+   BOOST_MATH_GPU_ENABLED T newton_raphson_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t& max_iter);
 
    // Halley
    template <class F, class T>

From 2def550bfe3484d258646f7c27d5052e8fa67261 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 30 Aug 2024 16:14:06 -0400
Subject: [PATCH 370/399] Replace broken umalut-o with oe (Ersatzschreibung)

---
 doc/roots/roots.qbk | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/doc/roots/roots.qbk b/doc/roots/roots.qbk
index ee3619f4f0..ea347639b9 100644
--- a/doc/roots/roots.qbk
+++ b/doc/roots/roots.qbk
@@ -1,4 +1,4 @@
-[section:roots_deriv Root Finding With Derivatives: Newton-Raphson, Halley & Schr'''&#xf6;'''der]
+[section:roots_deriv Root Finding With Derivatives: Newton-Raphson, Halley & Schroeder]
 
 [h4 Synopsis]
 
@@ -22,7 +22,7 @@
    template <class F, class T>
    T halley_iterate(F f, T guess, T min, T max, int digits, std::uintmax_t& max_iter);
 
-   // Schr'''&#xf6;'''der
+   // Schroeder
    template <class F, class T>
    T schroder_iterate(F f, T guess, T min, T max, int digits);
 
@@ -61,7 +61,7 @@ For second-order iterative method ([@http://en.wikipedia.org/wiki/Newton_Raphson
 
 For the third-order methods
 ([@http://en.wikipedia.org/wiki/Halley%27s_method Halley] and
-Schr'''&#xf6;'''der)
+Schroeder)
         the `tuple` should have [*three] elements containing the evaluation of
         the function and its first and second derivatives.]]
 [[T guess] [The initial starting value. A good guess is crucial to quick convergence!]]
@@ -147,7 +147,7 @@ Out of bounds steps revert to bisection of the current bounds.
 
 Under ideal conditions, the number of correct digits trebles with each iteration.
 
-[h4:schroder Schr'''&#xf6;'''der's Method]
+[h4:schroder Schroeder's Method]
 
 Given an initial guess x0 the subsequent values are computed using:
 
@@ -162,8 +162,8 @@ Out of bounds steps revert to __bisection_wikipedia of the current bounds.
 
 Under ideal conditions, the number of correct digits trebles with each iteration.
 
-This is Schr'''&#xf6;'''der's general result (equation 18 from [@http://drum.lib.umd.edu/handle/1903/577 Stewart, G. W.
-"On Infinitely Many Algorithms for Solving Equations." English translation of Schr'''&#xf6;'''der's original paper.
+This is Schroeder's general result (equation 18 from [@http://drum.lib.umd.edu/handle/1903/577 Stewart, G. W.
+"On Infinitely Many Algorithms for Solving Equations." English translation of Schroeder's original paper.
 College Park, MD: University of Maryland, Institute for Advanced Computer Studies, Department of Computer Science, 1993].)
 
 This method guarantees at least quadratic convergence (the same as Newton's method), and is known to work well in the presence of multiple roots:

From b8c33953e6f380221e3020ec35860668a88f99db Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 3 Sep 2024 10:33:56 -0400
Subject: [PATCH 371/399] Fix missing end section

---
 doc/overview/gpu.qbk | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/doc/overview/gpu.qbk b/doc/overview/gpu.qbk
index 18ebaba2a4..b97b059a60 100644
--- a/doc/overview/gpu.qbk
+++ b/doc/overview/gpu.qbk
@@ -55,6 +55,8 @@ And lastly on SYCL:
 
 Once your kernel function has been written then use the framework mechanism for launching the kernel.
 
+[endsect] [/section:gpu Support for GPU programming in Boost.Math]
+
 [/ 
   Copyright 2024. Matt Borland
   Distributed under the Boost Software License, Version 1.0.

From 45c774137d00ab115b63cf19c673cd9508d29569 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 3 Sep 2024 15:57:34 -0400
Subject: [PATCH 372/399] Update docs

---
 doc/distributions/fisher.qbk              | 14 ++++++++------
 doc/distributions/gamma.qbk               | 14 ++++++++------
 doc/distributions/geometric.qbk           | 16 +++++++++-------
 doc/distributions/inverse_chi_squared.qbk | 18 ++++++++++--------
 doc/distributions/inverse_gamma.qbk       | 14 ++++++++------
 5 files changed, 43 insertions(+), 33 deletions(-)

diff --git a/doc/distributions/fisher.qbk b/doc/distributions/fisher.qbk
index 80c9a9b29b..9b3a55f59d 100644
--- a/doc/distributions/fisher.qbk
+++ b/doc/distributions/fisher.qbk
@@ -17,11 +17,11 @@
       typedef RealType value_type;
       
       // Construct:
-      fisher_f_distribution(const RealType& i, const RealType& j);
+      BOOST_MATH_GPU_ENABLED fisher_f_distribution(const RealType& i, const RealType& j);
       
       // Accessors:
-      RealType degrees_of_freedom1()const;
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
    };
    
    }} //namespaces
@@ -46,7 +46,7 @@ two degrees of freedom parameters.
 
 [h4 Member Functions]
 
-      fisher_f_distribution(const RealType& df1, const RealType& df2);
+      BOOST_MATH_GPU_ENABLED fisher_f_distribution(const RealType& df1, const RealType& df2);
       
 Constructs an F-distribution with numerator degrees of freedom /df1/
 and denominator degrees of freedom /df2/.
@@ -54,11 +54,11 @@ and denominator degrees of freedom /df2/.
 Requires that /df1/ and /df2/ are both greater than zero, otherwise __domain_error
 is called.
       
-      RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
       
 Returns the numerator degrees of freedom parameter of the distribution.
 
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
       
 Returns the denominator degrees of freedom parameter of the distribution.
 
@@ -66,6 +66,8 @@ Returns the denominator degrees of freedom parameter of the distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 
diff --git a/doc/distributions/gamma.qbk b/doc/distributions/gamma.qbk
index 56be002194..dd34ed2fc0 100644
--- a/doc/distributions/gamma.qbk
+++ b/doc/distributions/gamma.qbk
@@ -12,10 +12,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      gamma_distribution(RealType shape, RealType scale = 1)
+      BOOST_MATH_GPU_ENABLED gamma_distribution(RealType shape, RealType scale = 1)
 
-      RealType shape()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType shape()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
    
    }} // namespaces
@@ -76,7 +76,7 @@ a dedicated Erlang Distribution.
 
 [h4 Member Functions]
 
-   gamma_distribution(RealType shape, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED gamma_distribution(RealType shape, RealType scale = 1);
    
 Constructs a gamma distribution with shape /shape/ and 
 scale /scale/.
@@ -84,11 +84,11 @@ scale /scale/.
 Requires that the shape and scale parameters are greater than zero, otherwise calls
 __domain_error.
 
-   RealType shape()const;
+   BOOST_MATH_GPU_ENABLED RealType shape()const;
    
 Returns the /shape/ parameter of this distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
       
 Returns the /scale/ parameter of this distribution.
 
@@ -96,6 +96,8 @@ Returns the /scale/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0,+[infin]\].
 
diff --git a/doc/distributions/geometric.qbk b/doc/distributions/geometric.qbk
index cf1e2bff08..2a4357a2a5 100644
--- a/doc/distributions/geometric.qbk
+++ b/doc/distributions/geometric.qbk
@@ -17,28 +17,28 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Constructor from success_fraction:
-      geometric_distribution(RealType p);
+      BOOST_MATH_GPU_ENABLED geometric_distribution(RealType p);
       
       // Parameter accessors:
-      RealType success_fraction() const;
-      RealType successes() const;
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const;
+      BOOST_MATH_GPU_ENABLED RealType successes() const;
      
       // Bounds on success fraction:
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
          RealType trials, 
          RealType successes,
          RealType probability); // alpha
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
          RealType trials, 
          RealType successes,
          RealType probability); // alpha
          
       // Estimate min/max number of trials:
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
@@ -268,6 +268,8 @@ of observing more than k failures.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 However it's worth taking a moment to define what these actually mean in 
 the context of this distribution:
diff --git a/doc/distributions/inverse_chi_squared.qbk b/doc/distributions/inverse_chi_squared.qbk
index 7bc75a8813..8d67082d07 100644
--- a/doc/distributions/inverse_chi_squared.qbk
+++ b/doc/distributions/inverse_chi_squared.qbk
@@ -12,11 +12,11 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      inverse_chi_squared_distribution(RealType df = 1); // Not explicitly scaled, default 1/df.
-      inverse_chi_squared_distribution(RealType df, RealType scale = 1/df);  // Scaled.
+      BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df = 1); // Not explicitly scaled, default 1/df.
+      BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df, RealType scale = 1/df);  // Scaled.
 
-      RealType degrees_of_freedom()const; // Default 1.
-      RealType scale()const; // Optional scale [xi] (variance), default 1/degrees_of_freedom.
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const; // Default 1.
+      BOOST_MATH_GPU_ENABLED RealType scale()const; // Optional scale [xi] (variance), default 1/degrees_of_freedom.
    };
    
    }} // namespace boost // namespace math
@@ -99,8 +99,8 @@ varies for a few values of parameters [nu] and [xi]:
 
 [h4 Member Functions]
 
-   inverse_chi_squared_distribution(RealType df = 1); // Implicitly scaled 1/df.
-   inverse_chi_squared_distribution(RealType df = 1, RealType scale); // Explicitly scaled.
+   BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df = 1); // Implicitly scaled 1/df.
+   BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df = 1, RealType scale); // Explicitly scaled.
 
 Constructs an inverse chi_squared distribution with [nu] degrees of freedom ['df],
 and scale ['scale] with default value 1\/df.
@@ -108,11 +108,11 @@ and scale ['scale] with default value 1\/df.
 Requires that the degrees of freedom [nu] parameter is greater than zero, otherwise calls
 __domain_error.
 
-   RealType degrees_of_freedom()const; 
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const; 
    
 Returns the degrees_of_freedom [nu] parameter of this distribution.
 
-   RealType scale()const; 
+   BOOST_MATH_GPU_ENABLED RealType scale()const; 
    
 Returns the scale [xi] parameter of this distribution.
 
@@ -120,6 +120,8 @@ Returns the scale [xi] parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variate is \[0,+[infin]\].
 [note Unlike some definitions, this implementation supports a random variate 
diff --git a/doc/distributions/inverse_gamma.qbk b/doc/distributions/inverse_gamma.qbk
index 51d6538846..f657ec31b4 100644
--- a/doc/distributions/inverse_gamma.qbk
+++ b/doc/distributions/inverse_gamma.qbk
@@ -12,10 +12,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      inverse_gamma_distribution(RealType shape, RealType scale = 1)
+      BOOST_MATH_GPU_ENABLED inverse_gamma_distribution(RealType shape, RealType scale = 1)
 
-      RealType shape()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType shape()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
    
    }} // namespaces
@@ -63,18 +63,18 @@ varies as the parameters vary:
 
 [h4 Member Functions]
 
-   inverse_gamma_distribution(RealType shape = 1, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED inverse_gamma_distribution(RealType shape = 1, RealType scale = 1);
    
 Constructs an inverse gamma distribution with shape [alpha] and scale [beta].
 
 Requires that the shape and scale parameters are greater than zero, otherwise calls
 __domain_error.
 
-   RealType shape()const;
+   BOOST_MATH_GPU_ENABLED RealType shape()const;
    
 Returns the [alpha] shape parameter of this inverse gamma distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
       
 Returns the [beta] scale parameter of this inverse gamma distribution.
 
@@ -82,6 +82,8 @@ Returns the [beta] scale parameter of this inverse gamma distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variate is \[0,+[infin]\].
 [note Unlike some definitions, this implementation supports a random variate 

From d01893d215f9069849f34c667c467b1112882e64 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 3 Sep 2024 10:48:07 -0400
Subject: [PATCH 373/399] Add GPU markers to fisher f dist

Add SYCL testing of fisher f dist

Add CUDA fisher f dist testing

Add NVRTC fisher f dist testing

Add GPU support to gamma dist

Add SYCL testing of gamma dist

Add CUDA gamma dist testing

Add NVRTC gamma dist testing

Reduce number of threads per block since it can crash CI

Add GPU support to the geometric dist

Add SYCL testing of geometric dist

Add cuda::std::tie

Add GPU support to inv_discrete_quantile

Add CUDA testing of geometric dist

Add NVRTC testing of geometric dist

Add SYCL testing of inverse_chi_squared dist

Adjust tol

Add NVRTC inverse chi squared dist testing

Add CUDA inverse chi squared dist testing

Add GPU support to inverse gamma dist

Add SYCL testing to inverse gamma dist

Add NVRTC testing of inverse gamma dist

Add CUDA testing of inverse gamma dist
---
 .../detail/inv_discrete_quantile.hpp          |  71 ++++---
 include/boost/math/distributions/fisher_f.hpp |  69 +++----
 include/boost/math/distributions/gamma.hpp    |  84 ++++----
 .../boost/math/distributions/geometric.hpp    |  93 +++++----
 .../distributions/inverse_chi_squared.hpp     |  68 +++----
 .../math/distributions/inverse_gamma.hpp      |  77 +++----
 include/boost/math/tools/tuple.hpp            |   1 +
 test/cuda_jamfile                             |  35 ++++
 test/nvrtc_jamfile                            |  35 ++++
 test/sycl_jamfile                             |   5 +
 test/test_arcsine_cdf_double.cu               |   2 +-
 test/test_arcsine_cdf_float.cu                |   2 +-
 test/test_arcsine_pdf_double.cu               |   2 +-
 test/test_arcsine_pdf_float.cu                |   2 +-
 test/test_arcsine_quan_double.cu              |   2 +-
 test/test_arcsine_quan_float.cu               |   2 +-
 test/test_arcsine_range_support_double.cu     |   2 +-
 test/test_arcsine_range_support_float.cu      |   2 +-
 test/test_bernoulli_cdf_double.cu             |   2 +-
 test/test_bernoulli_cdf_float.cu              |   2 +-
 test/test_bernoulli_pdf_double.cu             |   2 +-
 test/test_bernoulli_pdf_float.cu              |   2 +-
 test/test_bernoulli_range_support_double.cu   |   2 +-
 test/test_bernoulli_range_support_float.cu    |   2 +-
 test/test_beta_dist_cdf_double.cu             |   2 +-
 test/test_beta_dist_cdf_float.cu              |   2 +-
 test/test_beta_dist_pdf_double.cu             |   2 +-
 test/test_beta_dist_pdf_float.cu              |   2 +-
 test/test_beta_dist_quan_double.cu            |   2 +-
 test/test_beta_dist_quan_float.cu             |   2 +-
 test/test_cauchy_cdf_double.cu                |   2 +-
 test/test_cauchy_cdf_float.cu                 |   2 +-
 test/test_cauchy_pdf_double.cu                |   2 +-
 test/test_cauchy_pdf_float.cu                 |   2 +-
 test/test_cauchy_quan_double.cu               |   2 +-
 test/test_cauchy_quan_float.cu                |   2 +-
 test/test_cauchy_range_support_double.cu      |   2 +-
 test/test_cauchy_range_support_float.cu       |   2 +-
 test/test_chi_squared_cdf_double.cu           |   2 +-
 test/test_chi_squared_cdf_float.cu            |   2 +-
 test/test_chi_squared_pdf_double.cu           |   2 +-
 test/test_chi_squared_pdf_float.cu            |   2 +-
 test/test_chi_squared_quan_double.cu          |   2 +-
 test/test_chi_squared_quan_float.cu           |   2 +-
 test/test_exponential_cdf_double.cu           |   2 +-
 test/test_exponential_cdf_float.cu            |   2 +-
 test/test_exponential_pdf_double.cu           |   2 +-
 test/test_exponential_pdf_float.cu            |   2 +-
 test/test_exponential_quan_double.cu          |   2 +-
 test/test_exponential_quan_float.cu           |   2 +-
 test/test_exponential_range_support_double.cu |   2 +-
 test/test_exponential_range_support_float.cu  |   2 +-
 test/test_extreme_value_cdf_double.cu         |   2 +-
 test/test_extreme_value_cdf_float.cu          |   2 +-
 test/test_extreme_value_pdf_double.cu         |   2 +-
 test/test_extreme_value_pdf_float.cu          |   2 +-
 test/test_extreme_value_quan_double.cu        |   2 +-
 test/test_extreme_value_quan_float.cu         |   2 +-
 test/test_fisher_f.cpp                        |   6 +-
 test/test_fisher_f_cdf_double.cu              | 109 ++++++++++
 test/test_fisher_f_cdf_float.cu               | 109 ++++++++++
 test/test_fisher_f_cdf_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_fisher_f_cdf_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_fisher_f_pdf_double.cu              | 109 ++++++++++
 test/test_fisher_f_pdf_float.cu               | 109 ++++++++++
 test/test_fisher_f_pdf_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_fisher_f_pdf_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_fisher_f_quan_double.cu             | 109 ++++++++++
 test/test_fisher_f_quan_float.cu              | 109 ++++++++++
 test/test_fisher_f_quan_nvrtc_double.cpp      | 191 ++++++++++++++++++
 test/test_fisher_f_quan_nvrtc_float.cpp       | 191 ++++++++++++++++++
 test/test_gamma_dist.cpp                      |   9 +-
 test/test_gamma_dist_cdf_double.cu            | 109 ++++++++++
 test/test_gamma_dist_cdf_float.cu             | 109 ++++++++++
 test/test_gamma_dist_cdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_gamma_dist_cdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_gamma_dist_pdf_double.cu            | 109 ++++++++++
 test/test_gamma_dist_pdf_float.cu             | 109 ++++++++++
 test/test_gamma_dist_pdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_gamma_dist_pdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_gamma_dist_quan_double.cu           | 109 ++++++++++
 test/test_gamma_dist_quan_float.cu            | 109 ++++++++++
 test/test_gamma_dist_quan_nvrtc_double.cpp    | 191 ++++++++++++++++++
 test/test_gamma_dist_quan_nvrtc_float.cpp     | 191 ++++++++++++++++++
 test/test_geometric.cpp                       |  18 +-
 test/test_geometric_dist_cdf_double.cu        | 109 ++++++++++
 test/test_geometric_dist_cdf_float.cu         | 109 ++++++++++
 test/test_geometric_dist_cdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_geometric_dist_cdf_nvrtc_float.cpp  | 191 ++++++++++++++++++
 test/test_geometric_dist_pdf_double.cu        | 109 ++++++++++
 test/test_geometric_dist_pdf_float.cu         | 109 ++++++++++
 test/test_geometric_dist_pdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_geometric_dist_pdf_nvrtc_float.cpp  | 191 ++++++++++++++++++
 test/test_geometric_dist_quan_double.cu       | 109 ++++++++++
 test/test_geometric_dist_quan_float.cu        | 109 ++++++++++
 .../test_geometric_dist_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_geometric_dist_quan_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_holtsmark_cdf_double.cu             |   2 +-
 test/test_holtsmark_cdf_float.cu              |   2 +-
 test/test_holtsmark_pdf_double.cu             |   2 +-
 test/test_holtsmark_pdf_float.cu              |   2 +-
 test/test_inverse_chi_squared_cdf_double.cu   | 110 ++++++++++
 test/test_inverse_chi_squared_cdf_float.cu    | 110 ++++++++++
 ...t_inverse_chi_squared_cdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...st_inverse_chi_squared_cdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 .../test_inverse_chi_squared_distribution.cpp |   7 +-
 test/test_inverse_chi_squared_pdf_double.cu   | 110 ++++++++++
 test/test_inverse_chi_squared_pdf_float.cu    | 110 ++++++++++
 ...t_inverse_chi_squared_pdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...st_inverse_chi_squared_pdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_inverse_chi_squared_quan_double.cu  | 110 ++++++++++
 test/test_inverse_chi_squared_quan_float.cu   | 110 ++++++++++
 ..._inverse_chi_squared_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...t_inverse_chi_squared_quan_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_inverse_gamma_cdf_double.cu         | 110 ++++++++++
 test/test_inverse_gamma_cdf_float.cu          | 110 ++++++++++
 test/test_inverse_gamma_cdf_nvrtc_double.cpp  | 191 ++++++++++++++++++
 test/test_inverse_gamma_cdf_nvrtc_float.cpp   | 191 ++++++++++++++++++
 test/test_inverse_gamma_distribution.cpp      |   7 +-
 test/test_inverse_gamma_pdf_double.cu         | 110 ++++++++++
 test/test_inverse_gamma_pdf_float.cu          | 110 ++++++++++
 test/test_inverse_gamma_pdf_nvrtc_double.cpp  | 191 ++++++++++++++++++
 test/test_inverse_gamma_pdf_nvrtc_float.cpp   | 191 ++++++++++++++++++
 test/test_inverse_gamma_quan_double.cu        | 110 ++++++++++
 test/test_inverse_gamma_quan_float.cu         | 110 ++++++++++
 test/test_inverse_gamma_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_inverse_gamma_quan_nvrtc_float.cpp  | 191 ++++++++++++++++++
 test/test_landau_cdf_double.cu                |   2 +-
 test/test_landau_cdf_float.cu                 |   2 +-
 test/test_landau_pdf_double.cu                |   2 +-
 test/test_landau_pdf_float.cu                 |   2 +-
 test/test_landau_quan_double.cu               |   2 +-
 test/test_landau_quan_float.cu                |   2 +-
 test/test_laplace_cdf_double.cu               |   2 +-
 test/test_laplace_cdf_float.cu                |   2 +-
 test/test_laplace_pdf_double.cu               |   2 +-
 test/test_laplace_pdf_float.cu                |   2 +-
 test/test_laplace_quan_double.cu              |   2 +-
 test/test_laplace_quan_float.cu               |   2 +-
 test/test_logistic_cdf_double.cu              |   2 +-
 test/test_logistic_cdf_float.cu               |   2 +-
 test/test_logistic_pdf_double.cu              |   2 +-
 test/test_logistic_pdf_float.cu               |   2 +-
 test/test_logistic_quan_double.cu             |   2 +-
 test/test_logistic_quan_float.cu              |   2 +-
 test/test_mapairy_cdf_double.cu               |   2 +-
 test/test_mapairy_cdf_float.cu                |   2 +-
 test/test_mapairy_pdf_double.cu               |   2 +-
 test/test_mapairy_pdf_float.cu                |   2 +-
 test/test_mapairy_quan_double.cu              |   2 +-
 test/test_mapairy_quan_float.cu               |   2 +-
 test/test_saspoint5_cdf_double.cu             |   2 +-
 test/test_saspoint5_cdf_float.cu              |   2 +-
 test/test_saspoint5_pdf_double.cu             |   2 +-
 test/test_saspoint5_pdf_float.cu              |   2 +-
 test/test_saspoint5_quan_double.cu            |   2 +-
 test/test_saspoint5_quan_float.cu             |   2 +-
 test/test_weibull_cdf_double.cu               |   2 +-
 test/test_weibull_cdf_float.cu                |   2 +-
 test/test_weibull_pdf_double.cu               |   2 +-
 test/test_weibull_pdf_float.cu                |   2 +-
 test/test_weibull_quan_double.cu              |   2 +-
 test/test_weibull_quan_float.cu               |   2 +-
 163 files changed, 9449 insertions(+), 324 deletions(-)
 create mode 100644 test/test_fisher_f_cdf_double.cu
 create mode 100644 test/test_fisher_f_cdf_float.cu
 create mode 100644 test/test_fisher_f_cdf_nvrtc_double.cpp
 create mode 100644 test/test_fisher_f_cdf_nvrtc_float.cpp
 create mode 100644 test/test_fisher_f_pdf_double.cu
 create mode 100644 test/test_fisher_f_pdf_float.cu
 create mode 100644 test/test_fisher_f_pdf_nvrtc_double.cpp
 create mode 100644 test/test_fisher_f_pdf_nvrtc_float.cpp
 create mode 100644 test/test_fisher_f_quan_double.cu
 create mode 100644 test/test_fisher_f_quan_float.cu
 create mode 100644 test/test_fisher_f_quan_nvrtc_double.cpp
 create mode 100644 test/test_fisher_f_quan_nvrtc_float.cpp
 create mode 100644 test/test_gamma_dist_cdf_double.cu
 create mode 100644 test/test_gamma_dist_cdf_float.cu
 create mode 100644 test/test_gamma_dist_cdf_nvrtc_double.cpp
 create mode 100644 test/test_gamma_dist_cdf_nvrtc_float.cpp
 create mode 100644 test/test_gamma_dist_pdf_double.cu
 create mode 100644 test/test_gamma_dist_pdf_float.cu
 create mode 100644 test/test_gamma_dist_pdf_nvrtc_double.cpp
 create mode 100644 test/test_gamma_dist_pdf_nvrtc_float.cpp
 create mode 100644 test/test_gamma_dist_quan_double.cu
 create mode 100644 test/test_gamma_dist_quan_float.cu
 create mode 100644 test/test_gamma_dist_quan_nvrtc_double.cpp
 create mode 100644 test/test_gamma_dist_quan_nvrtc_float.cpp
 create mode 100644 test/test_geometric_dist_cdf_double.cu
 create mode 100644 test/test_geometric_dist_cdf_float.cu
 create mode 100644 test/test_geometric_dist_cdf_nvrtc_double.cpp
 create mode 100644 test/test_geometric_dist_cdf_nvrtc_float.cpp
 create mode 100644 test/test_geometric_dist_pdf_double.cu
 create mode 100644 test/test_geometric_dist_pdf_float.cu
 create mode 100644 test/test_geometric_dist_pdf_nvrtc_double.cpp
 create mode 100644 test/test_geometric_dist_pdf_nvrtc_float.cpp
 create mode 100644 test/test_geometric_dist_quan_double.cu
 create mode 100644 test/test_geometric_dist_quan_float.cu
 create mode 100644 test/test_geometric_dist_quan_nvrtc_double.cpp
 create mode 100644 test/test_geometric_dist_quan_nvrtc_float.cpp
 create mode 100644 test/test_inverse_chi_squared_cdf_double.cu
 create mode 100644 test/test_inverse_chi_squared_cdf_float.cu
 create mode 100644 test/test_inverse_chi_squared_cdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_chi_squared_cdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_chi_squared_pdf_double.cu
 create mode 100644 test/test_inverse_chi_squared_pdf_float.cu
 create mode 100644 test/test_inverse_chi_squared_pdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_chi_squared_pdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_chi_squared_quan_double.cu
 create mode 100644 test/test_inverse_chi_squared_quan_float.cu
 create mode 100644 test/test_inverse_chi_squared_quan_nvrtc_double.cpp
 create mode 100644 test/test_inverse_chi_squared_quan_nvrtc_float.cpp
 create mode 100644 test/test_inverse_gamma_cdf_double.cu
 create mode 100644 test/test_inverse_gamma_cdf_float.cu
 create mode 100644 test/test_inverse_gamma_cdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gamma_cdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_gamma_pdf_double.cu
 create mode 100644 test/test_inverse_gamma_pdf_float.cu
 create mode 100644 test/test_inverse_gamma_pdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gamma_pdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_gamma_quan_double.cu
 create mode 100644 test/test_inverse_gamma_quan_float.cu
 create mode 100644 test/test_inverse_gamma_quan_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gamma_quan_nvrtc_float.cpp

diff --git a/include/boost/math/distributions/detail/inv_discrete_quantile.hpp b/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
index 739a866660..f688345b79 100644
--- a/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
+++ b/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
@@ -6,7 +6,11 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_DETAIL_INV_DISCRETE_QUANTILE
 #define BOOST_MATH_DISTRIBUTIONS_DETAIL_INV_DISCRETE_QUANTILE
 
-#include <algorithm>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/toms748_solve.hpp>
+#include <boost/math/tools/tuple.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
@@ -19,10 +23,10 @@ struct distribution_quantile_finder
    typedef typename Dist::value_type value_type;
    typedef typename Dist::policy_type policy_type;
 
-   distribution_quantile_finder(const Dist d, value_type p, bool c)
+   BOOST_MATH_GPU_ENABLED distribution_quantile_finder(const Dist d, value_type p, bool c)
       : dist(d), target(p), comp(c) {}
 
-   value_type operator()(value_type const& x)
+   BOOST_MATH_GPU_ENABLED value_type operator()(value_type const& x)
    {
       return comp ? value_type(target - cdf(complement(dist, x))) : value_type(cdf(dist, x) - target);
    }
@@ -42,24 +46,24 @@ struct distribution_quantile_finder
 // in the root no longer being bracketed.
 //
 template <class Real, class Tol>
-void adjust_bounds(Real& /* a */, Real& /* b */, Tol const& /* tol */){}
+BOOST_MATH_GPU_ENABLED void adjust_bounds(Real& /* a */, Real& /* b */, Tol const& /* tol */){}
 
 template <class Real>
-void adjust_bounds(Real& /* a */, Real& b, tools::equal_floor const& /* tol */)
+BOOST_MATH_GPU_ENABLED void adjust_bounds(Real& /* a */, Real& b, tools::equal_floor const& /* tol */)
 {
    BOOST_MATH_STD_USING
    b -= tools::epsilon<Real>() * b;
 }
 
 template <class Real>
-void adjust_bounds(Real& a, Real& /* b */, tools::equal_ceil const& /* tol */)
+BOOST_MATH_GPU_ENABLED void adjust_bounds(Real& a, Real& /* b */, tools::equal_ceil const& /* tol */)
 {
    BOOST_MATH_STD_USING
    a += tools::epsilon<Real>() * a;
 }
 
 template <class Real>
-void adjust_bounds(Real& a, Real& b, tools::equal_nearest_integer const& /* tol */)
+BOOST_MATH_GPU_ENABLED void adjust_bounds(Real& a, Real& b, tools::equal_nearest_integer const& /* tol */)
 {
    BOOST_MATH_STD_USING
    a += tools::epsilon<Real>() * a;
@@ -69,7 +73,7 @@ void adjust_bounds(Real& a, Real& b, tools::equal_nearest_integer const& /* tol
 // This is where all the work is done:
 //
 template <class Dist, class Tolerance>
-typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED typename Dist::value_type 
    do_inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -78,7 +82,7 @@ typename Dist::value_type
       const typename Dist::value_type& multiplier,
       typename Dist::value_type adder,
       const Tolerance& tol,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    typedef typename Dist::value_type value_type;
    typedef typename Dist::policy_type policy_type;
@@ -100,7 +104,7 @@ typename Dist::value_type
       guess = min_bound;
 
    value_type fa = f(guess);
-   std::uintmax_t count = max_iter - 1;
+   boost::math::uintmax_t count = max_iter - 1;
    value_type fb(fa), a(guess), b =0; // Compiler warning C4701: potentially uninitialized local variable 'b' used
 
    if(fa == 0)
@@ -130,7 +134,7 @@ typename Dist::value_type
          else
          {
             b = a;
-            a = (std::max)(value_type(b - 1), value_type(0));
+            a = BOOST_MATH_GPU_SAFE_MAX(value_type(b - 1), value_type(0));
             if(a < min_bound)
                a = min_bound;
             fa = f(a);
@@ -153,7 +157,7 @@ typename Dist::value_type
       // If we're looking for a large result, then bump "adder" up
       // by a bit to increase our chances of bracketing the root:
       //
-      //adder = (std::max)(adder, 0.001f * guess);
+      //adder = BOOST_MATH_GPU_SAFE_MAX(adder, 0.001f * guess);
       if(fa < 0)
       {
          b = a + adder;
@@ -162,7 +166,7 @@ typename Dist::value_type
       }
       else
       {
-         b = (std::max)(value_type(a - adder), value_type(0));
+         b = BOOST_MATH_GPU_SAFE_MAX(value_type(a - adder), value_type(0));
          if(b < min_bound)
             b = min_bound;
       }
@@ -186,7 +190,7 @@ typename Dist::value_type
          }
          else
          {
-            b = (std::max)(value_type(a - adder), value_type(0));
+            b = BOOST_MATH_GPU_SAFE_MAX(value_type(a - adder), value_type(0));
             if(b < min_bound)
                b = min_bound;
          }
@@ -195,9 +199,8 @@ typename Dist::value_type
       }
       if(a > b)
       {
-         using std::swap;
-         swap(a, b);
-         swap(fa, fb);
+         BOOST_MATH_GPU_SAFE_SWAP(a, b);
+         BOOST_MATH_GPU_SAFE_SWAP(fa, fb);
       }
    }
    //
@@ -274,7 +277,7 @@ typename Dist::value_type
    //
    // Go ahead and find the root:
    //
-   std::pair<value_type, value_type> r = toms748_solve(f, a, b, fa, fb, tol, count, policy_type());
+   boost::math::pair<value_type, value_type> r = toms748_solve(f, a, b, fa, fb, tol, count, policy_type());
    max_iter += count;
    if (max_iter >= policies::get_max_root_iterations<policy_type>())
    {
@@ -293,7 +296,7 @@ typename Dist::value_type
 // is very close 1.
 //
 template <class Dist>
-inline typename Dist::value_type round_to_floor(const Dist& d, typename Dist::value_type result, typename Dist::value_type p, bool c)
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type round_to_floor(const Dist& d, typename Dist::value_type result, typename Dist::value_type p, bool c)
 {
    BOOST_MATH_STD_USING
    typename Dist::value_type cc = ceil(result);
@@ -325,7 +328,7 @@ inline typename Dist::value_type round_to_floor(const Dist& d, typename Dist::va
 #endif
 
 template <class Dist>
-inline typename Dist::value_type round_to_ceil(const Dist& d, typename Dist::value_type result, typename Dist::value_type p, bool c)
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type round_to_ceil(const Dist& d, typename Dist::value_type result, typename Dist::value_type p, bool c)
 {
    BOOST_MATH_STD_USING
    typename Dist::value_type cc = floor(result);
@@ -339,7 +342,11 @@ inline typename Dist::value_type round_to_ceil(const Dist& d, typename Dist::val
    //
    while(true)
    {
+      #ifdef BOOST_MATH_HAS_GPU_SUPPORT
+      cc = ceil(nextafter(result, tools::max_value<typename Dist::value_type>()));
+      #else
       cc = ceil(float_next(result));
+      #endif
       if(cc > support(d).second)
          break;
       pp = c ? cdf(complement(d, cc)) : cdf(d, cc);
@@ -362,7 +369,7 @@ inline typename Dist::value_type round_to_ceil(const Dist& d, typename Dist::val
 // to an int where required.
 //
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       typename Dist::value_type p,
@@ -371,7 +378,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::real>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    if(p > 0.5)
    {
@@ -393,7 +400,7 @@ inline typename Dist::value_type
 }
 
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -402,7 +409,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::integer_round_outwards>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    typedef typename Dist::value_type value_type;
    BOOST_MATH_STD_USING
@@ -436,7 +443,7 @@ inline typename Dist::value_type
 }
 
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -445,7 +452,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::integer_round_inwards>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    typedef typename Dist::value_type value_type;
    BOOST_MATH_STD_USING
@@ -479,7 +486,7 @@ inline typename Dist::value_type
 }
 
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -488,7 +495,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::integer_round_down>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    typedef typename Dist::value_type value_type;
    BOOST_MATH_STD_USING
@@ -507,7 +514,7 @@ inline typename Dist::value_type
 }
 
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -516,7 +523,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::integer_round_up>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    BOOST_MATH_STD_USING
    typename Dist::value_type pp = c ? 1 - p : p;
@@ -534,7 +541,7 @@ inline typename Dist::value_type
 }
 
 template <class Dist>
-inline typename Dist::value_type 
+BOOST_MATH_GPU_ENABLED inline typename Dist::value_type 
    inverse_discrete_quantile(
       const Dist& dist,
       const typename Dist::value_type& p,
@@ -543,7 +550,7 @@ inline typename Dist::value_type
       const typename Dist::value_type& multiplier,
       const typename Dist::value_type& adder,
       const policies::discrete_quantile<policies::integer_round_nearest>&,
-      std::uintmax_t& max_iter)
+      boost::math::uintmax_t& max_iter)
 {
    typedef typename Dist::value_type value_type;
    BOOST_MATH_STD_USING
diff --git a/include/boost/math/distributions/fisher_f.hpp b/include/boost/math/distributions/fisher_f.hpp
index e22cdf50ae..56b288d88e 100644
--- a/include/boost/math/distributions/fisher_f.hpp
+++ b/include/boost/math/distributions/fisher_f.hpp
@@ -1,5 +1,5 @@
 // Copyright John Maddock 2006.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -8,14 +8,15 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_FISHER_F_HPP
 #define BOOST_MATH_DISTRIBUTIONS_FISHER_F_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for incomplete beta.
 #include <boost/math/distributions/complement.hpp> // complements
 #include <boost/math/distributions/detail/common_error_handling.hpp> // error checks
 #include <boost/math/special_functions/fpclassify.hpp>
 
-#include <utility>
-
 namespace boost{ namespace math{
 
 template <class RealType = double, class Policy = policies::policy<> >
@@ -25,9 +26,9 @@ class fisher_f_distribution
    typedef RealType value_type;
    typedef Policy policy_type;
 
-   fisher_f_distribution(const RealType& i, const RealType& j) : m_df1(i), m_df2(j)
+   BOOST_MATH_GPU_ENABLED fisher_f_distribution(const RealType& i, const RealType& j) : m_df1(i), m_df2(j)
    {
-      static const char* function = "fisher_f_distribution<%1%>::fisher_f_distribution";
+      constexpr auto function = "fisher_f_distribution<%1%>::fisher_f_distribution";
       RealType result;
       detail::check_df(
          function, m_df1, &result, Policy());
@@ -35,11 +36,11 @@ class fisher_f_distribution
          function, m_df2, &result, Policy());
    } // fisher_f_distribution
 
-   RealType degrees_of_freedom1()const
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const
    {
       return m_df1;
    }
-   RealType degrees_of_freedom2()const
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const
    {
       return m_df2;
    }
@@ -60,29 +61,29 @@ fisher_f_distribution(RealType,RealType)->fisher_f_distribution<typename boost::
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const fisher_f_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const fisher_f_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const fisher_f_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const fisher_f_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-RealType pdf(const fisher_f_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED RealType pdf(const fisher_f_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
    RealType error_result = 0;
-   static const char* function = "boost::math::pdf(fisher_f_distribution<%1%> const&, %1%)";
+   constexpr auto function = "boost::math::pdf(fisher_f_distribution<%1%> const&, %1%)";
    if(false == (detail::check_df(
          function, df1, &error_result, Policy())
          && detail::check_df(
@@ -132,9 +133,9 @@ RealType pdf(const fisher_f_distribution<RealType, Policy>& dist, const RealType
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const fisher_f_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const fisher_f_distribution<RealType, Policy>& dist, const RealType& x)
 {
-   static const char* function = "boost::math::cdf(fisher_f_distribution<%1%> const&, %1%)";
+   constexpr auto function = "boost::math::cdf(fisher_f_distribution<%1%> const&, %1%)";
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
@@ -167,9 +168,9 @@ inline RealType cdf(const fisher_f_distribution<RealType, Policy>& dist, const R
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const fisher_f_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const fisher_f_distribution<RealType, Policy>& dist, const RealType& p)
 {
-   static const char* function = "boost::math::quantile(fisher_f_distribution<%1%> const&, %1%)";
+   constexpr auto function = "boost::math::quantile(fisher_f_distribution<%1%> const&, %1%)";
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
@@ -192,9 +193,9 @@ inline RealType quantile(const fisher_f_distribution<RealType, Policy>& dist, co
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<fisher_f_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<fisher_f_distribution<RealType, Policy>, RealType>& c)
 {
-   static const char* function = "boost::math::cdf(fisher_f_distribution<%1%> const&, %1%)";
+   constexpr auto function = "boost::math::cdf(fisher_f_distribution<%1%> const&, %1%)";
    RealType df1 = c.dist.degrees_of_freedom1();
    RealType df2 = c.dist.degrees_of_freedom2();
    RealType x = c.param;
@@ -228,9 +229,9 @@ inline RealType cdf(const complemented2_type<fisher_f_distribution<RealType, Pol
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<fisher_f_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<fisher_f_distribution<RealType, Policy>, RealType>& c)
 {
-   static const char* function = "boost::math::quantile(fisher_f_distribution<%1%> const&, %1%)";
+   constexpr auto function = "boost::math::quantile(fisher_f_distribution<%1%> const&, %1%)";
    RealType df1 = c.dist.degrees_of_freedom1();
    RealType df2 = c.dist.degrees_of_freedom2();
    RealType p = c.param;
@@ -252,9 +253,9 @@ inline RealType quantile(const complemented2_type<fisher_f_distribution<RealType
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const fisher_f_distribution<RealType, Policy>& dist)
 { // Mean of F distribution = v.
-   static const char* function = "boost::math::mean(fisher_f_distribution<%1%> const&)";
+   constexpr auto function = "boost::math::mean(fisher_f_distribution<%1%> const&)";
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
@@ -273,9 +274,9 @@ inline RealType mean(const fisher_f_distribution<RealType, Policy>& dist)
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const fisher_f_distribution<RealType, Policy>& dist)
 { // Variance of F distribution.
-   static const char* function = "boost::math::variance(fisher_f_distribution<%1%> const&)";
+   constexpr auto function = "boost::math::variance(fisher_f_distribution<%1%> const&)";
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
@@ -294,9 +295,9 @@ inline RealType variance(const fisher_f_distribution<RealType, Policy>& dist)
 } // variance
 
 template <class RealType, class Policy>
-inline RealType mode(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const fisher_f_distribution<RealType, Policy>& dist)
 {
-   static const char* function = "boost::math::mode(fisher_f_distribution<%1%> const&)";
+   constexpr auto function = "boost::math::mode(fisher_f_distribution<%1%> const&)";
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
    // Error check:
@@ -317,15 +318,15 @@ inline RealType mode(const fisher_f_distribution<RealType, Policy>& dist)
 //template <class RealType, class Policy>
 //inline RealType median(const fisher_f_distribution<RealType, Policy>& dist)
 //{ // Median of Fisher F distribution is not defined.
-//  return tools::domain_error<RealType>(BOOST_CURRENT_FUNCTION, "Median is not implemented, result is %1%!", std::numeric_limits<RealType>::quiet_NaN());
+//  return tools::domain_error<RealType>(BOOST_CURRENT_FUNCTION, "Median is not implemented, result is %1%!", boost::math::numeric_limits<RealType>::quiet_NaN());
 //  } // median
 
 // Now implemented via quantile(half) in derived accessors.
 
 template <class RealType, class Policy>
-inline RealType skewness(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const fisher_f_distribution<RealType, Policy>& dist)
 {
-   static const char* function = "boost::math::skewness(fisher_f_distribution<%1%> const&)";
+   constexpr auto function = "boost::math::skewness(fisher_f_distribution<%1%> const&)";
    BOOST_MATH_STD_USING // ADL of std names
    // See http://mathworld.wolfram.com/F-Distribution.html
    RealType df1 = dist.degrees_of_freedom1();
@@ -346,18 +347,18 @@ inline RealType skewness(const fisher_f_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-RealType kurtosis_excess(const fisher_f_distribution<RealType, Policy>& dist);
+BOOST_MATH_GPU_ENABLED RealType kurtosis_excess(const fisher_f_distribution<RealType, Policy>& dist);
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const fisher_f_distribution<RealType, Policy>& dist)
 {
    return 3 + kurtosis_excess(dist);
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const fisher_f_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const fisher_f_distribution<RealType, Policy>& dist)
 {
-   static const char* function = "boost::math::kurtosis_excess(fisher_f_distribution<%1%> const&)";
+   constexpr auto function = "boost::math::kurtosis_excess(fisher_f_distribution<%1%> const&)";
    // See http://mathworld.wolfram.com/F-Distribution.html
    RealType df1 = dist.degrees_of_freedom1();
    RealType df2 = dist.degrees_of_freedom2();
diff --git a/include/boost/math/distributions/gamma.hpp b/include/boost/math/distributions/gamma.hpp
index 28b7c55b0b..5176f906d8 100644
--- a/include/boost/math/distributions/gamma.hpp
+++ b/include/boost/math/distributions/gamma.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,22 +11,22 @@
 // http://mathworld.wolfram.com/GammaDistribution.html
 // http://en.wikipedia.org/wiki/Gamma_distribution
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/special_functions/digamma.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 
-#include <utility>
-#include <type_traits>
-
 namespace boost{ namespace math
 {
 namespace detail
 {
 
 template <class RealType, class Policy>
-inline bool check_gamma_shape(
+BOOST_MATH_GPU_ENABLED inline bool check_gamma_shape(
       const char* function,
       RealType shape,
       RealType* result, const Policy& pol)
@@ -41,7 +42,7 @@ inline bool check_gamma_shape(
 }
 
 template <class RealType, class Policy>
-inline bool check_gamma_x(
+BOOST_MATH_GPU_ENABLED inline bool check_gamma_x(
       const char* function,
       RealType const& x,
       RealType* result, const Policy& pol)
@@ -57,7 +58,7 @@ inline bool check_gamma_x(
 }
 
 template <class RealType, class Policy>
-inline bool check_gamma(
+BOOST_MATH_GPU_ENABLED inline bool check_gamma(
       const char* function,
       RealType scale,
       RealType shape,
@@ -75,19 +76,19 @@ class gamma_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit gamma_distribution(RealType l_shape, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED explicit gamma_distribution(RealType l_shape, RealType l_scale = 1)
       : m_shape(l_shape), m_scale(l_scale)
    {
       RealType result;
       detail::check_gamma("boost::math::gamma_distribution<%1%>::gamma_distribution", l_scale, l_shape, &result, Policy());
    }
 
-   RealType shape()const
+   BOOST_MATH_GPU_ENABLED RealType shape()const
    {
       return m_shape;
    }
 
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_scale;
    }
@@ -109,27 +110,27 @@ gamma_distribution(RealType,RealType)->gamma_distribution<typename boost::math::
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const gamma_distribution<RealType, Policy>& /* dist */)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const gamma_distribution<RealType, Policy>& /* dist */)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const gamma_distribution<RealType, Policy>& /* dist */)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const gamma_distribution<RealType, Policy>& /* dist */)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
    using boost::math::tools::min_value;
-   return std::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(min_value<RealType>(),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -149,17 +150,17 @@ inline RealType pdf(const gamma_distribution<RealType, Policy>& dist, const Real
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    using boost::math::lgamma;
 
-   static const char* function = "boost::math::logpdf(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logpdf(const gamma_distribution<%1%>&, %1%)";
 
    RealType k = dist.shape();
    RealType theta = dist.scale();
 
-   RealType result = -std::numeric_limits<RealType>::infinity();
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
    if(false == detail::check_gamma(function, theta, k, &result, Policy()))
       return result;
    if(false == detail::check_gamma_x(function, x, &result, Policy()))
@@ -167,7 +168,7 @@ inline RealType logpdf(const gamma_distribution<RealType, Policy>& dist, const R
 
    if(x == 0)
    {
-      return std::numeric_limits<RealType>::quiet_NaN();
+      return boost::math::numeric_limits<RealType>::quiet_NaN();
    }
 
    result = -k*log(theta) + (k-1)*log(x) - lgamma(k) - (x/theta);
@@ -176,11 +177,11 @@ inline RealType logpdf(const gamma_distribution<RealType, Policy>& dist, const R
 } // logpdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -196,11 +197,11 @@ inline RealType cdf(const gamma_distribution<RealType, Policy>& dist, const Real
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const gamma_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const gamma_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -220,11 +221,11 @@ inline RealType quantile(const gamma_distribution<RealType, Policy>& dist, const
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<gamma_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<gamma_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -241,11 +242,11 @@ inline RealType cdf(const complemented2_type<gamma_distribution<RealType, Policy
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<gamma_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<gamma_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -266,11 +267,11 @@ inline RealType quantile(const complemented2_type<gamma_distribution<RealType, P
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::mean(const gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mean(const gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -284,11 +285,11 @@ inline RealType mean(const gamma_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::variance(const gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::variance(const gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -302,11 +303,11 @@ inline RealType variance(const gamma_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::mode(const gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mode(const gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -331,11 +332,11 @@ inline RealType mode(const gamma_distribution<RealType, Policy>& dist)
 //}
 
 template <class RealType, class Policy>
-inline RealType skewness(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::skewness(const gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::skewness(const gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -349,11 +350,11 @@ inline RealType skewness(const gamma_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::kurtosis_excess(const gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::kurtosis_excess(const gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -367,18 +368,19 @@ inline RealType kurtosis_excess(const gamma_distribution<RealType, Policy>& dist
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const gamma_distribution<RealType, Policy>& dist)
 {
    return kurtosis_excess(dist) + 3;
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const gamma_distribution<RealType, Policy>& dist)
 {
+   BOOST_MATH_STD_USING
+
    RealType k = dist.shape();
    RealType theta = dist.scale();
-   using std::log;
-   return k + log(theta) + lgamma(k) + (1-k)*digamma(k);
+   return k + log(theta) + boost::math::lgamma(k) + (1-k)*digamma(k);
 }
 
 } // namespace math
diff --git a/include/boost/math/distributions/geometric.hpp b/include/boost/math/distributions/geometric.hpp
index 7c511ef2db..0a7b383c24 100644
--- a/include/boost/math/distributions/geometric.hpp
+++ b/include/boost/math/distributions/geometric.hpp
@@ -36,6 +36,9 @@
 #ifndef BOOST_MATH_SPECIAL_GEOMETRIC_HPP
 #define BOOST_MATH_SPECIAL_GEOMETRIC_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for ibeta(a, b, x) == Ix(a, b).
 #include <boost/math/distributions/complement.hpp> // complement.
@@ -45,10 +48,6 @@
 #include <boost/math/distributions/detail/inv_discrete_quantile.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 
-#include <limits> // using std::numeric_limits;
-#include <utility>
-#include <cmath>
-
 #if defined (BOOST_MSVC)
 #  pragma warning(push)
 // This believed not now necessary, so commented out.
@@ -64,7 +63,7 @@ namespace boost
     {
       // Common error checking routines for geometric distribution function:
       template <class RealType, class Policy>
-      inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         if( !(boost::math::isfinite)(p) || (p < 0) || (p > 1) )
         {
@@ -77,13 +76,13 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         return check_success_fraction(function, p, result, pol);
       }
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_k(const char* function,  const RealType& p, RealType k, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function,  const RealType& p, RealType k, RealType* result, const Policy& pol)
       {
         if(check_dist(function, p, result, pol) == false)
         {
@@ -100,7 +99,7 @@ namespace boost
       } // Check_dist_and_k
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, RealType p, RealType prob, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, RealType p, RealType prob, RealType* result, const Policy& pol)
       {
         if((check_dist(function, p, result, pol) && detail::check_probability(function, prob, result, pol)) == false)
         {
@@ -117,7 +116,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      geometric_distribution(RealType p) : m_p(p)
+      BOOST_MATH_GPU_ENABLED geometric_distribution(RealType p) : m_p(p)
       { // Constructor stores success_fraction p.
         RealType result;
         geometric_detail::check_dist(
@@ -127,22 +126,22 @@ namespace boost
       } // geometric_distribution constructor.
 
       // Private data getter class member functions.
-      RealType success_fraction() const
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const
       { // Probability of success as fraction in range 0 to 1.
         return m_p;
       }
-      RealType successes() const
+      BOOST_MATH_GPU_ENABLED RealType successes() const
       { // Total number of successes r = 1 (for compatibility with negative binomial?).
         return 1;
       }
 
       // Parameter estimation.
       // (These are copies of negative_binomial distribution with successes = 1).
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
         RealType trials,
         RealType alpha) // alpha 0.05 equivalent to 95% for one-sided test.
       {
-        static const char* function = "boost::math::geometric<%1%>::find_lower_bound_on_p";
+        constexpr auto function = "boost::math::geometric<%1%>::find_lower_bound_on_p";
         RealType result = 0;  // of error checks.
         RealType successes = 1;
         RealType failures = trials - successes;
@@ -163,11 +162,11 @@ namespace boost
         return ibeta_inv(successes, failures + 1, alpha, static_cast<RealType*>(nullptr), Policy());
       } // find_lower_bound_on_p
 
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
         RealType trials,
         RealType alpha) // alpha 0.05 equivalent to 95% for one-sided test.
       {
-        static const char* function = "boost::math::geometric<%1%>::find_upper_bound_on_p";
+        constexpr auto function = "boost::math::geometric<%1%>::find_upper_bound_on_p";
         RealType result = 0;  // of error checks.
         RealType successes = 1;
         RealType failures = trials - successes;
@@ -195,12 +194,12 @@ namespace boost
       // Estimate number of trials :
       // "How many trials do I need to be P% sure of seeing k or fewer failures?"
 
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
         RealType k,     // number of failures (k >= 0).
         RealType p,     // success fraction 0 <= p <= 1.
         RealType alpha) // risk level threshold 0 <= alpha <= 1.
       {
-        static const char* function = "boost::math::geometric<%1%>::find_minimum_number_of_trials";
+        constexpr auto function = "boost::math::geometric<%1%>::find_minimum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == geometric_detail::check_dist_and_k(
@@ -213,12 +212,12 @@ namespace boost
         return result + k;
       } // RealType find_number_of_failures
 
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
         RealType k,     // number of failures (k >= 0).
         RealType p,     // success fraction 0 <= p <= 1.
         RealType alpha) // risk level threshold 0 <= alpha <= 1.
       {
-        static const char* function = "boost::math::geometric<%1%>::find_maximum_number_of_trials";
+        constexpr auto function = "boost::math::geometric<%1%>::find_maximum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == geometric_detail::check_dist_and_k(
@@ -244,22 +243,22 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const geometric_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const geometric_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable k.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // max_integer?
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // max_integer?
     }
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const geometric_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const geometric_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable k.
        // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>()); // max_integer?
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>()); // max_integer?
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const geometric_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const geometric_distribution<RealType, Policy>& dist)
     { // Mean of geometric distribution = (1-p)/p.
       return (1 - dist.success_fraction() ) / dist.success_fraction();
     } // mean
@@ -267,21 +266,21 @@ namespace boost
     // median implemented via quantile(half) in derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType mode(const geometric_distribution<RealType, Policy>&)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const geometric_distribution<RealType, Policy>&)
     { // Mode of geometric distribution = zero.
       BOOST_MATH_STD_USING // ADL of std functions.
       return 0;
     } // mode
 
     template <class RealType, class Policy>
-    inline RealType variance(const geometric_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const geometric_distribution<RealType, Policy>& dist)
     { // Variance of Binomial distribution = (1-p) / p^2.
       return  (1 - dist.success_fraction())
         / (dist.success_fraction() * dist.success_fraction());
     } // variance
 
     template <class RealType, class Policy>
-    inline RealType skewness(const geometric_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const geometric_distribution<RealType, Policy>& dist)
     { // skewness of geometric distribution = 2-p / (sqrt(r(1-p))
       BOOST_MATH_STD_USING // ADL of std functions.
       RealType p = dist.success_fraction();
@@ -289,7 +288,7 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const geometric_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const geometric_distribution<RealType, Policy>& dist)
     { // kurtosis of geometric distribution
       // http://en.wikipedia.org/wiki/geometric is kurtosis_excess so add 3
       RealType p = dist.success_fraction();
@@ -297,7 +296,7 @@ namespace boost
     } // kurtosis
 
      template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const geometric_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const geometric_distribution<RealType, Policy>& dist)
     { // kurtosis excess of geometric distribution
       // http://mathworld.wolfram.com/Kurtosis.html table of kurtosis_excess
       RealType p = dist.success_fraction();
@@ -312,11 +311,11 @@ namespace boost
     // chf of geometric distribution provided by derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType pdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
     { // Probability Density/Mass Function.
       BOOST_FPU_EXCEPTION_GUARD
       BOOST_MATH_STD_USING  // For ADL of math functions.
-      static const char* function = "boost::math::pdf(const geometric_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const geometric_distribution<%1%>&, %1%)";
 
       RealType p = dist.success_fraction();
       RealType result = 0;
@@ -350,9 +349,9 @@ namespace boost
     } // geometric_pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
     { // Cumulative Distribution Function of geometric.
-      static const char* function = "boost::math::cdf(const geometric_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::cdf(const geometric_distribution<%1%>&, %1%)";
 
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
@@ -381,12 +380,10 @@ namespace boost
     } // cdf Cumulative Distribution Function geometric.
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const geometric_distribution<RealType, Policy>& dist, const RealType& k)
     { // Cumulative Distribution Function of geometric.
-      using std::pow;
-      using std::log;
-      using std::exp;
-      static const char* function = "boost::math::logcdf(const geometric_distribution<%1%>&, %1%)";
+      BOOST_MATH_STD_USING
+      constexpr auto function = "boost::math::logcdf(const geometric_distribution<%1%>&, %1%)";
 
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
@@ -399,7 +396,7 @@ namespace boost
         k,
         &result, Policy()))
       {
-        return -std::numeric_limits<RealType>::infinity();
+        return -boost::math::numeric_limits<RealType>::infinity();
       }
       if(k == 0)
       {
@@ -413,10 +410,10 @@ namespace boost
     } // logcdf Cumulative Distribution Function geometric.
 
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function geometric.
       BOOST_MATH_STD_USING
-      static const char* function = "boost::math::cdf(const geometric_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::cdf(const geometric_distribution<%1%>&, %1%)";
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
       RealType const& k = c.param;
@@ -438,10 +435,10 @@ namespace boost
     } // cdf Complemented Cumulative Distribution Function geometric.
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function geometric.
       BOOST_MATH_STD_USING
-      static const char* function = "boost::math::logcdf(const geometric_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::logcdf(const geometric_distribution<%1%>&, %1%)";
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
       RealType const& k = c.param;
@@ -455,21 +452,21 @@ namespace boost
         k,
         &result, Policy()))
       {
-        return -std::numeric_limits<RealType>::infinity();
+        return -boost::math::numeric_limits<RealType>::infinity();
       }
 
       return boost::math::log1p(-p, Policy()) * (k+1);
     } // logcdf Complemented Cumulative Distribution Function geometric.
 
     template <class RealType, class Policy>
-    inline RealType quantile(const geometric_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const geometric_distribution<RealType, Policy>& dist, const RealType& x)
     { // Quantile, percentile/100 or Percent Point geometric function.
       // Return the number of expected failures k for a given probability p.
 
       // Inverse cumulative Distribution Function or Quantile (percentile / 100) of geometric Probability.
       // k argument may be integral, signed, or unsigned, or floating point.
 
-      static const char* function = "boost::math::quantile(const geometric_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::quantile(const geometric_distribution<%1%>&, %1%)";
       BOOST_MATH_STD_USING // ADL of std functions.
 
       RealType success_fraction = dist.success_fraction();
@@ -513,11 +510,11 @@ namespace boost
     } // RealType quantile(const geometric_distribution dist, p)
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<geometric_distribution<RealType, Policy>, RealType>& c)
     {  // Quantile or Percent Point Binomial function.
        // Return the number of expected failures k for a given
        // complement of the probability Q = 1 - P.
-       static const char* function = "boost::math::quantile(const geometric_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::quantile(const geometric_distribution<%1%>&, %1%)";
        BOOST_MATH_STD_USING
        // Error checks:
        RealType x = c.param;
diff --git a/include/boost/math/distributions/inverse_chi_squared.hpp b/include/boost/math/distributions/inverse_chi_squared.hpp
index 19dd0371e8..1a3c680d23 100644
--- a/include/boost/math/distributions/inverse_chi_squared.hpp
+++ b/include/boost/math/distributions/inverse_chi_squared.hpp
@@ -1,6 +1,6 @@
 // Copyright John Maddock 2010.
 // Copyright Paul A. Bristow 2010.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -9,6 +9,8 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_INVERSE_CHI_SQUARED_HPP
 #define BOOST_MATH_DISTRIBUTIONS_INVERSE_CHI_SQUARED_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp> // for incomplete beta.
 #include <boost/math/distributions/complement.hpp> // for complements.
@@ -24,14 +26,12 @@
 // Weisstein, Eric W. "Inverse Chi-Squared Distribution." From MathWorld--A Wolfram Web Resource.
 // http://mathworld.wolfram.com/InverseChi-SquaredDistribution.html
 
-#include <utility>
-
 namespace boost{ namespace math{
 
 namespace detail
 {
   template <class RealType, class Policy>
-  inline bool check_inverse_chi_squared( // Check both distribution parameters.
+  BOOST_MATH_GPU_ENABLED inline bool check_inverse_chi_squared( // Check both distribution parameters.
         const char* function,
         RealType degrees_of_freedom, // degrees_of_freedom (aka nu).
         RealType scale,  // scale (aka sigma^2)
@@ -51,7 +51,7 @@ class inverse_chi_squared_distribution
    typedef RealType value_type;
    typedef Policy policy_type;
 
-   inverse_chi_squared_distribution(RealType df, RealType l_scale) : m_df(df), m_scale (l_scale)
+   BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df, RealType l_scale) : m_df(df), m_scale (l_scale)
    {
       RealType result;
       detail::check_df(
@@ -62,7 +62,7 @@ class inverse_chi_squared_distribution
          m_scale, &result,  Policy());
    } // inverse_chi_squared_distribution constructor 
 
-   inverse_chi_squared_distribution(RealType df = 1) : m_df(df)
+   BOOST_MATH_GPU_ENABLED inverse_chi_squared_distribution(RealType df = 1) : m_df(df)
    {
       RealType result;
       m_scale = 1 / m_df ; // Default scale = 1 / degrees of freedom (Wikipedia definition 1).
@@ -71,11 +71,11 @@ class inverse_chi_squared_distribution
          m_df, &result, Policy());
    } // inverse_chi_squared_distribution
 
-   RealType degrees_of_freedom()const
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const
    {
       return m_df; // aka nu
    }
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_scale;  // aka xi
    }
@@ -105,28 +105,28 @@ inverse_chi_squared_distribution(RealType,RealType)->inverse_chi_squared_distrib
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const inverse_chi_squared_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const inverse_chi_squared_distribution<RealType, Policy>& /*dist*/)
 {  // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + infinity.
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // 0 to + infinity.
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const inverse_chi_squared_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const inverse_chi_squared_distribution<RealType, Policy>& /*dist*/)
 {  // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), tools::max_value<RealType>()); // 0 to + infinity.
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), tools::max_value<RealType>()); // 0 to + infinity.
 }
 
 template <class RealType, class Policy>
-RealType pdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED RealType pdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions.
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
    RealType error_result;
 
-   static const char* function = "boost::math::pdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
 
    if(false == detail::check_inverse_chi_squared
      (function, df, scale, &error_result, Policy())
@@ -159,9 +159,9 @@ RealType pdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, con
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
 {
-   static const char* function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
    RealType error_result;
@@ -188,13 +188,13 @@ inline RealType cdf(const inverse_chi_squared_distribution<RealType, Policy>& di
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const inverse_chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
 {
    using boost::math::gamma_q_inv;
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
 
-   static const char* function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false == detail::check_df(
@@ -220,13 +220,13 @@ inline RealType quantile(const inverse_chi_squared_distribution<RealType, Policy
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
 {
    using boost::math::gamma_q_inv;
    RealType const& df = c.dist.degrees_of_freedom();
    RealType const& scale = c.dist.scale();
    RealType const& x = c.param;
-   static const char* function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const inverse_chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false == detail::check_df(
@@ -251,14 +251,14 @@ inline RealType cdf(const complemented2_type<inverse_chi_squared_distribution<Re
 } // cdf(complemented
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<inverse_chi_squared_distribution<RealType, Policy>, RealType>& c)
 {
    using boost::math::gamma_q_inv;
 
    RealType const& df = c.dist.degrees_of_freedom();
    RealType const& scale = c.dist.scale();
    RealType const& q = c.param;
-   static const char* function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const inverse_chi_squared_distribution<%1%>&, %1%)";
    // Error check:
    RealType error_result;
    if(false == detail::check_df(function, df, &error_result, Policy()))
@@ -280,12 +280,12 @@ inline RealType quantile(const complemented2_type<inverse_chi_squared_distributi
 } // quantile(const complement
 
 template <class RealType, class Policy>
-inline RealType mean(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 { // Mean of inverse Chi-Squared distribution.
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
 
-   static const char* function = "boost::math::mean(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mean(const inverse_chi_squared_distribution<%1%>&)";
    if(df <= 2)
       return policies::raise_domain_error<RealType>(
          function,
@@ -295,11 +295,11 @@ inline RealType mean(const inverse_chi_squared_distribution<RealType, Policy>& d
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 { // Variance of inverse Chi-Squared distribution.
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
-   static const char* function = "boost::math::variance(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::variance(const inverse_chi_squared_distribution<%1%>&)";
    if(df <= 4)
    {
       return policies::raise_domain_error<RealType>(
@@ -311,14 +311,14 @@ inline RealType variance(const inverse_chi_squared_distribution<RealType, Policy
 } // variance
 
 template <class RealType, class Policy>
-inline RealType mode(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 { // mode is not defined in Mathematica.
   // See Discussion section http://en.wikipedia.org/wiki/Talk:Scaled-inverse-chi-square_distribution
   // for origin of the formula used below.
 
    RealType df = dist.degrees_of_freedom();
    RealType scale = dist.scale();
-   static const char* function = "boost::math::mode(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mode(const inverse_chi_squared_distribution<%1%>&)";
    if(df < 0)
       return policies::raise_domain_error<RealType>(
          function,
@@ -341,11 +341,11 @@ inline RealType mode(const inverse_chi_squared_distribution<RealType, Policy>& d
 // Now implemented via quantile(half) in derived accessors.
 
 template <class RealType, class Policy>
-inline RealType skewness(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING // For ADL
    RealType df = dist.degrees_of_freedom();
-   static const char* function = "boost::math::skewness(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::skewness(const inverse_chi_squared_distribution<%1%>&)";
    if(df <= 6)
       return policies::raise_domain_error<RealType>(
          function,
@@ -356,10 +356,10 @@ inline RealType skewness(const inverse_chi_squared_distribution<RealType, Policy
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
-   static const char* function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
    if(df <= 8)
       return policies::raise_domain_error<RealType>(
          function,
@@ -370,10 +370,10 @@ inline RealType kurtosis(const inverse_chi_squared_distribution<RealType, Policy
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const inverse_chi_squared_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const inverse_chi_squared_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
-   static const char* function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
+   constexpr auto function = "boost::math::kurtosis(const inverse_chi_squared_distribution<%1%>&)";
    if(df <= 8)
       return policies::raise_domain_error<RealType>(
          function,
diff --git a/include/boost/math/distributions/inverse_gamma.hpp b/include/boost/math/distributions/inverse_gamma.hpp
index 8c9e4763d5..6aa798ed82 100644
--- a/include/boost/math/distributions/inverse_gamma.hpp
+++ b/include/boost/math/distributions/inverse_gamma.hpp
@@ -2,6 +2,7 @@
 
 //  Copyright Paul A. Bristow 2010.
 //  Copyright John Maddock 2010.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -22,21 +23,21 @@
 // http://mathworld.wolfram.com/GammaDistribution.html
 // http://en.wikipedia.org/wiki/Gamma_distribution
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 
-#include <utility>
-#include <cfenv>
-
 namespace boost{ namespace math
 {
 namespace detail
 {
 
 template <class RealType, class Policy>
-inline bool check_inverse_gamma_shape(
+BOOST_MATH_GPU_ENABLED inline bool check_inverse_gamma_shape(
       const char* function, // inverse_gamma
       RealType shape, // shape aka alpha
       RealType* result, // to update, perhaps with NaN
@@ -57,7 +58,7 @@ inline bool check_inverse_gamma_shape(
 } //bool check_inverse_gamma_shape
 
 template <class RealType, class Policy>
-inline bool check_inverse_gamma_x(
+BOOST_MATH_GPU_ENABLED inline bool check_inverse_gamma_x(
       const char* function,
       RealType const& x,
       RealType* result, const Policy& pol)
@@ -73,7 +74,7 @@ inline bool check_inverse_gamma_x(
 }
 
 template <class RealType, class Policy>
-inline bool check_inverse_gamma(
+BOOST_MATH_GPU_ENABLED inline bool check_inverse_gamma(
       const char* function, // TODO swap these over, so shape is first.
       RealType scale,  // scale aka beta
       RealType shape, // shape aka alpha
@@ -92,7 +93,7 @@ class inverse_gamma_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit inverse_gamma_distribution(RealType l_shape = 1, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED explicit inverse_gamma_distribution(RealType l_shape = 1, RealType l_scale = 1)
       : m_shape(l_shape), m_scale(l_scale)
    {
       RealType result;
@@ -101,12 +102,12 @@ class inverse_gamma_distribution
         l_scale, l_shape, &result, Policy());
    }
 
-   RealType shape()const
+   BOOST_MATH_GPU_ENABLED RealType shape()const
    {
       return m_shape;
    }
 
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_scale;
    }
@@ -132,27 +133,27 @@ inverse_gamma_distribution(RealType,RealType)->inverse_gamma_distribution<typena
 // Allow random variable x to be zero, treated as a special case (unlike some definitions).
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const inverse_gamma_distribution<RealType, Policy>& /* dist */)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const inverse_gamma_distribution<RealType, Policy>& /* dist */)
 {  // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const inverse_gamma_distribution<RealType, Policy>& /* dist */)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const inverse_gamma_distribution<RealType, Policy>& /* dist */)
 {  // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
    using boost::math::tools::min_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::pdf(const inverse_gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const inverse_gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -195,17 +196,17 @@ inline RealType pdf(const inverse_gamma_distribution<RealType, Policy>& dist, co
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    using boost::math::lgamma;
 
-   static const char* function = "boost::math::logpdf(const inverse_gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logpdf(const inverse_gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
 
-   RealType result = -std::numeric_limits<RealType>::infinity();
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
    if(false == detail::check_inverse_gamma(function, scale, shape, &result, Policy()))
    { // distribution parameters bad.
       return result;
@@ -232,11 +233,11 @@ inline RealType logpdf(const inverse_gamma_distribution<RealType, Policy>& dist,
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const inverse_gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const inverse_gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -260,12 +261,12 @@ inline RealType cdf(const inverse_gamma_distribution<RealType, Policy>& dist, co
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const inverse_gamma_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    using boost::math::gamma_q_inv;
 
-   static const char* function = "boost::math::quantile(const inverse_gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const inverse_gamma_distribution<%1%>&, %1%)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -287,11 +288,11 @@ inline RealType quantile(const inverse_gamma_distribution<RealType, Policy>& dis
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<inverse_gamma_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<inverse_gamma_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const gamma_distribution<%1%>&, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -310,11 +311,11 @@ inline RealType cdf(const complemented2_type<inverse_gamma_distribution<RealType
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<inverse_gamma_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<inverse_gamma_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const inverse_gamma_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const inverse_gamma_distribution<%1%>&, %1%)";
 
    RealType shape = c.dist.shape();
    RealType scale = c.dist.scale();
@@ -338,11 +339,11 @@ inline RealType quantile(const complemented2_type<inverse_gamma_distribution<Rea
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::mean(const inverse_gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mean(const inverse_gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -365,11 +366,11 @@ inline RealType mean(const inverse_gamma_distribution<RealType, Policy>& dist)
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::variance(const inverse_gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::variance(const inverse_gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -391,11 +392,11 @@ inline RealType variance(const inverse_gamma_distribution<RealType, Policy>& dis
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::mode(const inverse_gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::mode(const inverse_gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -418,11 +419,11 @@ inline RealType mode(const inverse_gamma_distribution<RealType, Policy>& dist)
 //}
 
 template <class RealType, class Policy>
-inline RealType skewness(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::skewness(const inverse_gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::skewness(const inverse_gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -444,11 +445,11 @@ inline RealType skewness(const inverse_gamma_distribution<RealType, Policy>& dis
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::kurtosis_excess(const inverse_gamma_distribution<%1%>&)";
+   constexpr auto function = "boost::math::kurtosis_excess(const inverse_gamma_distribution<%1%>&)";
 
    RealType shape = dist.shape();
    RealType scale = dist.scale();
@@ -470,9 +471,9 @@ inline RealType kurtosis_excess(const inverse_gamma_distribution<RealType, Polic
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const inverse_gamma_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const inverse_gamma_distribution<RealType, Policy>& dist)
 {
-  static const char* function = "boost::math::kurtosis(const inverse_gamma_distribution<%1%>&)";
+  constexpr auto function = "boost::math::kurtosis(const inverse_gamma_distribution<%1%>&)";
    RealType shape = dist.shape();
    RealType scale = dist.scale();
 
diff --git a/include/boost/math/tools/tuple.hpp b/include/boost/math/tools/tuple.hpp
index 82d23b8d77..dcc763e37a 100644
--- a/include/boost/math/tools/tuple.hpp
+++ b/include/boost/math/tools/tuple.hpp
@@ -23,6 +23,7 @@ using cuda::std::tuple;
 
 using cuda::std::make_pair;
 
+using cuda::std::tie;
 using cuda::std::get;
 
 using cuda::std::tuple_size;
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index c9a70e8a99..bae42a8d99 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -64,11 +64,46 @@ run test_extreme_value_pdf_float.cu ;
 run test_extreme_value_quan_double.cu ;
 run test_extreme_value_quan_float.cu ;
 
+run test_fisher_f_cdf_double.cu ;
+run test_fisher_f_cdf_float.cu ;
+run test_fisher_f_pdf_double.cu ;
+run test_fisher_f_pdf_float.cu ;
+run test_fisher_f_quan_double.cu ;
+run test_fisher_f_quan_float.cu ;
+
+run test_gamma_dist_cdf_double.cu ;
+run test_gamma_dist_cdf_float.cu ;
+run test_gamma_dist_pdf_double.cu ;
+run test_gamma_dist_pdf_float.cu ;
+run test_gamma_dist_quan_double.cu ;
+run test_gamma_dist_quan_float.cu ;
+
+run test_geometric_dist_cdf_double.cu ;
+run test_geometric_dist_cdf_float.cu ;
+run test_geometric_dist_pdf_double.cu ;
+run test_geometric_dist_pdf_float.cu ;
+run test_geometric_dist_quan_double.cu ;
+run test_geometric_dist_quan_float.cu ;
+
 run test_holtsmark_cdf_double.cu ;
 run test_holtsmark_cdf_float.cu ;
 run test_holtsmark_pdf_double.cu ;
 run test_holtsmark_pdf_float.cu ;
 
+run test_inverse_chi_squared_cdf_double.cu ;
+run test_inverse_chi_squared_cdf_float.cu ;
+run test_inverse_chi_squared_pdf_double.cu ;
+run test_inverse_chi_squared_pdf_float.cu ;
+run test_inverse_chi_squared_quan_double.cu ;
+run test_inverse_chi_squared_quan_float.cu ;
+
+run test_inverse_gamma_cdf_double.cu ;
+run test_inverse_gamma_cdf_float.cu ;
+run test_inverse_gamma_pdf_double.cu ;
+run test_inverse_gamma_pdf_float.cu ;
+run test_inverse_gamma_quan_double.cu ;
+run test_inverse_gamma_quan_float.cu ;
+
 run test_landau_cdf_double.cu ;
 run test_landau_cdf_float.cu ;
 run test_landau_pdf_double.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 1fc2746a1f..1b001eb2f1 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -59,6 +59,27 @@ run test_extreme_value_pdf_nvrtc_float.cpp ;
 run test_extreme_value_quan_nvrtc_double.cpp ;
 run test_extreme_value_quan_nvrtc_float.cpp ;
 
+run test_fisher_f_cdf_nvrtc_double.cpp ;
+run test_fisher_f_cdf_nvrtc_float.cpp ;
+run test_fisher_f_pdf_nvrtc_double.cpp ;
+run test_fisher_f_pdf_nvrtc_float.cpp ;
+run test_fisher_f_quan_nvrtc_double.cpp ;
+run test_fisher_f_quan_nvrtc_float.cpp ;
+
+run test_gamma_dist_cdf_nvrtc_double.cpp ;
+run test_gamma_dist_cdf_nvrtc_float.cpp ;
+run test_gamma_dist_pdf_nvrtc_double.cpp ;
+run test_gamma_dist_pdf_nvrtc_float.cpp ;
+run test_gamma_dist_quan_nvrtc_double.cpp ;
+run test_gamma_dist_quan_nvrtc_float.cpp ;
+
+run test_geometric_dist_cdf_nvrtc_double.cpp ;
+run test_geometric_dist_cdf_nvrtc_float.cpp ;
+run test_geometric_dist_pdf_nvrtc_double.cpp ;
+run test_geometric_dist_pdf_nvrtc_float.cpp ;
+run test_geometric_dist_quan_nvrtc_double.cpp ;
+run test_geometric_dist_quan_nvrtc_float.cpp ;
+
 run test_holtsmark_cdf_nvrtc_double.cpp ;
 run test_holtsmark_cdf_nvrtc_float.cpp ;
 run test_holtsmark_pdf_nvrtc_double.cpp ;
@@ -66,6 +87,20 @@ run test_holtsmark_pdf_nvrtc_float.cpp ;
 run test_holtsmark_quan_nvrtc_double.cpp ;
 run test_holtsmark_quan_nvrtc_float.cpp ;
 
+run test_inverse_chi_squared_cdf_nvrtc_double.cpp ; 
+run test_inverse_chi_squared_cdf_nvrtc_float.cpp ;
+run test_inverse_chi_squared_pdf_nvrtc_double.cpp ; 
+run test_inverse_chi_squared_pdf_nvrtc_float.cpp ;
+run test_inverse_chi_squared_quan_nvrtc_double.cpp ; 
+run test_inverse_chi_squared_quan_nvrtc_float.cpp ;
+
+run test_inverse_gamma_cdf_nvrtc_double.cpp ;
+run test_inverse_gamma_cdf_nvrtc_float.cpp ;
+run test_inverse_gamma_pdf_nvrtc_double.cpp ;
+run test_inverse_gamma_pdf_nvrtc_float.cpp ;
+run test_inverse_gamma_quan_nvrtc_double.cpp ;
+run test_inverse_gamma_quan_nvrtc_float.cpp ;
+
 run test_landau_cdf_nvrtc_double.cpp ;
 run test_landau_cdf_nvrtc_float.cpp ;
 run test_landau_pdf_nvrtc_double.cpp ;
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 5d3d85cd8f..bcdfb7e5d2 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -17,7 +17,12 @@ run test_cauchy.cpp ;
 run test_chi_squared.cpp ;
 run test_exponential_dist.cpp ;
 run test_extreme_value.cpp ;
+run test_fisher_f.cpp ;
+run test_gamma_dist.cpp ;
+run test_geometric.cpp ;
 run test_holtsmark.cpp ;
+run test_inverse_chi_squared_distribution.cpp ;
+run test_inverse_gamma_distribution.cpp ;
 run test_landau.cpp ;
 run test_laplace.cpp ;
 run test_logistic_dist.cpp ;
diff --git a/test/test_arcsine_cdf_double.cu b/test/test_arcsine_cdf_double.cu
index d6f6f7b357..3ac9e22cd0 100644
--- a/test/test_arcsine_cdf_double.cu
+++ b/test/test_arcsine_cdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_cdf_float.cu b/test/test_arcsine_cdf_float.cu
index 148b1dffb0..cc73ce95bd 100644
--- a/test/test_arcsine_cdf_float.cu
+++ b/test/test_arcsine_cdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_pdf_double.cu b/test/test_arcsine_pdf_double.cu
index 7a73bb34eb..8f45017ba8 100644
--- a/test/test_arcsine_pdf_double.cu
+++ b/test/test_arcsine_pdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_pdf_float.cu b/test/test_arcsine_pdf_float.cu
index 54a11253c5..c236b7876f 100644
--- a/test/test_arcsine_pdf_float.cu
+++ b/test/test_arcsine_pdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_quan_double.cu b/test/test_arcsine_quan_double.cu
index 31f6eac8a1..a457370635 100644
--- a/test/test_arcsine_quan_double.cu
+++ b/test/test_arcsine_quan_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_quan_float.cu b/test/test_arcsine_quan_float.cu
index 6decb347b0..fd8cd11fcc 100644
--- a/test/test_arcsine_quan_float.cu
+++ b/test/test_arcsine_quan_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_range_support_double.cu b/test/test_arcsine_range_support_double.cu
index cec919a1ae..b3fb575faa 100644
--- a/test/test_arcsine_range_support_double.cu
+++ b/test/test_arcsine_range_support_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_arcsine_range_support_float.cu b/test/test_arcsine_range_support_float.cu
index d397e0c86d..d207d0598e 100644
--- a/test/test_arcsine_range_support_float.cu
+++ b/test/test_arcsine_range_support_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_cdf_double.cu b/test/test_bernoulli_cdf_double.cu
index e4c21ca062..1a6dce645e 100644
--- a/test/test_bernoulli_cdf_double.cu
+++ b/test/test_bernoulli_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_cdf_float.cu b/test/test_bernoulli_cdf_float.cu
index 82c0eabc0f..998f247361 100644
--- a/test/test_bernoulli_cdf_float.cu
+++ b/test/test_bernoulli_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_pdf_double.cu b/test/test_bernoulli_pdf_double.cu
index 24b33c16c0..147e2f3401 100644
--- a/test/test_bernoulli_pdf_double.cu
+++ b/test/test_bernoulli_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_pdf_float.cu b/test/test_bernoulli_pdf_float.cu
index 08d2ca5a01..49eaea32f9 100644
--- a/test/test_bernoulli_pdf_float.cu
+++ b/test/test_bernoulli_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_range_support_double.cu b/test/test_bernoulli_range_support_double.cu
index 86c77bd114..ade952fca3 100644
--- a/test/test_bernoulli_range_support_double.cu
+++ b/test/test_bernoulli_range_support_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_bernoulli_range_support_float.cu b/test/test_bernoulli_range_support_float.cu
index cdcf544189..ef276b9384 100644
--- a/test/test_bernoulli_range_support_float.cu
+++ b/test/test_bernoulli_range_support_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_cdf_double.cu b/test/test_beta_dist_cdf_double.cu
index fa460244a3..9188f4305f 100644
--- a/test/test_beta_dist_cdf_double.cu
+++ b/test/test_beta_dist_cdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_cdf_float.cu b/test/test_beta_dist_cdf_float.cu
index 321c844205..0278f64155 100644
--- a/test/test_beta_dist_cdf_float.cu
+++ b/test/test_beta_dist_cdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_pdf_double.cu b/test/test_beta_dist_pdf_double.cu
index c0ee9272ae..e86cf94dd8 100644
--- a/test/test_beta_dist_pdf_double.cu
+++ b/test/test_beta_dist_pdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_pdf_float.cu b/test/test_beta_dist_pdf_float.cu
index 75e4fa27b4..97dd606f2f 100644
--- a/test/test_beta_dist_pdf_float.cu
+++ b/test/test_beta_dist_pdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_quan_double.cu b/test/test_beta_dist_quan_double.cu
index 101526afae..a6b842e8ef 100644
--- a/test/test_beta_dist_quan_double.cu
+++ b/test/test_beta_dist_quan_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_beta_dist_quan_float.cu b/test/test_beta_dist_quan_float.cu
index 77696c6393..48a860f4c2 100644
--- a/test/test_beta_dist_quan_float.cu
+++ b/test/test_beta_dist_quan_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_cdf_double.cu b/test/test_cauchy_cdf_double.cu
index dc99cbe33c..526744ba1f 100644
--- a/test/test_cauchy_cdf_double.cu
+++ b/test/test_cauchy_cdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_cdf_float.cu b/test/test_cauchy_cdf_float.cu
index dc99cbe33c..526744ba1f 100644
--- a/test/test_cauchy_cdf_float.cu
+++ b/test/test_cauchy_cdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_pdf_double.cu b/test/test_cauchy_pdf_double.cu
index 7a7fe5ba62..62398c31ed 100644
--- a/test/test_cauchy_pdf_double.cu
+++ b/test/test_cauchy_pdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_pdf_float.cu b/test/test_cauchy_pdf_float.cu
index 5ec3b604b5..aff3369b83 100644
--- a/test/test_cauchy_pdf_float.cu
+++ b/test/test_cauchy_pdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_quan_double.cu b/test/test_cauchy_quan_double.cu
index 21f4b4ddaa..0fcaaafe7c 100644
--- a/test/test_cauchy_quan_double.cu
+++ b/test/test_cauchy_quan_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_quan_float.cu b/test/test_cauchy_quan_float.cu
index b6bed15207..9c04c5b12a 100644
--- a/test/test_cauchy_quan_float.cu
+++ b/test/test_cauchy_quan_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_range_support_double.cu b/test/test_cauchy_range_support_double.cu
index 4ec792ce30..3a42c1bd30 100644
--- a/test/test_cauchy_range_support_double.cu
+++ b/test/test_cauchy_range_support_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_cauchy_range_support_float.cu b/test/test_cauchy_range_support_float.cu
index 1cdd90e407..e713736e60 100644
--- a/test/test_cauchy_range_support_float.cu
+++ b/test/test_cauchy_range_support_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_cdf_double.cu b/test/test_chi_squared_cdf_double.cu
index 1b0c34ce6b..c2475883b9 100644
--- a/test/test_chi_squared_cdf_double.cu
+++ b/test/test_chi_squared_cdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_cdf_float.cu b/test/test_chi_squared_cdf_float.cu
index 8ca99ed2e0..07dce0d067 100644
--- a/test/test_chi_squared_cdf_float.cu
+++ b/test/test_chi_squared_cdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_pdf_double.cu b/test/test_chi_squared_pdf_double.cu
index ed45246d3c..30edafd050 100644
--- a/test/test_chi_squared_pdf_double.cu
+++ b/test/test_chi_squared_pdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_pdf_float.cu b/test/test_chi_squared_pdf_float.cu
index 5a0f97db93..9b205182ba 100644
--- a/test/test_chi_squared_pdf_float.cu
+++ b/test/test_chi_squared_pdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_quan_double.cu b/test/test_chi_squared_quan_double.cu
index 3b7dad972b..3fae7d966f 100644
--- a/test/test_chi_squared_quan_double.cu
+++ b/test/test_chi_squared_quan_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_chi_squared_quan_float.cu b/test/test_chi_squared_quan_float.cu
index 3e779a090f..7a717530e1 100644
--- a/test/test_chi_squared_quan_float.cu
+++ b/test/test_chi_squared_quan_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_cdf_double.cu b/test/test_exponential_cdf_double.cu
index 8601d1c081..e3a57e86ec 100644
--- a/test/test_exponential_cdf_double.cu
+++ b/test/test_exponential_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_cdf_float.cu b/test/test_exponential_cdf_float.cu
index aa5ef9153e..ed214a4953 100644
--- a/test/test_exponential_cdf_float.cu
+++ b/test/test_exponential_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_pdf_double.cu b/test/test_exponential_pdf_double.cu
index 9a5615f1bc..530b1023b3 100644
--- a/test/test_exponential_pdf_double.cu
+++ b/test/test_exponential_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_pdf_float.cu b/test/test_exponential_pdf_float.cu
index f15ee3ea81..0801e2d0be 100644
--- a/test/test_exponential_pdf_float.cu
+++ b/test/test_exponential_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_quan_double.cu b/test/test_exponential_quan_double.cu
index ea5a5a6813..f4eb4c3b18 100644
--- a/test/test_exponential_quan_double.cu
+++ b/test/test_exponential_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_quan_float.cu b/test/test_exponential_quan_float.cu
index ea5a5a6813..f4eb4c3b18 100644
--- a/test/test_exponential_quan_float.cu
+++ b/test/test_exponential_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_range_support_double.cu b/test/test_exponential_range_support_double.cu
index eec3981d2a..c19497ed50 100644
--- a/test/test_exponential_range_support_double.cu
+++ b/test/test_exponential_range_support_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_exponential_range_support_float.cu b/test/test_exponential_range_support_float.cu
index 00f443e52f..a111090de5 100644
--- a/test/test_exponential_range_support_float.cu
+++ b/test/test_exponential_range_support_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_cdf_double.cu b/test/test_extreme_value_cdf_double.cu
index 8f7f366b3b..7ca0003482 100644
--- a/test/test_extreme_value_cdf_double.cu
+++ b/test/test_extreme_value_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_cdf_float.cu b/test/test_extreme_value_cdf_float.cu
index d1b6cc7624..bc3ead6ebb 100644
--- a/test/test_extreme_value_cdf_float.cu
+++ b/test/test_extreme_value_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_pdf_double.cu b/test/test_extreme_value_pdf_double.cu
index 4cf3fc2d0f..44ccc5b716 100644
--- a/test/test_extreme_value_pdf_double.cu
+++ b/test/test_extreme_value_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_pdf_float.cu b/test/test_extreme_value_pdf_float.cu
index c0c5da7eeb..390622f400 100644
--- a/test/test_extreme_value_pdf_float.cu
+++ b/test/test_extreme_value_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_quan_double.cu b/test/test_extreme_value_quan_double.cu
index 703d2054f3..41f2f69a68 100644
--- a/test/test_extreme_value_quan_double.cu
+++ b/test/test_extreme_value_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_extreme_value_quan_float.cu b/test/test_extreme_value_quan_float.cu
index 25d982cd0f..5fe16e9a8c 100644
--- a/test/test_extreme_value_quan_float.cu
+++ b/test/test_extreme_value_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_fisher_f.cpp b/test/test_fisher_f.cpp
index c18ed8ff1c..f142a33273 100644
--- a/test/test_fisher_f.cpp
+++ b/test/test_fisher_f.cpp
@@ -8,9 +8,13 @@
 // (See accompanying file LICENSE_1_0.txt
 // or copy at http://www.boost.org/LICENSE_1_0.txt)
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
 #include <boost/math/distributions/fisher_f.hpp> // for fisher_f_distribution
 using boost::math::fisher_f_distribution;
diff --git a/test/test_fisher_f_cdf_double.cu b/test/test_fisher_f_cdf_double.cu
new file mode 100644
index 0000000000..c6d6f0a94c
--- /dev/null
+++ b/test/test_fisher_f_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_cdf_float.cu b/test/test_fisher_f_cdf_float.cu
new file mode 100644
index 0000000000..9df1bc8695
--- /dev/null
+++ b/test/test_fisher_f_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_cdf_nvrtc_double.cpp b/test/test_fisher_f_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1eb9cb00f6
--- /dev/null
+++ b/test/test_fisher_f_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fisher_f_cdf_nvrtc_float.cpp b/test/test_fisher_f_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..244190cf19
--- /dev/null
+++ b/test/test_fisher_f_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fisher_f_pdf_double.cu b/test/test_fisher_f_pdf_double.cu
new file mode 100644
index 0000000000..77a3b655ab
--- /dev/null
+++ b/test/test_fisher_f_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_pdf_float.cu b/test/test_fisher_f_pdf_float.cu
new file mode 100644
index 0000000000..323edf3424
--- /dev/null
+++ b/test/test_fisher_f_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_pdf_nvrtc_double.cpp b/test/test_fisher_f_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..8aa1482aae
--- /dev/null
+++ b/test/test_fisher_f_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fisher_f_pdf_nvrtc_float.cpp b/test/test_fisher_f_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..e461dea9af
--- /dev/null
+++ b/test/test_fisher_f_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fisher_f_quan_double.cu b/test/test_fisher_f_quan_double.cu
new file mode 100644
index 0000000000..c16eb2a952
--- /dev/null
+++ b/test/test_fisher_f_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_quan_float.cu b/test/test_fisher_f_quan_float.cu
new file mode 100644
index 0000000000..85cf479670
--- /dev/null
+++ b/test/test_fisher_f_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::fisher_f_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_fisher_f_quan_nvrtc_double.cpp b/test/test_fisher_f_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..16ad0cbc03
--- /dev/null
+++ b/test/test_fisher_f_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_fisher_f_quan_nvrtc_float.cpp b/test/test_fisher_f_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..377048e526
--- /dev/null
+++ b/test/test_fisher_f_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/fisher_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/fisher_f.hpp>
+extern "C" __global__ 
+void test_fisher_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_fisher_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_fisher_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_fisher_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::fisher_f_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist.cpp b/test/test_gamma_dist.cpp
index b7776c79cb..2b1a181f33 100644
--- a/test/test_gamma_dist.cpp
+++ b/test/test_gamma_dist.cpp
@@ -15,16 +15,23 @@
 // From MathWorld--A Wolfram Web Resource.
 // http://mathworld.wolfram.com/GammaDistribution.html
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp> // include directory libs/math/src/tr1/ is needed.
+#endif
+
+#include <boost/math/tools/config.hpp>
 
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/gamma.hpp>
     using boost::math::gamma_distribution;
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_gamma_dist_cdf_double.cu b/test/test_gamma_dist_cdf_double.cu
new file mode 100644
index 0000000000..4777196aa1
--- /dev/null
+++ b/test/test_gamma_dist_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_cdf_float.cu b/test/test_gamma_dist_cdf_float.cu
new file mode 100644
index 0000000000..a93aca3950
--- /dev/null
+++ b/test/test_gamma_dist_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_cdf_nvrtc_double.cpp b/test/test_gamma_dist_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..3e911f4e05
--- /dev/null
+++ b/test/test_gamma_dist_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist_cdf_nvrtc_float.cpp b/test/test_gamma_dist_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..17762d4066
--- /dev/null
+++ b/test/test_gamma_dist_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist_pdf_double.cu b/test/test_gamma_dist_pdf_double.cu
new file mode 100644
index 0000000000..a8411d5b6d
--- /dev/null
+++ b/test/test_gamma_dist_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_pdf_float.cu b/test/test_gamma_dist_pdf_float.cu
new file mode 100644
index 0000000000..6ab3247acb
--- /dev/null
+++ b/test/test_gamma_dist_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_pdf_nvrtc_double.cpp b/test/test_gamma_dist_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1faae99866
--- /dev/null
+++ b/test/test_gamma_dist_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist_pdf_nvrtc_float.cpp b/test/test_gamma_dist_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..054ddbbadc
--- /dev/null
+++ b/test/test_gamma_dist_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist_quan_double.cu b/test/test_gamma_dist_quan_double.cu
new file mode 100644
index 0000000000..d29bf6d6be
--- /dev/null
+++ b/test/test_gamma_dist_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_quan_float.cu b/test/test_gamma_dist_quan_float.cu
new file mode 100644
index 0000000000..58aa42e90f
--- /dev/null
+++ b/test/test_gamma_dist_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::gamma_distribution<float_type>(1, 1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_gamma_dist_quan_nvrtc_double.cpp b/test/test_gamma_dist_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..132efcd6c1
--- /dev/null
+++ b/test/test_gamma_dist_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gamma_dist_quan_nvrtc_float.cpp b/test/test_gamma_dist_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..7749523abc
--- /dev/null
+++ b/test/test_gamma_dist_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/gamma.hpp>
+extern "C" __global__ 
+void test_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::gamma_distribution<float_type>(1, 1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::gamma_distribution<float_type>(1, 1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric.cpp b/test/test_geometric.cpp
index 928a2aa0ed..13a9e090b9 100644
--- a/test/test_geometric.cpp
+++ b/test/test_geometric.cpp
@@ -26,9 +26,14 @@
 #  define TEST_REAL_CONCEPT
 #endif
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
 #include <boost/math/distributions/geometric.hpp> // for geometric_distribution
 using boost::math::geometric_distribution;
@@ -64,7 +69,11 @@ void test_spot( // Test a single spot value against 'known good' values.
                RealType tol,     // Test tolerance
                RealType logtol)  // Logcdf Test tolerance.
 {
-   BOOST_IF_CONSTEXPR (std::is_same<RealType, long double>::value || std::is_same<RealType, real_concept>::value)
+   BOOST_IF_CONSTEXPR (std::is_same<RealType, long double>::value 
+                       #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
+                       || std::is_same<RealType, real_concept>::value
+                       #endif
+                       )
    {
      logtol *= 100;
    }
@@ -376,7 +385,9 @@ if(std::numeric_limits<RealType>::is_specialized)
   static_cast<RealType>(9.9000000000003448e-201L), //
   100 * tolerance); // Note difference
 
-    // p nearer unity.
+  // p nearer unity.
+  // On GPU this gets flushed to 0 which has an eps difference of 3.4e+38
+  #ifndef BOOST_MATH_HAS_GPU_SUPPORT
   BOOST_CHECK_CLOSE_FRACTION( //
   pdf(geometric_distribution<RealType>(static_cast<RealType>(0.9999)),
   static_cast<RealType>(10) ),  // Number of failures, k
@@ -384,6 +395,7 @@ if(std::numeric_limits<RealType>::is_specialized)
   // static_cast<float>(1.00156406e-040)
   static_cast<RealType>(9.999e-41), // exact from 100 digit calculator.
   2e3 * tolerance); // Note bigger tolerance needed.
+  #endif
 
   // Moshier Cephes 100 digits calculator says 9.999e-41
   //0.9999*pow(1-0.9999,10)
diff --git a/test/test_geometric_dist_cdf_double.cu b/test/test_geometric_dist_cdf_double.cu
new file mode 100644
index 0000000000..98b6510ad1
--- /dev/null
+++ b/test/test_geometric_dist_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_cdf_float.cu b/test/test_geometric_dist_cdf_float.cu
new file mode 100644
index 0000000000..2662ac07c5
--- /dev/null
+++ b/test/test_geometric_dist_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_cdf_nvrtc_double.cpp b/test/test_geometric_dist_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f8c5ed5aad
--- /dev/null
+++ b/test/test_geometric_dist_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric_dist_cdf_nvrtc_float.cpp b/test/test_geometric_dist_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..a53cd0d972
--- /dev/null
+++ b/test/test_geometric_dist_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric_dist_pdf_double.cu b/test/test_geometric_dist_pdf_double.cu
new file mode 100644
index 0000000000..03d2dc0078
--- /dev/null
+++ b/test/test_geometric_dist_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_pdf_float.cu b/test/test_geometric_dist_pdf_float.cu
new file mode 100644
index 0000000000..1034d122b5
--- /dev/null
+++ b/test/test_geometric_dist_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_pdf_nvrtc_double.cpp b/test/test_geometric_dist_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..8a6b5756e6
--- /dev/null
+++ b/test/test_geometric_dist_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric_dist_pdf_nvrtc_float.cpp b/test/test_geometric_dist_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..dfb05105dd
--- /dev/null
+++ b/test/test_geometric_dist_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric_dist_quan_double.cu b/test/test_geometric_dist_quan_double.cu
new file mode 100644
index 0000000000..fcac938e5a
--- /dev/null
+++ b/test/test_geometric_dist_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_quan_float.cu b/test/test_geometric_dist_quan_float.cu
new file mode 100644
index 0000000000..0749522021
--- /dev/null
+++ b/test/test_geometric_dist_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch geometric distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::geometric_distribution<float_type>(0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 1000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_geometric_dist_quan_nvrtc_double.cpp b/test/test_geometric_dist_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..52b2e97ec4
--- /dev/null
+++ b/test/test_geometric_dist_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_geometric_dist_quan_nvrtc_float.cpp b/test/test_geometric_dist_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..a83cf857e8
--- /dev/null
+++ b/test/test_geometric_dist_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/geometric.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/geometric.hpp>
+extern "C" __global__ 
+void test_geometric_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::geometric_distribution<float_type>(0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_geometric_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_geometric_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_geometric_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::geometric_distribution<float_type>(0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_holtsmark_cdf_double.cu b/test/test_holtsmark_cdf_double.cu
index 5a02b7ddb5..6b1d57041c 100644
--- a/test/test_holtsmark_cdf_double.cu
+++ b/test/test_holtsmark_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_holtsmark_cdf_float.cu b/test/test_holtsmark_cdf_float.cu
index 71ae21f731..2a3533bac9 100644
--- a/test/test_holtsmark_cdf_float.cu
+++ b/test/test_holtsmark_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_holtsmark_pdf_double.cu b/test/test_holtsmark_pdf_double.cu
index b883515a76..a53360d200 100644
--- a/test/test_holtsmark_pdf_double.cu
+++ b/test/test_holtsmark_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_holtsmark_pdf_float.cu b/test/test_holtsmark_pdf_float.cu
index c568159739..57052803fc 100644
--- a/test/test_holtsmark_pdf_float.cu
+++ b/test/test_holtsmark_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_inverse_chi_squared_cdf_double.cu b/test/test_inverse_chi_squared_cdf_double.cu
new file mode 100644
index 0000000000..9703e7a3a0
--- /dev/null
+++ b/test/test_inverse_chi_squared_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_cdf_float.cu b/test/test_inverse_chi_squared_cdf_float.cu
new file mode 100644
index 0000000000..bb56a48728
--- /dev/null
+++ b/test/test_inverse_chi_squared_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_cdf_nvrtc_double.cpp b/test/test_inverse_chi_squared_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..b221aedaab
--- /dev/null
+++ b/test/test_inverse_chi_squared_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_chi_squared_cdf_nvrtc_float.cpp b/test/test_inverse_chi_squared_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..743654c149
--- /dev/null
+++ b/test/test_inverse_chi_squared_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_chi_squared_distribution.cpp b/test/test_inverse_chi_squared_distribution.cpp
index a697824185..cbc9dcf191 100644
--- a/test/test_inverse_chi_squared_distribution.cpp
+++ b/test/test_inverse_chi_squared_distribution.cpp
@@ -14,11 +14,14 @@
 
 // http://www.wolframalpha.com/input/?i=inverse+chisquare+distribution
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
-//#include <boost/math/tools/test.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // for test_main
 #include <boost/test/tools/floating_point_comparison.hpp> // for BOOST_CHECK_CLOSE_FRACTION
diff --git a/test/test_inverse_chi_squared_pdf_double.cu b/test/test_inverse_chi_squared_pdf_double.cu
new file mode 100644
index 0000000000..f306117493
--- /dev/null
+++ b/test/test_inverse_chi_squared_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_pdf_float.cu b/test/test_inverse_chi_squared_pdf_float.cu
new file mode 100644
index 0000000000..8a3d1c1ef3
--- /dev/null
+++ b/test/test_inverse_chi_squared_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_pdf_nvrtc_double.cpp b/test/test_inverse_chi_squared_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4608b3bd62
--- /dev/null
+++ b/test/test_inverse_chi_squared_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_chi_squared_pdf_nvrtc_float.cpp b/test/test_inverse_chi_squared_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..8b4db55c0a
--- /dev/null
+++ b/test/test_inverse_chi_squared_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_chi_squared_quan_double.cu b/test/test_inverse_chi_squared_quan_double.cu
new file mode 100644
index 0000000000..f9022c6a32
--- /dev/null
+++ b/test/test_inverse_chi_squared_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_quan_float.cu b/test/test_inverse_chi_squared_quan_float.cu
new file mode 100644
index 0000000000..10aa6d7075
--- /dev/null
+++ b/test/test_inverse_chi_squared_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_chi_squared_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_chi_squared_quan_nvrtc_double.cpp b/test/test_inverse_chi_squared_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..0f8a9a5f82
--- /dev/null
+++ b/test/test_inverse_chi_squared_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_chi_squared_quan_nvrtc_float.cpp b/test/test_inverse_chi_squared_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..ab494a8da3
--- /dev/null
+++ b/test/test_inverse_chi_squared_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_chi_squared.hpp>
+extern "C" __global__ 
+void test_inverse_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_chi_squared_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_cdf_double.cu b/test/test_inverse_gamma_cdf_double.cu
new file mode 100644
index 0000000000..4368a2284b
--- /dev/null
+++ b/test/test_inverse_gamma_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_cdf_float.cu b/test/test_inverse_gamma_cdf_float.cu
new file mode 100644
index 0000000000..cef2ec955f
--- /dev/null
+++ b/test/test_inverse_gamma_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_cdf_nvrtc_double.cpp b/test/test_inverse_gamma_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..c5a4b9878a
--- /dev/null
+++ b/test/test_inverse_gamma_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_cdf_nvrtc_float.cpp b/test/test_inverse_gamma_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..d76d512256
--- /dev/null
+++ b/test/test_inverse_gamma_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_distribution.cpp b/test/test_inverse_gamma_distribution.cpp
index 68b238fbc8..436131d83f 100644
--- a/test/test_inverse_gamma_distribution.cpp
+++ b/test/test_inverse_gamma_distribution.cpp
@@ -14,11 +14,14 @@
 #  pragma warning (disable : 4310) // cast truncates constant value
 #endif
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
-//#include <boost/math/tools/test.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // for test_main
 #include <boost/test/tools/floating_point_comparison.hpp> // for BOOST_CHECK_CLOSE_FRACTION
diff --git a/test/test_inverse_gamma_pdf_double.cu b/test/test_inverse_gamma_pdf_double.cu
new file mode 100644
index 0000000000..fa5073dbe0
--- /dev/null
+++ b/test/test_inverse_gamma_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_pdf_float.cu b/test/test_inverse_gamma_pdf_float.cu
new file mode 100644
index 0000000000..c2d80fe8d5
--- /dev/null
+++ b/test/test_inverse_gamma_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_pdf_nvrtc_double.cpp b/test/test_inverse_gamma_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..db2c8c4e19
--- /dev/null
+++ b/test/test_inverse_gamma_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_pdf_nvrtc_float.cpp b/test/test_inverse_gamma_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..4d552cf619
--- /dev/null
+++ b/test/test_inverse_gamma_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_quan_double.cu b/test/test_inverse_gamma_quan_double.cu
new file mode 100644
index 0000000000..c9095d7527
--- /dev/null
+++ b/test/test_inverse_gamma_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_quan_float.cu b/test/test_inverse_gamma_quan_float.cu
new file mode 100644
index 0000000000..3e60feaa18
--- /dev/null
+++ b/test/test_inverse_gamma_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gamma distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_gamma_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gamma_quan_nvrtc_double.cpp b/test/test_inverse_gamma_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..a49600bde1
--- /dev/null
+++ b/test/test_inverse_gamma_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gamma_quan_nvrtc_float.cpp b/test/test_inverse_gamma_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..f71ed964aa
--- /dev/null
+++ b/test/test_inverse_gamma_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gamma.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gamma.hpp>
+extern "C" __global__ 
+void test_inverse_gamma_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gamma_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gamma_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gamma_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gamma_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_gamma_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_landau_cdf_double.cu b/test/test_landau_cdf_double.cu
index 092fff00ed..40bff707d8 100644
--- a/test/test_landau_cdf_double.cu
+++ b/test/test_landau_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_landau_cdf_float.cu b/test/test_landau_cdf_float.cu
index 143755aff9..c4513c0844 100644
--- a/test/test_landau_cdf_float.cu
+++ b/test/test_landau_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_landau_pdf_double.cu b/test/test_landau_pdf_double.cu
index eea6f87add..6ce3f5f784 100644
--- a/test/test_landau_pdf_double.cu
+++ b/test/test_landau_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_landau_pdf_float.cu b/test/test_landau_pdf_float.cu
index a424bdd678..5818ddf8a5 100644
--- a/test/test_landau_pdf_float.cu
+++ b/test/test_landau_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_landau_quan_double.cu b/test/test_landau_quan_double.cu
index 8cdf12588d..4995bd49cf 100644
--- a/test/test_landau_quan_double.cu
+++ b/test/test_landau_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_landau_quan_float.cu b/test/test_landau_quan_float.cu
index 8cdf12588d..4995bd49cf 100644
--- a/test/test_landau_quan_float.cu
+++ b/test/test_landau_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_cdf_double.cu b/test/test_laplace_cdf_double.cu
index cddcfa2bc0..ec3c83ecde 100644
--- a/test/test_laplace_cdf_double.cu
+++ b/test/test_laplace_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_cdf_float.cu b/test/test_laplace_cdf_float.cu
index 2af43f9f5e..96acea2fda 100644
--- a/test/test_laplace_cdf_float.cu
+++ b/test/test_laplace_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_pdf_double.cu b/test/test_laplace_pdf_double.cu
index 2f53c0dd10..568be622b5 100644
--- a/test/test_laplace_pdf_double.cu
+++ b/test/test_laplace_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_pdf_float.cu b/test/test_laplace_pdf_float.cu
index a8d673dba5..cb2aa67c11 100644
--- a/test/test_laplace_pdf_float.cu
+++ b/test/test_laplace_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_quan_double.cu b/test/test_laplace_quan_double.cu
index cddcfa2bc0..ec3c83ecde 100644
--- a/test/test_laplace_quan_double.cu
+++ b/test/test_laplace_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_laplace_quan_float.cu b/test/test_laplace_quan_float.cu
index 2af43f9f5e..96acea2fda 100644
--- a/test/test_laplace_quan_float.cu
+++ b/test/test_laplace_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_cdf_double.cu b/test/test_logistic_cdf_double.cu
index 5dd3723c57..6b4e850259 100644
--- a/test/test_logistic_cdf_double.cu
+++ b/test/test_logistic_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_cdf_float.cu b/test/test_logistic_cdf_float.cu
index 89d05747b9..75b6ab0afd 100644
--- a/test/test_logistic_cdf_float.cu
+++ b/test/test_logistic_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_pdf_double.cu b/test/test_logistic_pdf_double.cu
index 39aaa1597a..90232a2d6a 100644
--- a/test/test_logistic_pdf_double.cu
+++ b/test/test_logistic_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_pdf_float.cu b/test/test_logistic_pdf_float.cu
index 279112b995..0a99ff9cf1 100644
--- a/test/test_logistic_pdf_float.cu
+++ b/test/test_logistic_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_quan_double.cu b/test/test_logistic_quan_double.cu
index ad929d4424..afe8a4c8cd 100644
--- a/test/test_logistic_quan_double.cu
+++ b/test/test_logistic_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_logistic_quan_float.cu b/test/test_logistic_quan_float.cu
index 81c22ea4b6..92c371062f 100644
--- a/test/test_logistic_quan_float.cu
+++ b/test/test_logistic_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_cdf_double.cu b/test/test_mapairy_cdf_double.cu
index 1494181bf5..7cb62a9343 100644
--- a/test/test_mapairy_cdf_double.cu
+++ b/test/test_mapairy_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_cdf_float.cu b/test/test_mapairy_cdf_float.cu
index 41dd4615aa..b67c0ee933 100644
--- a/test/test_mapairy_cdf_float.cu
+++ b/test/test_mapairy_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_pdf_double.cu b/test/test_mapairy_pdf_double.cu
index ad3abfbeea..4ccd8b2f23 100644
--- a/test/test_mapairy_pdf_double.cu
+++ b/test/test_mapairy_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_pdf_float.cu b/test/test_mapairy_pdf_float.cu
index cabee4a2f6..520ac9a68a 100644
--- a/test/test_mapairy_pdf_float.cu
+++ b/test/test_mapairy_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_quan_double.cu b/test/test_mapairy_quan_double.cu
index fe6265effe..3787000207 100644
--- a/test/test_mapairy_quan_double.cu
+++ b/test/test_mapairy_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_mapairy_quan_float.cu b/test/test_mapairy_quan_float.cu
index ad2f6b5eb4..cd9d120070 100644
--- a/test/test_mapairy_quan_float.cu
+++ b/test/test_mapairy_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_cdf_double.cu b/test/test_saspoint5_cdf_double.cu
index 745ca2bf80..fb3e2f74c8 100644
--- a/test/test_saspoint5_cdf_double.cu
+++ b/test/test_saspoint5_cdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_cdf_float.cu b/test/test_saspoint5_cdf_float.cu
index 51bc2e8705..325a470bba 100644
--- a/test/test_saspoint5_cdf_float.cu
+++ b/test/test_saspoint5_cdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_pdf_double.cu b/test/test_saspoint5_pdf_double.cu
index 948a092600..5392a328bf 100644
--- a/test/test_saspoint5_pdf_double.cu
+++ b/test/test_saspoint5_pdf_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_pdf_float.cu b/test/test_saspoint5_pdf_float.cu
index 4980e9070c..01fbcd472b 100644
--- a/test/test_saspoint5_pdf_float.cu
+++ b/test/test_saspoint5_pdf_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_quan_double.cu b/test/test_saspoint5_quan_double.cu
index 764c278993..7415f06906 100644
--- a/test/test_saspoint5_quan_double.cu
+++ b/test/test_saspoint5_quan_double.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_saspoint5_quan_float.cu b/test/test_saspoint5_quan_float.cu
index a65958fb81..d6f49084bb 100644
--- a/test/test_saspoint5_quan_float.cu
+++ b/test/test_saspoint5_quan_float.cu
@@ -65,7 +65,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_cdf_double.cu b/test/test_weibull_cdf_double.cu
index 65efbe2528..1b2e5cf0db 100644
--- a/test/test_weibull_cdf_double.cu
+++ b/test/test_weibull_cdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_cdf_float.cu b/test/test_weibull_cdf_float.cu
index 65c3ce1ffc..76bf3a4e1c 100644
--- a/test/test_weibull_cdf_float.cu
+++ b/test/test_weibull_cdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_pdf_double.cu b/test/test_weibull_pdf_double.cu
index 645df4c0ad..dd48b57d60 100644
--- a/test/test_weibull_pdf_double.cu
+++ b/test/test_weibull_pdf_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_pdf_float.cu b/test/test_weibull_pdf_float.cu
index f1e6917f03..40064b1ed7 100644
--- a/test/test_weibull_pdf_float.cu
+++ b/test/test_weibull_pdf_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_quan_double.cu b/test/test_weibull_quan_double.cu
index 2f05006022..9263fb5365 100644
--- a/test/test_weibull_quan_double.cu
+++ b/test/test_weibull_quan_double.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 
diff --git a/test/test_weibull_quan_float.cu b/test/test_weibull_quan_float.cu
index 3027e14dda..5dd6bd6eef 100644
--- a/test/test_weibull_quan_float.cu
+++ b/test/test_weibull_quan_float.cu
@@ -64,7 +64,7 @@ int main(void)
     }
 
     // Launch the Vector Add CUDA Kernel
-    int threadsPerBlock = 512;
+    int threadsPerBlock = 256;
     int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
     std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
 

From 41f07b079445932f18b0d355a5381654d3ca7fb0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ren=C3=A9=20Ferdinand=20Rivera=20Morell?=
 <grafikrobot@gmail.com>
Date: Fri, 6 Sep 2024 07:45:23 -0500
Subject: [PATCH 374/399] Add support for modular build structure. (#1160)

* Make the library modular usable.

* Fix -Wundef warnings

* Switch to library requirements instead of source. As source puts extra source in install targets.

* Add missing NO_LIB usage requirements.

* Remove boost-root relative include path.

* Add missing import-search for cconfig/predef checks.

* Add requires-b2 check to top-level build file.

* Sync upstream.

* Fix typo in test framework reference.

* Bump B2 require to 5.2

* Update copyright dates.

* Move inter-lib dependencies to a project variable and into the build targets.

* Switch to /boost/test//included target for header only mode of Boost.Test.

* Adjust doc build to avoid boost-root references.

* Update build deps.

* Fix project props not applying to the no_eh.obj compile.

* Update build deps.

* Add missing import-search.

* Fix float128_type checks to actually disable tests. Problem was that build is a non-free feature. Which can't be acquired through a usage requirement.

* GPU Batch 7

Fix igamma_large support on device

Add GPU support to toms748

Add GPU support to igamma_inv

Add GPU markers to gamma_inva

Add GPU Markers to lgamma_small

Remove STL usage from gamma

Remove NVRTC workaround

Fix fraction use of STL headers

Mark gamma functions in fwd

Disable declval on all GPU platforms

Disable more unneeded code on device

Add forward decl for NVRTC tgamma

Disable unneeded items for all GPU

Change workaround for missing overloads

Rearrange definition location

Add include path to cuda now that workaround is removed

Fix NVRTC incompatibility with recursion and forward decls

Add tgamma_ratio CUDA and NVRTC testing

Fix NVRTC handling of gamma_p_derivative

Add gamma_p_derivative CUDA and NVRTC testing

Remove recursion from gamma_incomplete_imp

Add SYCL testing of igamma, igamma_inv, and igamma_inva

Ignore literal-range warnings

Remove use of static const char* for function name

Fix missing CUDA header

Remove calls under NVRTC to fwd decl

Add more nvrtc workarounds

Use builtin erfc instead of header cycle

Add CUDA and NVRTC testing of gamma_p_inv

Adjust tolerances

Add GPU support to chi squared dist

Fix static local variable

Add chi squared dist SYCL testing

Add chi squared dist CUDA testing

Add chi squared dist NVRTC testing

Add GPU support to weibull dist

Add weibull dist SYCL testing

Add weibull dist CUDA testing

Add weibull dist NVRTC testing

* Fix policy macro definition for MSVC platforms

* Don't add quadmath lib for has_128bit_floatmax_t check. It was accidentally copy+pasted.

* Fix incorrect name for float128 type check that caused it to not apear.

---------

Co-authored-by: Matt Borland <matt@mattborland.com>
---
 build.jam                             |  48 ++
 build/Jamfile.v2                      |  38 +-
 config/Jamfile.v2                     |  10 +-
 doc/Jamfile.v2                        |  14 +-
 example/Jamfile.v2                    |  14 +-
 reporting/accuracy/Jamfile.v2         |  91 +--
 reporting/performance/Jamfile.v2      |  84 +--
 test/Jamfile.v2                       | 886 +++++++++++++-------------
 test/float128/log1p_expm1_test.cpp    |   2 +-
 test/float128/powm1_sqrtp1m1_test.cpp |   2 +-
 test/float128/table_type.hpp          |   2 +-
 test/float128/test_bessel_i.cpp       |   2 +-
 test/float128/test_bessel_j.cpp       |   2 +-
 test/float128/test_bessel_k.cpp       |   2 +-
 test/float128/test_bessel_y.cpp       |   2 +-
 test/float128/test_beta.cpp           |   2 +-
 test/float128/test_binomial_coeff.cpp |   2 +-
 test/float128/test_carlson.cpp        |   2 +-
 test/float128/test_cbrt.cpp           |   2 +-
 test/float128/test_digamma.cpp        |   2 +-
 test/float128/test_ellint_1.cpp       |   2 +-
 test/float128/test_ellint_2.cpp       |   2 +-
 test/float128/test_ellint_3.cpp       |   2 +-
 test/float128/test_erf.cpp            |   2 +-
 test/float128/test_expint.cpp         |   2 +-
 test/float128/test_gamma.cpp          |   2 +-
 test/float128/test_hermite.cpp        |   2 +-
 test/float128/test_ibeta.cpp          |   2 +-
 test/float128/test_ibeta_inv_1.cpp    |   2 +-
 test/float128/test_ibeta_inv_ab_4.cpp |   2 +-
 test/float128/test_igamma.cpp         |   2 +-
 test/float128/test_igamma_inv.cpp     |   2 +-
 test/float128/test_igamma_inva.cpp    |   2 +-
 test/float128/test_laguerre.cpp       |   2 +-
 test/float128/test_legendre.cpp       |   2 +-
 test/float128/test_polygamma.cpp      |   2 +-
 test/float128/test_tgamma_ratio.cpp   |   2 +-
 test/float128/test_trigamma.cpp       |   2 +-
 test/float128/test_zeta.cpp           |   2 +-
 test/test_bernoulli_constants.cpp     | 198 +++---
 test/test_nonfinite_io.cpp            |   4 +-
 tools/Jamfile.v2                      | 132 ++--
 tools/ibeta_derivative_data.cpp       |   4 +-
 tools/nc_t_data.cpp                   |   6 +-
 44 files changed, 832 insertions(+), 759 deletions(-)
 create mode 100644 build.jam

diff --git a/build.jam b/build.jam
new file mode 100644
index 0000000000..fb244e511d
--- /dev/null
+++ b/build.jam
@@ -0,0 +1,48 @@
+# Copyright René Ferdinand Rivera Morell 2023-2024
+# Distributed under the Boost Software License, Version 1.0.
+# (See accompanying file LICENSE_1_0.txt or copy at
+# http://www.boost.org/LICENSE_1_0.txt)
+
+require-b2 5.2 ;
+
+constant boost_dependencies :
+    /boost/assert//boost_assert
+    /boost/concept_check//boost_concept_check
+    /boost/config//boost_config
+    /boost/core//boost_core
+    /boost/integer//boost_integer
+    /boost/lexical_cast//boost_lexical_cast
+    /boost/predef//boost_predef
+    /boost/random//boost_random
+    /boost/static_assert//boost_static_assert
+    /boost/throw_exception//boost_throw_exception ;
+
+project /boost/math
+    : common-requirements
+        <include>include
+    ;
+
+explicit
+    [ alias boost_math : : : : <library>$(boost_dependencies) ]
+    [ alias boost_math_c99 : build//boost_math_c99 ]
+    [ alias boost_math_c99f : build//boost_math_c99f ]
+    [ alias boost_math_c99l : build//boost_math_c99l ]
+    [ alias boost_math_tr1 : build//boost_math_tr1 ]
+    [ alias boost_math_tr1f : build//boost_math_tr1f ]
+    [ alias boost_math_tr1l : build//boost_math_tr1l ]
+    [ alias all :
+        boost_math
+        boost_math_c99 boost_math_c99f boost_math_c99l
+        boost_math_tr1 boost_math_tr1f boost_math_tr1l
+        example test ]
+    [ alias testing : : : :
+        <include>test
+        <include>include_private ]
+    ;
+
+call-if : boost-library math
+    : install boost_math
+        boost_math_c99 boost_math_c99f boost_math_c99l
+        boost_math_tr1 boost_math_tr1f boost_math_tr1l
+    ;
+
diff --git a/build/Jamfile.v2 b/build/Jamfile.v2
index 6549e06b79..500c77363d 100644
--- a/build/Jamfile.v2
+++ b/build/Jamfile.v2
@@ -1,16 +1,18 @@
 # copyright John Maddock 2008
-# Distributed under the Boost Software License, Version 1.0. 
-# (See accompanying file LICENSE_1_0.txt or copy at 
+# Distributed under the Boost Software License, Version 1.0.
+# (See accompanying file LICENSE_1_0.txt or copy at
 # http://www.boost.org/LICENSE_1_0.txt.
 
 import testing ;
 import pch ;
-import ../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 
-project  
-    : requirements 
-      <toolset>intel-win:<cxxflags>-nologo 
-      <toolset>intel-win:<linkflags>-nologo 
+project
+    : common-requirements <library>$(boost_dependencies)
+    : requirements
+      <toolset>intel-win:<cxxflags>-nologo
+      <toolset>intel-win:<linkflags>-nologo
       #<toolset>intel-linux:<pch>off
       <toolset>intel-darwin:<pch>off
       <toolset>gcc,<target-os>windows:<pch>off
@@ -20,9 +22,11 @@ project
       [ check-target-builds ../config//has_gcc_visibility "gcc visibility" : <toolset>gcc:<cxxflags>-fvisibility=hidden : ]
       [ requires cxx11_noexcept cxx11_rvalue_references sfinae_expr cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_hdr_initializer_list cxx11_hdr_chrono cxx11_thread_local cxx11_constexpr cxx11_nullptr cxx11_numeric_limits cxx11_decltype cxx11_hdr_array cxx11_hdr_atomic cxx11_hdr_type_traits cxx11_allocator cxx11_explicit_conversion_operators ]
       [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction ]
+    : usage-requirements
+        <define>BOOST_MATH_TR1_NO_LIB=1
     ;
 
-cpp-pch pch : ../src/tr1/pch.hpp : <include>../src/tr1 <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1 ; 
+cpp-pch pch : ../src/tr1/pch.hpp : <include>../src/tr1 <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1 ;
 
 C99_SOURCES = acosh
 asinh
@@ -46,7 +50,7 @@ round
 tgamma
 trunc ;
 
-TR1_SOURCES = 
+TR1_SOURCES =
 assoc_laguerre
 assoc_legendre
 beta
@@ -80,22 +84,22 @@ import targets ;
 
 obj long_double_check : ../config/has_long_double_support.cpp ;
 explicit long_double_check ;
-        
+
 # Library targets
 lib boost_math_tr1 : ../src/tr1/$(TR1_SOURCES).cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <include>../src/tr1
    ;
 
 lib boost_math_tr1f : ../src/tr1/$(TR1_SOURCES)f.cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <include>../src/tr1
    ;
 
 lib boost_math_tr1l : ../src/tr1/$(TR1_SOURCES)l.cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <dependency>../config//has_long_double_support
          <include>../src/tr1
@@ -103,23 +107,21 @@ lib boost_math_tr1l : ../src/tr1/$(TR1_SOURCES)l.cpp pch
    ;
 
 lib boost_math_c99 : ../src/tr1/$(C99_SOURCES).cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <include>../src/tr1
    ;
 
 lib boost_math_c99f : ../src/tr1/$(C99_SOURCES)f.cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <include>../src/tr1
    ;
 
 lib boost_math_c99l : ../src/tr1/$(C99_SOURCES)l.cpp pch
-    :         
+    :
          <link>shared:<define>BOOST_MATH_TR1_DYN_LINK=1
          <dependency>../config//has_long_double_support
          <include>../src/tr1
          [ check-target-builds ../config//has_long_double_support "long double support" : : <build>no ]
    ;
-
-boost-install boost_math_c99 boost_math_c99f boost_math_c99l boost_math_tr1 boost_math_tr1f boost_math_tr1l ;
diff --git a/config/Jamfile.v2 b/config/Jamfile.v2
index 77aca7c2e3..650e888809 100644
--- a/config/Jamfile.v2
+++ b/config/Jamfile.v2
@@ -9,11 +9,11 @@ import path ;
 local ntl-path = [ modules.peek : NTL_PATH ] ;
 local gmp_path = [ modules.peek : GMP_PATH ] ;
 
-lib quadmath ;
-lib fftw3 ;
-lib fftw3f ;
-lib fftw3l ;
-lib fftw3q ;
+searched-lib quadmath ;
+searched-lib fftw3 ;
+searched-lib fftw3f ;
+searched-lib fftw3l ;
+searched-lib fftw3q ;
 
 obj has_long_double_support : has_long_double_support.cpp ;
 obj has_mpfr_class : has_mpfr_class.cpp :
diff --git a/doc/Jamfile.v2 b/doc/Jamfile.v2
index 71746726f5..511262d493 100644
--- a/doc/Jamfile.v2
+++ b/doc/Jamfile.v2
@@ -13,7 +13,7 @@ path-constant here : . ;
 constant here-url : [ regex.replace $(here) "\\\\" "/" ] ;
 
 xml math : math.qbk :
-        <quickbook-define>enable_index 
+        <quickbook-define>enable_index
         <quickbook-define>__base_path__=$(here-url)
         <format>pdf:<quickbook-define>__build_pdf
         <format>html:<quickbook-define>__build_html
@@ -25,7 +25,7 @@ boostbook standalone
         # Path for links to Boost:
         <xsl:param>boost.root=../../../..
         <xsl:param>html.stylesheet=math.css
-        
+
         # Some general style settings:
         <xsl:param>table.footnote.number.format=1
         <xsl:param>footnote.number.format=1
@@ -46,11 +46,11 @@ boostbook standalone
         # Index on type:
         <xsl:param>index.on.type=1
         <xsl:param>boost.noexpand.chapter.toc=1
-        
+
         #<xsl:param>root.filename="sf_dist_and_tools"
         #<xsl:param>graphicsize.extension=1
         #<xsl:param>use.extensions=1
-        
+
         # PDF Options:
         # TOC Generation: this is needed for FOP-0.9 and later:
         <xsl:param>fop1.extensions=0
@@ -74,7 +74,7 @@ boostbook standalone
         # better use SVG's instead:
         <format>pdf:<xsl:param>admon.graphics.extension=".svg"
         <format>pdf:<xsl:param>admon.graphics.path=$(here)/../../../doc/src/images/
-        <format>pdf:<xsl:param>use.role.for.mediaobject=1 
+        <format>pdf:<xsl:param>use.role.for.mediaobject=1
         <format>pdf:<xsl:param>preferred.mediaobject.role=print
         <format>pdf:<xsl:param>img.src.path=$(images_location)/
         <format>pdf:<xsl:param>draft.mode="no"
@@ -82,7 +82,7 @@ boostbook standalone
         <auto-index>on <format>pdf:<auto-index-internal>off
         <format>html:<auto-index-internal>on
         <auto-index-script>$(here)/index.idx
-        <auto-index-prefix>$(here)/../../.. 
+        <auto-index-prefix>$(here)/../include
         #<auto-index-verbose>on
         <format>pdf:<xsl:param>index.on.type=1
     ;
@@ -90,7 +90,7 @@ boostbook standalone
 install pdfinstall : standalone/<format>pdf : <location>. <install-type>PDF <name>math.pdf ;
 explicit pdfinstall ; # b2 pdf pdfinstall to do this pdf file copy.
 
-install css_install : math.css : <location>$(here)/html ; 
+install css_install : math.css : <location>$(here)/html ;
 
 ###############################################################################
 alias boostdoc ;
diff --git a/example/Jamfile.v2 b/example/Jamfile.v2
index 34e4a5a8c8..2a6ad6947d 100644
--- a/example/Jamfile.v2
+++ b/example/Jamfile.v2
@@ -7,10 +7,13 @@
 
 # bring in the rules for testing
 import testing ;
-import ../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 
 project
     : requirements
+      <library>/boost/math//boost_math
+      <library>/boost/multiprecision//boost_multiprecision
       <toolset>gcc:<cxxflags>-Wno-missing-braces
       <toolset>darwin:<cxxflags>-Wno-missing-braces
       <toolset>acc:<cxxflags>+W2068,2461,2236,4070
@@ -36,7 +39,6 @@ project
       <toolset>clang:<cxxflags>-Wno-unknown-pragmas
       <toolset>clang:<cxxflags>-Wno-language-extension-token
 
-      <include>../../..
       <include>../include_private
       <exception-handling>off:<source>../test//no_eh
       [ requires cxx11_noexcept cxx11_rvalue_references sfinae_expr cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_hdr_initializer_list cxx11_hdr_chrono cxx11_thread_local cxx11_constexpr cxx11_nullptr cxx11_numeric_limits cxx11_decltype cxx11_hdr_array cxx11_hdr_atomic cxx11_hdr_type_traits cxx11_allocator cxx11_explicit_conversion_operators ]
@@ -53,7 +55,7 @@ test-suite examples :
    [ run binomial_example_nag.cpp  ]
    [ run binomial_quiz_example.cpp : : : <exception-handling>off:<build>no  ]
    [ run binomial_sample_sizes.cpp  ]
-   [ run brent_minimise_example.cpp  : : : [ requires cxx11_hdr_tuple ] ]
+   [ run brent_minimise_example.cpp /boost/test//included : : : [ requires cxx11_hdr_tuple ] ]
 
    [ run c_error_policy_example.cpp  ]
    [ run chi_square_std_dev_test.cpp : : : <exception-handling>off:<build>no  ]
@@ -93,11 +95,11 @@ test-suite examples :
 
    [ run nonfinite_num_facet.cpp  ]
    [ run nonfinite_facet_simple.cpp  ]
-   #[ run nonfinite_num_facet_serialization.cpp ../../serialization/build//boost_serialization : : : <exception-handling>off:<build>no <toolset>gcc-mingw:<link>static  ]
+   #[ run nonfinite_num_facet_serialization.cpp /boost/serialization//boost_serialization : : : <exception-handling>off:<build>no <toolset>gcc-mingw:<link>static  ]
    #[ # run lexical_cast_native.cpp  ] # Expected to fail on some (but not all) platforms.
    [ run lexical_cast_nonfinite_facets.cpp  ]
    [ run nonfinite_loopback_ok.cpp  ]
-   #[ run nonfinite_serialization_archives.cpp ../../serialization/build//boost_serialization  : : : <exception-handling>off:<build>no <toolset>gcc-mingw:<link>static  ]
+   #[ run nonfinite_serialization_archives.cpp /boost/serialization//boost_serialization  : : : <exception-handling>off:<build>no <toolset>gcc-mingw:<link>static  ]
    [ run nonfinite_facet_sstream.cpp  ]
 
    [ run constants_eg1.cpp  ]
@@ -113,7 +115,7 @@ test-suite examples :
    [ run policy_eg_6.cpp  ]
    [ run policy_eg_7.cpp  ]
    [ run policy_eg_8.cpp  ]
-   [ run policy_eg_9.cpp  ]
+   [ run policy_eg_9.cpp /boost/format//boost_format ]
    [ run policy_ref_snip1.cpp : : : <exception-handling>off:<build>no  ]
    [ run policy_ref_snip10.cpp  ]
    [ run policy_ref_snip11.cpp  ]
diff --git a/reporting/accuracy/Jamfile.v2 b/reporting/accuracy/Jamfile.v2
index a07e60083b..0d961e66c5 100644
--- a/reporting/accuracy/Jamfile.v2
+++ b/reporting/accuracy/Jamfile.v2
@@ -12,7 +12,8 @@ import testing ;
 import modules ;
 import path ;
 import pch ;
-import ../../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 using quickbook ;
 using auto-index ;
 
@@ -47,16 +48,16 @@ explicit has_gsl ;
 exe has_rmath : has_rmath.cpp Rmath ;
 explicit has_rmath ;
 
-CEPHES_SOURCE = acosh.c airy.c asin.c asinh.c atan.c atanh.c bdtr.c beta.c 
-btdtr.c cbrt.c chbevl.c chdtr.c clog.c cmplx.c const.c 
-cosh.c dawsn.c drand.c ei.c ellie.c ellik.c ellpe.c ellpj.c ellpk.c 
-exp.c exp10.c exp2.c expn.c expx2.c fabs.c fac.c fdtr.c 
-fresnl.c gamma.c gdtr.c hyp2f1.c hyperg.c i0.c i1.c igami.c incbet.c 
-incbi.c igam.c isnan.c iv.c j0.c j1.c jn.c jv.c k0.c k1.c kn.c kolmogorov.c 
-log.c log2.c log10.c lrand.c nbdtr.c ndtr.c ndtri.c pdtr.c planck.c 
-polevl.c polmisc.c polylog.c polyn.c pow.c powi.c psi.c rgamma.c round.c 
-shichi.c sici.c sin.c sindg.c sinh.c spence.c stdtr.c struve.c 
-tan.c tandg.c tanh.c unity.c yn.c zeta.c zetac.c 
+CEPHES_SOURCE = acosh.c airy.c asin.c asinh.c atan.c atanh.c bdtr.c beta.c
+btdtr.c cbrt.c chbevl.c chdtr.c clog.c cmplx.c const.c
+cosh.c dawsn.c drand.c ei.c ellie.c ellik.c ellpe.c ellpj.c ellpk.c
+exp.c exp10.c exp2.c expn.c expx2.c fabs.c fac.c fdtr.c
+fresnl.c gamma.c gdtr.c hyp2f1.c hyperg.c i0.c i1.c igami.c incbet.c
+incbi.c igam.c isnan.c iv.c j0.c j1.c jn.c jv.c k0.c k1.c kn.c kolmogorov.c
+log.c log2.c log10.c lrand.c nbdtr.c ndtr.c ndtri.c pdtr.c planck.c
+polevl.c polmisc.c polylog.c polyn.c pow.c powi.c psi.c rgamma.c round.c
+shichi.c sici.c sin.c sindg.c sinh.c spence.c stdtr.c struve.c
+tan.c tandg.c tanh.c unity.c yn.c zeta.c zetac.c
 sqrt.c floor.c setprec.c mtherr.c ;
 
 path-constant here : . ;
@@ -68,10 +69,10 @@ actions check_exists
 explicit $(here)/third_party/cephes_double/acosh.c ;
 
 lib cephes_double : $(here)/third_party/cephes_double/$(CEPHES_SOURCE)
-    :         
+    :
         release
         <link>static
-        [ check-target-builds $(here)/third_party/cephes_double/acosh.c : : <build>no ] 
+        [ check-target-builds $(here)/third_party/cephes_double/acosh.c : : <build>no ]
    ;
 
 explicit cephes_double ;
@@ -80,52 +81,52 @@ rule all-tests {
      local result ;
      for local source in [ glob test*.cpp ]
      {
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework 
-         : : : 
-          [ check-target-builds has_gsl : <define>ALWAYS_TEST_DOUBLE : ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index quadmath mpfr
+         : : :
+          [ check-target-builds has_gsl : <define>ALWAYS_TEST_DOUBLE : ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS) ]
          ;
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework 
-         : : : [ check-target-builds has_cxx17_cmath : <define>TEST_CXX17_CMATH : <build>no ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework  /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index quadmath mpfr
+         : : : [ check-target-builds has_cxx17_cmath : <define>TEST_CXX17_CMATH : <build>no ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS)
-          : $(source:B)_cxx17_cmath ] 
+          : $(source:B)_cxx17_cmath ]
          ;
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework 
-         : : : [ check-target-builds has_c99_cmath : <define>TEST_C99 : <build>no ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework  /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index quadmath mpfr
+         : : : [ check-target-builds has_c99_cmath : <define>TEST_C99 : <build>no ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS)
-          : $(source:B)_c99 ] 
+          : $(source:B)_c99 ]
          ;
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework gsl gslcblas
-         : : : [ check-target-builds has_gsl : <define>TEST_GSL : <build>no ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index gsl gslcblas
+         : : : [ check-target-builds has_gsl : <define>TEST_GSL : <build>no ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS)
-          : $(source:B)_gsl ] 
+          : $(source:B)_gsl ]
          ;
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework Rmath
-         : : : [ check-target-builds has_rmath : <define>TEST_RMATH : <build>no ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index Rmath
+         : : : [ check-target-builds has_rmath : <define>TEST_RMATH : <build>no ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS)
-          : $(source:B)_rmath ] 
+          : $(source:B)_rmath ]
          ;
-         result += [ run $(source) /boost/system /boost/filesystem /boost/test//boost_unit_test_framework cephes_double
-         : : : [ check-target-builds $(here)/third_party/cephes_double/acosh.c : <define>TEST_CEPHES <source>cephes_double : <build>no ] 
+         result += [ run $(source) /boost/system//boost_system /boost/filesystem//boost_filesystem /boost/test//boost_unit_test_framework /boost/interprocess//boost_interprocess /boost/multiprecision//boost_multiprecision /boost/type_index//boost_type_index cephes_double
+         : : : [ check-target-builds $(here)/third_party/cephes_double/acosh.c : <define>TEST_CEPHES <source>cephes_double : <build>no ]
           <target-os>linux:<linkflags>-lpthread
           <target-os>linux:<linkflags>-lrt
           <toolset>gcc:<linkflags>$(OTHERFLAGS)
-          : $(source:B)_cephes ] 
+          : $(source:B)_cephes ]
          ;
      }
-     return $(result) ;     
+     return $(result) ;
 }
-            
+
 test-suite report_gen : [ all-tests ] ;
 
 path-constant images_location : html ;
@@ -138,7 +139,7 @@ boostbook standalone
     :
         # Path for links to Boost:
         <xsl:param>boost.root=../../../../..
-        
+
         # Some general style settings:
         <xsl:param>table.footnote.number.format=1
         <xsl:param>footnote.number.format=1
@@ -159,25 +160,25 @@ boostbook standalone
         <xsl:param>generate.section.toc.level=10
     ;
 
-lib gmp ;
-lib mpfr ;
-lib quadmath ;
+searched-lib gmp : : <link>shared ;
+searched-lib mpfr : : <link>shared ;
+searched-lib quadmath : : <link>shared ;
 #
 # Some manual tests that are expensive to run:
 #
-run erf_error_plot.cpp mpfr gmp : : : release <cxxstd>17 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_double ;
+run erf_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_double ;
 explicit erf_error_plot_double ;
-run erf_error_plot.cpp mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE="\"long double\"" [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_long_double ;
+run erf_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE="\"long double\"" [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_long_double ;
 explicit erf_error_plot_long_double ;
-run erf_error_plot.cpp mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE=cpp_bin_float_50 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_cpp_bin_float_50 ;
+run erf_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE=cpp_bin_float_50 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_cpp_bin_float_50 ;
 explicit erf_error_plot_cpp_bin_float_50 ;
-run erf_error_plot.cpp mpfr gmp quadmath : : : release <cxxstd>17 <cxxstd-dialect>gnu <define>TEST_TYPE=float128 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_float128 ;
+run erf_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp quadmath : : : release <cxxstd>17 <cxxstd-dialect>gnu <define>TEST_TYPE=float128 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erf_error_plot_float128 ;
 explicit erf_error_plot_cpp_bin_float_50 ;
-run erfc_error_plot.cpp mpfr gmp : : : release <cxxstd>17 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_double ;
+run erfc_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_double ;
 explicit erfc_error_plot_double ;
-run erfc_error_plot.cpp mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE="\"long double\"" [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_long_double ;
+run erfc_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE="\"long double\"" [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_long_double ;
 explicit erfc_error_plot_long_double ;
-run erfc_error_plot.cpp mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE=cpp_bin_float_50 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_cpp_bin_float_50 ;
+run erfc_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp : : : release <cxxstd>17 <define>TEST_TYPE=cpp_bin_float_50 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_cpp_bin_float_50 ;
 explicit erfc_error_plot_cpp_bin_float_50 ;
-run erfc_error_plot.cpp mpfr gmp quadmath : : : release <cxxstd>17 <cxxstd-dialect>gnu <define>TEST_TYPE=float128 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_float128 ;
+run erfc_error_plot.cpp /boost/multiprecision//boost_multiprecision mpfr gmp quadmath : : : release <cxxstd>17 <cxxstd-dialect>gnu <define>TEST_TYPE=float128 [ check-target-builds ../../config//has_mpfr : : <build>no ] : erfc_error_plot_float128 ;
 explicit erfc_error_plot_cpp_bin_float_50 ;
diff --git a/reporting/performance/Jamfile.v2 b/reporting/performance/Jamfile.v2
index 1f1d6fd639..0a960e9236 100644
--- a/reporting/performance/Jamfile.v2
+++ b/reporting/performance/Jamfile.v2
@@ -12,11 +12,13 @@ import testing ;
 import modules ;
 import path ;
 import pch ;
-import ../../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 using quickbook ;
 using auto-index ;
 
-import ../../../predef/tools/check/predef
+import-search /boost/predef/tools/check ;
+import predef
     : check require
     : predef-check predef-require ;
 
@@ -39,9 +41,9 @@ if $(is_unix)
 #
 # Configuration first:
 #
-lib gsl ;
-lib gslcblas ;
-lib Rmath ;
+searched-lib gsl ;
+searched-lib gslcblas ;
+searched-lib Rmath ;
 obj has_libstdcxx_tr1 : ../accuracy/has_libstdcxx_tr1.cpp ;
 explicit has_libstdcxx_tr1 ;
 obj has_c99_cmath : has_c99_cmath.cpp ;
@@ -53,16 +55,16 @@ explicit has_rmath ;
 obj is_intel_win : is_intel_win.cpp ;
 explicit is_intel_win ;
 
-CEPHES_SOURCE = acosh.c airy.c asin.c asinh.c atan.c atanh.c bdtr.c beta.c 
-btdtr.c cbrt.c chbevl.c chdtr.c clog.c cmplx.c const.c 
-cosh.c dawsn.c drand.c ei.c ellie.c ellik.c ellpe.c ellpj.c ellpk.c 
-exp.c exp10.c exp2.c expn.c expx2.c fabs.c fac.c fdtr.c 
-fresnl.c gamma.c gdtr.c hyp2f1.c hyperg.c i0.c i1.c igami.c incbet.c 
-incbi.c igam.c isnan.c iv.c j0.c j1.c jn.c jv.c k0.c k1.c kn.c kolmogorov.c 
-log.c log2.c log10.c lrand.c nbdtr.c ndtr.c ndtri.c pdtr.c planck.c 
-polevl.c polmisc.c polylog.c polyn.c pow.c powi.c psi.c rgamma.c round.c 
-shichi.c sici.c sin.c sindg.c sinh.c spence.c stdtr.c struve.c 
-tan.c tandg.c tanh.c unity.c yn.c zeta.c zetac.c 
+CEPHES_SOURCE = acosh.c airy.c asin.c asinh.c atan.c atanh.c bdtr.c beta.c
+btdtr.c cbrt.c chbevl.c chdtr.c clog.c cmplx.c const.c
+cosh.c dawsn.c drand.c ei.c ellie.c ellik.c ellpe.c ellpj.c ellpk.c
+exp.c exp10.c exp2.c expn.c expx2.c fabs.c fac.c fdtr.c
+fresnl.c gamma.c gdtr.c hyp2f1.c hyperg.c i0.c i1.c igami.c incbet.c
+incbi.c igam.c isnan.c iv.c j0.c j1.c jn.c jv.c k0.c k1.c kn.c kolmogorov.c
+log.c log2.c log10.c lrand.c nbdtr.c ndtr.c ndtri.c pdtr.c planck.c
+polevl.c polmisc.c polylog.c polyn.c pow.c powi.c psi.c rgamma.c round.c
+shichi.c sici.c sin.c sindg.c sinh.c spence.c stdtr.c struve.c
+tan.c tandg.c tanh.c unity.c yn.c zeta.c zetac.c
 sqrt.c floor.c setprec.c mtherr.c ;
 
 DCDFLIB_SOURCE = dcdflib.c ipmpar.c ;
@@ -78,33 +80,33 @@ explicit $(here)/third_party/cephes_double/acosh.c ;
 explicit $(here)/third_party/dcdflib/dcdflib.c ;
 
 lib cephes_double : $(here)/third_party/cephes_double/$(CEPHES_SOURCE)
-    :         
+    :
         release
         <link>static
-        [ check-target-builds $(here)/third_party/cephes_double/acosh.c : : <build>no ] 
+        [ check-target-builds $(here)/third_party/cephes_double/acosh.c : : <build>no ]
    ;
 
 explicit cephes_double ;
 
 lib dcdflib : $(here)/third_party/dcdflib/$(DCDFLIB_SOURCE)
-    :         
+    :
         release
         <link>static
-        [ check-target-builds $(here)/third_party/dcdflib/dcdflib.c : : <build>no ] 
+        [ check-target-builds $(here)/third_party/dcdflib/dcdflib.c : : <build>no ]
    ;
 
 explicit dcdflib ;
 
-obj table_helper : table_helper.cpp ;
+obj table_helper : table_helper.cpp /boost/filesystem//boost_filesystem /boost/interprocess//boost_interprocess ;
 
 rule all-tests {
      local result ;
      for local source in [ glob test*.cpp ]
      {
-        result += [ run $(source) /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
-        : : : release <include>../../test 
-        [ check-target-builds ../accuracy//has_c99_cmath : <define>TEST_C99 ] 
-        [ check-target-builds has_libstdcxx_tr1 : <define>TEST_LIBSTDCXX ] 
+        result += [ run $(source) /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem /boost/multiprecision//boost_multiprecision /boost/filesystem//boost_filesystem table_helper
+        : : : <variant>release <include>../../test
+        [ check-target-builds ../accuracy//has_c99_cmath : <define>TEST_C99 ]
+        [ check-target-builds has_libstdcxx_tr1 : <define>TEST_LIBSTDCXX ]
         [ check-target-builds ../accuracy//has_gsl : <define>TEST_GSL <source>gsl <source>gslcblas ]
         [ check-target-builds ../accuracy//has_rmath : <define>TEST_RMATH <source>Rmath ]
        # [ check-target-builds is_intel_win : <build>no : ]
@@ -113,46 +115,46 @@ rule all-tests {
         #<toolset>msvc:<address-model>64
         ] ;
      }
-     return $(result) ;     
+     return $(result) ;
 }
-            
+
 #
 # Special cases to test different compiler options,
 # cbrt first as an example of a trivial function:
 #
-run test_cbrt.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_cbrt.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
      : : : debug <define>COMPILER_COMPARISON_TABLES [ predef-require "BOOST_COMP_MSVC" ] <address-model>32 : test_cbrt_msvc_debug ;
-run test_cbrt.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_cbrt.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
      : : : release <define>COMPILER_COMPARISON_TABLES [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>32 : test_cbrt_msvc_release_32 ;
-run test_cbrt.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_cbrt.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
      : : : release <define>COMPILER_COMPARISON_TABLES [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>64 : test_cbrt_msvc_release_64 ;
-run test_cbrt.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_cbrt.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
      : : : release <define>COMPILER_COMPARISON_TABLES [ check-target-builds is_intel_win : : <build>no ] <toolset>intel:<cxxflags>-Ox <address-model>64 : test_cbrt_intel_release ;
 #
 # Now jn as a little more complex:
 #
-run test_jn.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_jn.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : debug <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <address-model>32 : test_jn_msvc_debug ;
-run test_jn.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_jn.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>32 : test_jn_msvc_release_32 ;
-run test_jn.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_jn.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>64 : test_jn_msvc_release_64 ;
-run test_jn.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_jn.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ check-target-builds is_intel_win : : <build>no ] <address-model>64 : test_jn_intel_release ;
 #
 # Then something really expensive, like the inverse-incomplete-beta:
 #
-run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : debug <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <address-model>32 : test_ibeta_inv_msvc_debug ;
-run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>32 : test_ibeta_inv_msvc_release_32 ;
-run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ predef-require "BOOST_COMP_MSVC" ] <cxxflags>-Ox <address-model>64 : test_ibeta_inv_msvc_release_64 ;
-run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system /boost/chrono /boost/filesystem table_helper
+run test_ibeta_inv.cpp /boost/regex//boost_regex /boost/system//boost_system /boost/chrono//boost_chrono /boost/filesystem//boost_filesystem table_helper
    : : : release <define>COMPILER_COMPARISON_TABLES <include>../../test [ check-target-builds is_intel_win : : <build>no ] <toolset>intel:<cxxflags>-Ox <address-model>64 : test_ibeta_inv_intel_release ;
 
-test-suite report_gen : [ all-tests ] test_cbrt_msvc_debug test_cbrt_msvc_release_32 test_cbrt_msvc_release_64 test_cbrt_intel_release 
-   test_jn_msvc_debug test_jn_msvc_release_32 test_jn_msvc_release_64 test_jn_intel_release test_ibeta_inv_msvc_debug 
+test-suite report_gen : [ all-tests ] test_cbrt_msvc_debug test_cbrt_msvc_release_32 test_cbrt_msvc_release_64 test_cbrt_intel_release
+   test_jn_msvc_debug test_jn_msvc_release_32 test_jn_msvc_release_64 test_jn_intel_release test_ibeta_inv_msvc_debug
    test_ibeta_inv_msvc_release_32 test_ibeta_inv_msvc_release_64 test_ibeta_inv_intel_release ;
 
 path-constant images_location : html ;
@@ -165,7 +167,7 @@ boostbook standalone
     :
         # Path for links to Boost:
         <xsl:param>boost.root=../../../../..
-        
+
         # Some general style settings:
         <xsl:param>table.footnote.number.format=1
         <xsl:param>footnote.number.format=1
diff --git a/test/Jamfile.v2 b/test/Jamfile.v2
index 85ddf38f9b..e6814fd867 100644
--- a/test/Jamfile.v2
+++ b/test/Jamfile.v2
@@ -12,7 +12,8 @@ import testing ;
 import modules ;
 import path ;
 import pch ;
-import ../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 
 local ntl-path = [ modules.peek : NTL_PATH ] ;
 local gmp_path = [ modules.peek : GMP_PATH ] ;
@@ -29,11 +30,16 @@ if $(remove-test-targets)
    OBJ_REMOVAL_OPTIONS = <pch>off ;
 }
 
-obj no_eh : noeh_support.cpp ;
+obj no_eh : noeh_support.cpp : <library>/boost/config//boost_config ;
 
 
 project
     : requirements
+      <library>/boost/math//boost_math
+      <library>/boost/multiprecision//boost_multiprecision
+      <library>/boost/test//included
+      <library>/boost/type_index//boost_type_index
+      <library>/boost/ublas//boost_ublas
       $(OBJ_REMOVAL_OPTIONS)
       <toolset>acc:<cxxflags>+W2068,2461,2236,4070,4069
       <toolset>intel-win:<cxxflags>-nologo
@@ -59,7 +65,6 @@ project
       <toolset>borland:<runtime-link>static
       # <toolset>msvc:<cxxflags>/wd4506 has no effect?
       # suppress xstring(237) : warning C4506: no definition for inline function
-      <include>../../..
       <exception-handling>off:<source>no_eh
       <link>shared:<define>BOOST_REGEX_DYN_LINK=1
       # For simplicities sake, make everything a static lib:
@@ -84,178 +89,191 @@ if $(ntl-path)
 }
 else
 {
-   lib ntl ;
+   searched-lib ntl ;
 }
 
 explicit ntl ;
 
-cpp-pch pch : pch.hpp : <use>../../test/build//boost_unit_test_framework ;
-cpp-pch pch_light : pch_light.hpp : <use>../../test/build//boost_unit_test_framework ;
+cpp-pch pch : pch.hpp : <use>/boost/test//boost_unit_test_framework ;
+cpp-pch pch_light : pch_light.hpp : <use>/boost/test//boost_unit_test_framework ;
 lib compile_test_main : compile_test/main.cpp ;
 
+searched-lib quadmath ;
+
+local float128_type_intel_quad =
+    [ check-target-builds ../config//has_intel_quad "Intel _Quad datatype support"
+        : <cxxflags>-Qoption,cpp,--extended_float_type <define>BOOST_MATH_USE_FLOAT128 ] ;
+local float128_type_gcc =
+    [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support"
+        : <toolset>gcc:<library>quadmath <toolset>gcc:<define>BOOST_MATH_TEST_FLOAT128 ] ;
+local float128_type_floatmax =
+    [ check-target-builds ../config//has_128bit_floatmax_t "128-bit floatmax_t" : : <build>no ] ;
+local float128_type =
+    $(float128_type_intel_quad) $(float128_type_gcc) $(float128_type_floatmax) ;
+
 test-suite special_fun :
-   [ run test_1F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 : test_1F0_1 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
-   [ run test_1F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 : test_1F0_2 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
-   [ run test_1F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 : test_1F0_3 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
-   [ run test_2F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <define>TEST=1 : test_2F0_1 ]
-   [ run test_2F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <define>TEST=2 : test_2F0_2 ]
-   [ run test_2F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <define>TEST=3 : test_2F0_3 ]
-   [ run test_2F0.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <define>TEST=4 : test_2F0_4 ]
+   [ run test_1F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 : test_1F0_1 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
+   [ run test_1F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 : test_1F0_2 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
+   [ run test_1F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 : test_1F0_3 ] # hypergeometric_pFq_checked_series.hpp uses auto, the rest are from quadrature tests.
+   [ run test_2F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] $(float128_type) <define>TEST=1 : test_2F0_1 ]
+   [ run test_2F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] $(float128_type) <define>TEST=2 : test_2F0_2 ]
+   [ run test_2F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] $(float128_type) <define>TEST=3 : test_2F0_3 ]
+   [ run test_2F0.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] $(float128_type) <define>TEST=4 : test_2F0_4 ]
 
-   [ run test_0F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 : test_0F1_1 ]
-   [ run test_0F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 : test_0F1_2 ]
+   [ run test_0F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 : test_0F1_1 ]
+   [ run test_0F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 : test_0F1_2 ]
 
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_integrals ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_float ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_double ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_long_double ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=1 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_integrals ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_float ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_double ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_long_double ]
 
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_float ]
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_double ]
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_long_double ]
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_real_concept ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_float ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_double ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_long_double ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_real_concept ]
    #  These are slow...
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_float ]
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_double ]
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_long_double ]
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_real_concept ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_float ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_double ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_long_double ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_log_real_concept ]
    # pFq:
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_float ]
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_double ]
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_long_double ]
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_real_concept ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=2 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_float ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_double ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_long_double ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 release <toolset>clang:<cxxflags>-Wno-literal-range : test_pFq_real_concept ]
 
 
-   [ run hypot_test.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework ]
-   [ run pow_test.cpp ../../test/build//boost_unit_test_framework ]
-   [ run logaddexp_test.cpp ../../test/build//boost_unit_test_framework ]
-   [ run logsumexp_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_variadic_templates ] ]
-   [ run ccmath_sqrt_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isinf_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isnan_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_abs_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isfinite_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isnormal_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fpclassify_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_frexp_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_ldexp_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_div_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_logb_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_ilogb_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_scalbn_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_scalbln_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_floor_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_ceil_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_trunc_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_modf_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_round_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fmod_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_remainder_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_copysign_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_hypot_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fdim_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fmax_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fmin_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isgreater_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isgreaterequal_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isless_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_islessequal_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_isunordered_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_next_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_fma_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run ccmath_signbit_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run log1p_expm1_test.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run powm1_sqrtp1m1_test.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run git_issue_705.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run git_issue_810.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run git_issue_826.cpp ../../test/build//boost_unit_test_framework  ]
+   [ run hypot_test.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework ]
+   [ run pow_test.cpp /boost/test//boost_unit_test_framework ]
+   [ run logaddexp_test.cpp /boost/test//boost_unit_test_framework ]
+   [ run logsumexp_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_variadic_templates ] ]
+   [ run ccmath_sqrt_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isinf_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isnan_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_abs_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isfinite_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isnormal_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fpclassify_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_frexp_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_ldexp_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_div_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_logb_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_ilogb_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_scalbn_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_scalbln_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_floor_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_ceil_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_trunc_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_modf_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_round_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fmod_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_remainder_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_copysign_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_hypot_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fdim_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fmax_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fmin_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isgreater_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isgreaterequal_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isless_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_islessequal_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_isunordered_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_next_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_fma_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run ccmath_signbit_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr ] $(float128_type) ]
+   [ run log1p_expm1_test.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run powm1_sqrtp1m1_test.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run git_issue_705.cpp /boost/test//boost_unit_test_framework  ]
+   [ run git_issue_810.cpp /boost/test//boost_unit_test_framework  ]
+   [ run git_issue_826.cpp /boost/test//boost_unit_test_framework  ]
    [ run git_issue_961.cpp ]
    [ run git_issue_1006.cpp ]
    [ run git_issue_184.cpp ]
    [ run git_issue_1137.cpp ]
    [ run git_issue_1139.cpp ]
-   [ run special_functions_test.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_airy.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_j.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_y.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_i.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_k.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_j_prime.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_y_prime.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_i_prime.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_k_prime.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run bessel_iterator_test.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_beta.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_bessel_airy_zeros.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_bernoulli_constants.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_binomial_coeff.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_carlson.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run special_functions_test.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_airy.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_j.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_y.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_i.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_k.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_j_prime.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_y_prime.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_i_prime.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_k_prime.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run bessel_iterator_test.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_beta.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_bessel_airy_zeros.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_bernoulli_constants.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_binomial_coeff.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_carlson.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
         <define>TEST1
         : test_carlson_1  ]
-   [ run test_carlson.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_carlson.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
         <define>TEST2
       : test_carlson_2  ]
-   [ run test_carlson.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_carlson.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
         <define>TEST3
         : test_carlson_3  ]
-   [ run test_carlson.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_carlson.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
         <define>TEST4
         : test_carlson_4  ]
-   [ run test_cbrt.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_difference.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_digamma.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_ellint_1.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_ellint_2.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_ellint_3.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_ellint_d.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_jacobi_theta.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] ]
-   [ run test_jacobi_zeta.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_heuman_lambda.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_erf.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
+   [ run test_cbrt.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_difference.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_digamma.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_ellint_1.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_ellint_2.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_ellint_3.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_ellint_d.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_jacobi_theta.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] ]
+   [ run test_jacobi_zeta.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_heuman_lambda.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_erf.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
    [ run erf_limits_test.cpp ]
-   [ run test_expint.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_factorials.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_gamma.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
+   [ run test_expint.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_factorials.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_gamma.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
    [ run test_gamma_edge.cpp ]
-   [ run test_gamma_mp.cpp ../../test/build//boost_unit_test_framework : : : release <define>TEST=1 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :  test_gamma_mp_1 ]
-   [ run test_gamma_mp.cpp ../../test/build//boost_unit_test_framework : : : release <define>TEST=2 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_gamma_mp_2 ]
-   [ run test_gamma_mp.cpp ../../test/build//boost_unit_test_framework : : : release <define>TEST=3 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_gamma_mp_3 ]
-   [ run test_hankel.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_hermite.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_gamma_mp.cpp /boost/test//boost_unit_test_framework : : : release <define>TEST=1 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :  test_gamma_mp_1 ]
+   [ run test_gamma_mp.cpp /boost/test//boost_unit_test_framework : : : release <define>TEST=2 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_gamma_mp_2 ]
+   [ run test_gamma_mp.cpp /boost/test//boost_unit_test_framework : : : release <define>TEST=3 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_gamma_mp_3 ]
+   [ run test_hankel.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_hermite.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_ibeta_float  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_double  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_long_double  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -263,7 +281,7 @@ test-suite special_fun :
           <define>TEST_DATA=1
           <toolset>intel:<pch>off
         : test_ibeta_real_concept1  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -271,7 +289,7 @@ test-suite special_fun :
           <define>TEST_DATA=2
           <toolset>intel:<pch>off
         : test_ibeta_real_concept2  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -279,7 +297,7 @@ test-suite special_fun :
           <define>TEST_DATA=3
           <toolset>intel:<pch>off
         : test_ibeta_real_concept3  ]
-   [ run test_ibeta.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -288,7 +306,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
         : test_ibeta_real_concept4  ]
 
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -296,7 +314,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_float  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -304,7 +322,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_double  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -312,7 +330,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_long_double  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -321,7 +339,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_real_concept1  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -330,7 +348,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_real_concept2  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -339,7 +357,7 @@ test-suite special_fun :
           <toolset>intel:<pch>off
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_real_concept3  ]
-   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_derivative.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -349,28 +367,28 @@ test-suite special_fun :
           <toolset>gcc:<cxxflags>-Wno-overflow
         : test_ibeta_derivative_real_concept4  ]
 
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_ibeta_inv_float  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_inv_double  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_inv_long_double  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -378,7 +396,7 @@ test-suite special_fun :
           <define>TEST_DATA=1
           <toolset>intel:<pch>off
         : test_ibeta_inv_real_concept1  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -386,7 +404,7 @@ test-suite special_fun :
           <define>TEST_DATA=2
           <toolset>intel:<pch>off
         : test_ibeta_inv_real_concept2  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -394,7 +412,7 @@ test-suite special_fun :
           <define>TEST_DATA=3
           <toolset>intel:<pch>off
         : test_ibeta_inv_real_concept3  ]
-   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -402,28 +420,28 @@ test-suite special_fun :
           <define>TEST_DATA=4
           <toolset>intel:<pch>off
         : test_ibeta_inv_real_concept4  ]
-   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_float  ]
-   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_double  ]
-   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_long_double  ]
-   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -431,7 +449,7 @@ test-suite special_fun :
           <define>TEST_DATA=1
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_real_concept1  ]
-   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -439,7 +457,7 @@ test-suite special_fun :
           <define>TEST_DATA=2
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_real_concept2  ]
-   [ run test_ibeta_inv_ab.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_ibeta_inv_ab.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -447,57 +465,57 @@ test-suite special_fun :
           <define>TEST_DATA=3
           <toolset>intel:<pch>off
         : test_ibeta_inv_ab_real_concept3  ]
-   [ run test_igamma.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_igamma_inv.cpp test_instances//test_instances pch_light  ../../test/build//boost_unit_test_framework
+   [ run test_igamma.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_igamma_inv.cpp test_instances//test_instances pch_light  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_igamma_inv_float  ]
-   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_igamma_inv_double  ]
-   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_igamma_inv_long_double  ]
-   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inv.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_REAL_CONCEPT
           <toolset>intel:<pch>off
         : test_igamma_inv_real_concept  ]
-   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_igamma_inva_float  ]
-   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_igamma_inva_double  ]
-   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
       : test_igamma_inva_long_double  ]
-   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework
+   [ run test_igamma_inva.cpp  test_instances//test_instances pch_light /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -507,23 +525,23 @@ test-suite special_fun :
    [ run test_instantiate1.cpp test_instantiate2.cpp  ]
    [ run test_instantiate1.cpp test_instantiate2.cpp  : : : <exception-handling>off : test_instantiate_no_eh ]
    [ run test_instantiate3.cpp ]
-   [ run test_jacobi.cpp pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_laguerre.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
+   [ run test_jacobi.cpp pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_laguerre.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
 
-   [ run test_lambert_w.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_lambert_w.cpp ../../test/build//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=1  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_1 ]
-   [ run test_lambert_w.cpp ../../test/build//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=2  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_2 ]
-   [ run test_lambert_w.cpp ../../test/build//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=3  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_3 ]
-   [ run test_lambert_w.cpp ../../test/build//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=4 <define>BOOST_MATH_TEST_FLOAT128 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_4 ]
-   [ run test_lambert_w_integrals_float128.cpp ../../test/build//boost_unit_test_framework : : : release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" : <build>no ] [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
-   [ run test_lambert_w_integrals_quad.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
-   [ run test_lambert_w_integrals_long_double.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
-   [ run test_lambert_w_integrals_double.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
-   [ run test_lambert_w_integrals_float.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
-   [ run test_lambert_w_derivative.cpp ../../test/build//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ]  ]
+   [ run test_lambert_w.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_lambert_w.cpp /boost/test//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=1  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_1 ]
+   [ run test_lambert_w.cpp /boost/test//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=2  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_2 ]
+   [ run test_lambert_w.cpp /boost/test//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=3  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_3 ]
+   [ run test_lambert_w.cpp /boost/test//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION=4 <define>BOOST_MATH_TEST_FLOAT128 $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_lambert_w_multiprecision_4 ]
+   [ run test_lambert_w_integrals_float128.cpp /boost/test//boost_unit_test_framework : : : release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" : <build>no ] [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
+   [ run test_lambert_w_integrals_quad.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
+   [ run test_lambert_w_integrals_long_double.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
+   [ run test_lambert_w_integrals_double.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
+   [ run test_lambert_w_integrals_float.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] ]
+   [ run test_lambert_w_derivative.cpp /boost/test//boost_unit_test_framework : : : <define>BOOST_MATH_TEST_MULTIPRECISION  $(float128_type)  ]
 
-   [ run test_legendre.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ]  ]
-   [ run chebyshev_test.cpp  : : : [ requires cxx11_inline_namespaces cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_range_based_for cxx11_constexpr ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ]  ]
+   [ run test_legendre.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework : : : $(float128_type)  ]
+   [ run chebyshev_test.cpp  : : : [ requires cxx11_inline_namespaces cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_range_based_for cxx11_constexpr ] $(float128_type)  ]
    [ run chebyshev_transform_test.cpp ../config//fftw3f : : : <define>TEST1 [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_range_based_for ] [ check-target-builds ../config//has_fftw3 "libfftw3" : : <build>no ] : chebyshev_transform_test_1 ]
    [ run chebyshev_transform_test.cpp ../config//fftw3 : : : <define>TEST2 [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_range_based_for ] [ check-target-builds ../config//has_fftw3 "libfftw3" : : <build>no ] : chebyshev_transform_test_2 ]
    [ run chebyshev_transform_test.cpp ../config//fftw3l : : : <define>TEST3 [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_range_based_for ] [ check-target-builds ../config//has_fftw3 "libfftw3" : : <build>no ] : chebyshev_transform_test_3 ]
@@ -535,56 +553,56 @@ test-suite special_fun :
    [ run cardinal_trigonometric_test.cpp ../config//fftw3q ../config//quadmath : : : <define>TEST4 [ requires cxx11_auto_declarations cxx11_range_based_for ] [ check-target-builds ../config//has_fftw3 "libfftw3" : : <build>no ] [ check-target-builds ../config//has_float128 "__float128" : : <build>no ] : cardinal_trigonometric_test_4 ]
 
 
-   [ run test_ldouble_simple.cpp ../../test/build//boost_unit_test_framework  ]
+   [ run test_ldouble_simple.cpp /boost/test//boost_unit_test_framework  ]
    # Needs to run in release mode, as it's rather slow:
-   [ run test_next.cpp pch ../../test/build//boost_unit_test_framework : : : release  ]
-   [ run test_next_decimal.cpp pch ../../test/build//boost_unit_test_framework : : : release  ]
-   [ run test_owens_t.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_polygamma.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_trigamma.cpp test_instances//test_instances ../../test/build//boost_unit_test_framework  ]
-   [ run test_round.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run git_issue_430.cpp pch ../../test/build//boost_unit_test_framework ]
-   [ run test_spherical_harmonic.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_sign.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_tgamma_for_issue396_part1.cpp ../../test/build//boost_unit_test_framework : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
-   [ run test_tgamma_for_issue396_part2.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ]  ]
-   [ run test_tgamma_ratio.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_trig.cpp test_instances//test_instances pch_light ../../test/build//boost_unit_test_framework  ]
-   [ run test_zeta.cpp ../../test/build//boost_unit_test_framework test_instances//test_instances pch_light  ]
-   [ run test_sinc.cpp ../../test/build//boost_unit_test_framework pch_light ]
-   [ run test_fibonacci.cpp ../../test/build//boost_unit_test_framework ]
+   [ run test_next.cpp pch /boost/test//boost_unit_test_framework : : : release  ]
+   [ run test_next_decimal.cpp pch /boost/test//boost_unit_test_framework : : : release  ]
+   [ run test_owens_t.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_polygamma.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_trigamma.cpp test_instances//test_instances /boost/test//boost_unit_test_framework  ]
+   [ run test_round.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run git_issue_430.cpp pch /boost/test//boost_unit_test_framework ]
+   [ run test_spherical_harmonic.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_sign.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_tgamma_for_issue396_part1.cpp /boost/test//boost_unit_test_framework : : : $(float128_type) <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
+   [ run test_tgamma_for_issue396_part2.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ]  ]
+   [ run test_tgamma_ratio.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_trig.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
+   [ run test_zeta.cpp /boost/test//boost_unit_test_framework test_instances//test_instances pch_light  ]
+   [ run test_sinc.cpp /boost/test//boost_unit_test_framework pch_light ]
+   [ run test_fibonacci.cpp /boost/test//boost_unit_test_framework ]
 ;
 
 test-suite distribution_tests :
-   [ run test_arcsine.cpp pch ../../test/build//boost_unit_test_framework  ]
+   [ run test_arcsine.cpp pch /boost/test//boost_unit_test_framework  ]
    [ run test_landau.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
    [ run test_saspoint5.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
    [ run test_holtsmark.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
    [ run test_mapairy.cpp pch : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run test_bernoulli.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_beta_dist.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_bernoulli.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_beta_dist.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_binomial_float  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_binomial_double  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_binomial_long_double  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -592,7 +610,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=0
           <toolset>intel:<pch>off
         : test_binomial_real_concept0  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -600,7 +618,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=1
           <toolset>intel:<pch>off
         : test_binomial_real_concept1  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -608,7 +626,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=2
           <toolset>intel:<pch>off
         : test_binomial_real_concept2  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -616,7 +634,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=3
           <toolset>intel:<pch>off
         : test_binomial_real_concept3  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -624,7 +642,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=4
           <toolset>intel:<pch>off
         : test_binomial_real_concept4  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -632,7 +650,7 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=5
           <toolset>intel:<pch>off
         : test_binomial_real_concept5  ]
-   [ run test_binomial.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_binomial.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -640,145 +658,145 @@ test-suite distribution_tests :
           <define>TEST_ROUNDING=6
           <toolset>intel:<pch>off
         : test_binomial_real_concept6  ]
-   [ run test_cauchy.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_chi_squared.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_dist_overloads.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_exponential_dist.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_extreme_value.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_find_location.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_find_scale.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_fisher_f.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_gamma_dist.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_geometric.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_hyperexponential_dist.cpp ../../test/build//boost_unit_test_framework ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_cauchy.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_chi_squared.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_dist_overloads.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_exponential_dist.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_extreme_value.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_find_location.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_find_scale.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_fisher_f.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_gamma_dist.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_geometric.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_hyperexponential_dist.cpp /boost/test//boost_unit_test_framework ]
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=0
           <toolset>intel:<pch>off
         : test_hypergeometric_dist0  ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=1
           <toolset>intel:<pch>off
         : test_hypergeometric_dist1  ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=2
           <toolset>intel:<pch>off
         : test_hypergeometric_dist2  ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=3
           <toolset>intel:<pch>off
         : test_hypergeometric_dist3  ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=4
           <toolset>intel:<pch>off
         : test_hypergeometric_dist4  ]
-   [ run test_hypergeometric_dist.cpp ../../test/build//boost_unit_test_framework
+   [ run test_hypergeometric_dist.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_QUANT=5
           <toolset>intel:<pch>off
         : test_hypergeometric_dist5  ]
-   [ run test_inverse_chi_squared_distribution.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_inverse_gamma_distribution.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_inverse_gaussian.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_kolmogorov_smirnov.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] ]
-   [ run test_laplace.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_inv_hyp.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_logistic_dist.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_lognormal.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_negative_binomial.cpp ../../test/build//boost_unit_test_framework
+   [ run test_inverse_chi_squared_distribution.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_inverse_gamma_distribution.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_inverse_gaussian.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_kolmogorov_smirnov.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] ]
+   [ run test_laplace.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_inv_hyp.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_logistic_dist.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_lognormal.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_negative_binomial.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_negative_binomial_float  ]
-   [ run test_negative_binomial.cpp ../../test/build//boost_unit_test_framework
+   [ run test_negative_binomial.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_negative_binomial_double  ]
-   [ run test_negative_binomial.cpp ../../test/build//boost_unit_test_framework
+   [ run test_negative_binomial.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_negative_binomial_long_double  ]
-   [ run test_negative_binomial.cpp ../../test/build//boost_unit_test_framework
+   [ run test_negative_binomial.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_REAL_CONCEPT
           <toolset>intel:<pch>off
         : test_negative_binomial_real_concept  ]
-   [ run test_nc_chi_squared.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_chi_squared.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_nc_chi_squared_float  ]
-   [ run test_nc_chi_squared.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_chi_squared.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_nc_chi_squared_double  ]
-   [ run test_nc_chi_squared.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_chi_squared.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_nc_chi_squared_long_double  ]
-   [ run test_nc_chi_squared.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_chi_squared.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_REAL_CONCEPT
           <toolset>intel:<pch>off
         : test_nc_chi_squared_real_concept  ]
-   [ run test_nc_beta.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_nc_beta.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_nc_beta_float  ]
-   [ run test_nc_beta.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_nc_beta.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_nc_beta_double  ]
-   [ run test_nc_beta.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_nc_beta.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_nc_beta_long_double  ]
-   [ run test_nc_beta.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_nc_beta.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -786,7 +804,7 @@ test-suite distribution_tests :
           <define>TEST_DATA=1
           <toolset>intel:<pch>off
         : test_nc_beta_real_concept1  ]
-   [ run test_nc_beta.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_nc_beta.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
@@ -794,109 +812,109 @@ test-suite distribution_tests :
           <define>TEST_DATA=2
           <toolset>intel:<pch>off
         : test_nc_beta_real_concept2  ]
-   [ run test_nc_f.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_nc_t.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_f.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_nc_t.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_nc_t_float  ]
-   [ run test_nc_t.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_t.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_nc_t_double  ]
-   [ run test_nc_t.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_t.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_nc_t_long_double  ]
-   [ run test_nc_t.cpp  pch ../../test/build//boost_unit_test_framework
+   [ run test_nc_t.cpp  pch /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_REAL_CONCEPT
           <toolset>intel:<pch>off
         : test_nc_t_real_concept  ]
-   [ run test_normal.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_pareto.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_poisson.cpp ../../test/build//boost_unit_test_framework
+   [ run test_normal.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_pareto.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_poisson.cpp /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_FLOAT
           <toolset>intel:<pch>off
         : test_poisson_float  ]
-   [ run test_poisson.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_poisson.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_DOUBLE
           <toolset>intel:<pch>off
         : test_poisson_double  ]
-   [ run test_poisson.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_poisson.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_LDOUBLE
           <toolset>intel:<pch>off
         : test_poisson_long_double  ]
-   [ run test_poisson.cpp  ../../test/build//boost_unit_test_framework
+   [ run test_poisson.cpp  /boost/test//boost_unit_test_framework
         : # command line
         : # input files
         : # requirements
           <define>TEST_REAL_CONCEPT
           <toolset>intel:<pch>off
         : test_poisson_real_concept  ]
-   [ run test_rayleigh.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_students_t.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_skew_normal.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_triangular.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_uniform.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_weibull.cpp ../../test/build//boost_unit_test_framework  ]
+   [ run test_rayleigh.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_students_t.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_skew_normal.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_triangular.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_uniform.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_weibull.cpp /boost/test//boost_unit_test_framework ]
 
-   [ run test_legacy_nonfinite.cpp ../../test/build//boost_unit_test_framework ]
-   [ run test_basic_nonfinite.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_lexical_cast.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_nonfinite_trap.cpp ../../test/build//boost_unit_test_framework : : : <exception-handling>off:<build>no  ]
-   [ run test_signed_zero.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run complex_test.cpp ../../test/build//boost_unit_test_framework  ]
+   [ run test_legacy_nonfinite.cpp /boost/test//boost_unit_test_framework ]
+   [ run test_basic_nonfinite.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_lexical_cast.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_nonfinite_trap.cpp /boost/test//boost_unit_test_framework : : : <exception-handling>off:<build>no  ]
+   [ run test_signed_zero.cpp /boost/test//boost_unit_test_framework  ]
+   [ run complex_test.cpp /boost/test//boost_unit_test_framework  ]
 
    [ compile test_dist_deduction_guides.cpp : [ requires cpp_deduction_guides cpp_variadic_templates ] ]
-   [ run git_issue_800.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run git_issue_845.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_14901.cpp ../../test/build//boost_unit_test_framework ]
-   [ run scipy_issue_14901_ncf.cpp ../../test/build//boost_unit_test_framework ]
-   [ run scipy_issue_15101.cpp ../../test/build//boost_unit_test_framework ]
-   [ run scipy_issue_17146.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_17388.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_17916.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_17916_nct.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_18302.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run scipy_issue_18511.cpp ../../test/build//boost_unit_test_framework ]
+   [ run git_issue_800.cpp /boost/test//boost_unit_test_framework  ]
+   [ run git_issue_845.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_14901.cpp /boost/test//boost_unit_test_framework ]
+   [ run scipy_issue_14901_ncf.cpp /boost/test//boost_unit_test_framework ]
+   [ run scipy_issue_15101.cpp /boost/test//boost_unit_test_framework ]
+   [ run scipy_issue_17146.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_17388.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_17916.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_17916_nct.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_18302.cpp /boost/test//boost_unit_test_framework  ]
+   [ run scipy_issue_18511.cpp /boost/test//boost_unit_test_framework ]
    [ compile scipy_issue_19762.cpp ]
    [ run git_issue_1120.cpp ]
 ;
 
-test-suite new_floats : 
+test-suite new_floats :
    [ compile compile_test/float32.cpp ]
    [ compile compile_test/float64.cpp ]
    [ compile compile_test/float128.cpp ]
-   [ run test_float_io.cpp : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
-   [ run test_float_io.cpp : : : <define>BOOST_MATH_TEST_IO_AS_INTEL_QUAD=1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] : test_float_io_quad ]
+   [ run test_float_io.cpp : : : $(float128_type) ]
+   [ run test_float_io.cpp : : : <define>BOOST_MATH_TEST_IO_AS_INTEL_QUAD=1 $(float128_type) : test_float_io_quad ]
 ;
 
 test-suite mp :
 
-   [ run test_nc_t_quad.cpp  pch ../../test/build//boost_unit_test_framework : : : release <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run test_polynomial.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST1 : test_polynomial_1  ]
-   [ run test_polynomial.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST2 : test_polynomial_2  ]
-   [ run test_polynomial.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST3 : test_polynomial_3  ]
+   [ run test_nc_t_quad.cpp  pch /boost/test//boost_unit_test_framework : : : release <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
+   [ run test_polynomial.cpp /boost/test//boost_unit_test_framework : : : <define>TEST1 : test_polynomial_1  ]
+   [ run test_polynomial.cpp /boost/test//boost_unit_test_framework : : : <define>TEST2 : test_polynomial_2  ]
+   [ run test_polynomial.cpp /boost/test//boost_unit_test_framework : : : <define>TEST3 : test_polynomial_3  ]
    [ run test_estrin.cpp ]
    [ run polynomial_concept_check.cpp ]
 
@@ -912,13 +930,13 @@ test-suite misc :
    ../build//boost_math_tr1f
    ../build//boost_math_c99
    ../build//boost_math_c99f
-   ../../test/build//boost_unit_test_framework
+   /boost/test//boost_unit_test_framework
      ]
 
    [ run test_tr1.cpp
       ../build//boost_math_tr1l
       ../build//boost_math_c99l
-      ../../test/build//boost_unit_test_framework
+      /boost/test//boost_unit_test_framework
       : : :
       <define>TEST_LD=1
       [ check-target-builds ../config//has_long_double_support "long double support" : : <build>no ]
@@ -931,7 +949,7 @@ test-suite misc :
       ../build//boost_math_tr1f
       ../build//boost_math_c99
       ../build//boost_math_c99f
-      ../../test/build//boost_unit_test_framework
+      /boost/test//boost_unit_test_framework
       : : : #requirements
       :
       test_tr1_c
@@ -940,23 +958,23 @@ test-suite misc :
    [ run test_tr1.c
       ../build//boost_math_tr1l
       ../build//boost_math_c99l
-      ../../test/build//boost_unit_test_framework
+      /boost/test//boost_unit_test_framework
       : : :
       <define>TEST_LD=1
       [ check-target-builds ../config//has_long_double_support "long double support" : : <build>no ]
       :
       test_tr1_c_long_double
     ]
-   [ run test_constants.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run simple_continued_fraction_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run centered_continued_fraction_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run luroth_expansion_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run engel_expansion_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run test_classify.cpp pch ../../test/build//boost_unit_test_framework : : : <toolset>msvc:<cxxflags>/bigobj ]
-   [ run test_error_handling.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run legendre_stieltjes_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_range_based_for ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]  ]
-   [ run test_minima.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_rationals.cpp ../../test/build//boost_unit_test_framework
+   [ run test_constants.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) ]
+   [ run simple_continued_fraction_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) ]
+   [ run centered_continued_fraction_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) ]
+   [ run luroth_expansion_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) ]
+   [ run engel_expansion_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) ]
+   [ run test_classify.cpp pch /boost/test//boost_unit_test_framework : : : <toolset>msvc:<cxxflags>/bigobj ]
+   [ run test_error_handling.cpp /boost/test//boost_unit_test_framework  ]
+   [ run legendre_stieltjes_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_range_based_for ] $(float128_type)  ]
+   [ run test_minima.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_rationals.cpp /boost/test//boost_unit_test_framework
       test_rational_instances/test_rational_double1.cpp
       test_rational_instances/test_rational_double2.cpp
       test_rational_instances/test_rational_double3.cpp
@@ -977,96 +995,96 @@ test-suite misc :
       test_rational_instances/test_rational_real_concept4.cpp
       test_rational_instances/test_rational_real_concept5.cpp
    ]
-   [ run test_policy.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_2.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_3.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_4.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_5.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_6.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_7.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_8.cpp ../../test/build//boost_unit_test_framework  ]
+   [ run test_policy.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_2.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_3.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_4.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_5.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_6.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_7.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_8.cpp /boost/test//boost_unit_test_framework  ]
    [ compile test_policy_9.cpp  ]
-   [ run test_policy_10.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_policy_sf.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_long_double_support.cpp ../../test/build//boost_unit_test_framework
+   [ run test_policy_10.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_policy_sf.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_long_double_support.cpp /boost/test//boost_unit_test_framework
       : : : [ check-target-builds ../config//has_long_double_support "long double support" : : <build>no ] ]
    [ run test_recurrence.cpp : : : <define>TEST=1 [ requires cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_auto_declarations cxx11_decltype ] <toolset>msvc:<cxxflags>/bigobj : test_recurrence_1 ]
-   [ run test_recurrence.cpp : : : <define>TEST=2 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ requires cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_auto_declarations cxx11_decltype ]  : test_recurrence_2 ]
-   [ run test_recurrence.cpp : : : <define>TEST=3 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ requires cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_auto_declarations cxx11_decltype ]  : test_recurrence_3 ]
+   [ run test_recurrence.cpp : : : <define>TEST=2 release $(float128_type) [ requires cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_auto_declarations cxx11_decltype ]  : test_recurrence_2 ]
+   [ run test_recurrence.cpp : : : <define>TEST=3 release $(float128_type) [ requires cxx11_unified_initialization_syntax cxx11_hdr_tuple cxx11_auto_declarations cxx11_decltype ]  : test_recurrence_3 ]
 
    [ run test_print_info_on_type.cpp  ]
-   [ run univariate_statistics_test.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx17_if_constexpr cxx17_std_apply ] ]
-   [ run univariate_statistics_backwards_compatible_test.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ] ]
-   [ run ooura_fourier_integral_test.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ requires cxx17_if_constexpr cxx17_std_apply ] ]
+   [ run univariate_statistics_test.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx17_if_constexpr cxx17_std_apply ] ]
+   [ run univariate_statistics_backwards_compatible_test.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ] ]
+   [ run ooura_fourier_integral_test.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] $(float128_type) [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run empirical_cumulative_distribution_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ] ]
-   [ run norms_test.cpp ../../test/build//boost_unit_test_framework : : :  [ requires cxx17_if_constexpr cxx17_std_apply ] ]
+   [ run norms_test.cpp /boost/test//boost_unit_test_framework : : :  [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run signal_statistics_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run anderson_darling_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run ljung_box_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run cubic_roots_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
    [ run quartic_roots_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
-   [ run test_t_test.cpp : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ]  ]
-   [ run test_z_test.cpp : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ]  ]
+   [ run test_t_test.cpp : : : $(float128_type) [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ]  ]
+   [ run test_z_test.cpp : : : $(float128_type) [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ]  ]
    [ run bivariate_statistics_test.cpp : : : [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
    [ run linear_regression_test.cpp : : : [ requires cxx11_hdr_forward_list cxx11_hdr_atomic cxx11_hdr_thread cxx11_hdr_tuple cxx11_hdr_future cxx11_sfinae_expr ]  ]
    [ run test_runs_test.cpp : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
-   [ run test_chatterjee_correlation.cpp ../../test/build//boost_unit_test_framework ]
-   [ run test_rank.cpp ../../test/build//boost_unit_test_framework ]
-   [ run lanczos_smoothing_test.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
-   [ run condition_number_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=1 <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] : condition_number_test_1 ]
-   [ run condition_number_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=2 <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] : condition_number_test_2 ]
-   [ run condition_number_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=3 <toolset>msvc:<cxxflags>/bigobj [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] : condition_number_test_3 ]
-   [ run test_real_concept.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_remez.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_roots.cpp pch ../../test/build//boost_unit_test_framework  ]
-   [ run test_root_iterations.cpp pch ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_tuple ]  ]
-   [ run test_root_finding_concepts.cpp ../../test/build//boost_unit_test_framework  ]
-   [ run test_toms748_solve.cpp pch ../../test/build//boost_unit_test_framework  ]
+   [ run test_chatterjee_correlation.cpp /boost/test//boost_unit_test_framework ]
+   [ run test_rank.cpp /boost/test//boost_unit_test_framework ]
+   [ run lanczos_smoothing_test.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx17_if_constexpr cxx17_std_apply ] ]
+   [ run condition_number_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=1 <toolset>msvc:<cxxflags>/bigobj $(float128_type) : condition_number_test_1 ]
+   [ run condition_number_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=2 <toolset>msvc:<cxxflags>/bigobj $(float128_type) : condition_number_test_2 ]
+   [ run condition_number_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=3 <toolset>msvc:<cxxflags>/bigobj $(float128_type) : condition_number_test_3 ]
+   [ run test_real_concept.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_remez.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_roots.cpp pch /boost/test//boost_unit_test_framework  ]
+   [ run test_root_iterations.cpp pch /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_tuple ]  ]
+   [ run test_root_finding_concepts.cpp /boost/test//boost_unit_test_framework  ]
+   [ run test_toms748_solve.cpp pch /boost/test//boost_unit_test_framework  ]
    [ run  compile_test/interpolators_cubic_spline_incl_test.cpp compile_test_main : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/interpolators_barycentric_rational_incl_test.cpp compile_test_main : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run octonion_test.cpp
-       ../../test/build//boost_unit_test_framework ]
+       /boost/test//boost_unit_test_framework ]
    [ run octonion_test_simple.cpp ]
    [ run quaternion_constexpr_test.cpp ]
    [ run quaternion_test.cpp
-       ../../test/build//boost_unit_test_framework : : : <toolset>msvc-14.0:<debug-symbols>off [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
+       /boost/test//boost_unit_test_framework : : : <toolset>msvc-14.0:<debug-symbols>off $(float128_type) ]
    [ run quaternion_mult_incl_test.cpp
        quaternion_mi1.cpp
        quaternion_mi2.cpp
-       ../../test/build//boost_unit_test_framework ]
+       /boost/test//boost_unit_test_framework ]
 
 #   [ run __temporary_test.cpp test_instances//test_instances : : : <test-info>always_show_run_output <pch>off ]
 ;
 
 test-suite interpolators :
-   [ run test_barycentric_rational.cpp ../../test/build//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_unified_initialization_syntax ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]  ]
-   [ run test_vector_barycentric_rational.cpp ../../test/build//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_unified_initialization_syntax ]  [ check-target-builds ../../multiprecision/config//has_eigen : : <build>no ] ]
-   [ run cardinal_cubic_b_spline_test.cpp ../../test/build//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release ]
-   [ run cardinal_b_spline_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run jacobi_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run gegenbauer_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run daubechies_scaling_test.cpp  : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
-   [ run daubechies_wavelet_test.cpp  : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
-   [ run fourier_transform_daubechies_test.cpp  : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
-   [ run wavelet_transform_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
-   [ run agm_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run rsqrt_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run cohen_acceleration_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
+   [ run test_barycentric_rational.cpp /boost/test//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_unified_initialization_syntax ] $(float128_type)  ]
+   [ run test_vector_barycentric_rational.cpp /boost/test//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions cxx11_auto_declarations cxx11_unified_initialization_syntax ]  [ check-target-builds ../../multiprecision/config//has_eigen : : <build>no ] ]
+   [ run cardinal_cubic_b_spline_test.cpp /boost/test//boost_unit_test_framework : : :  [ requires cxx11_smart_ptr cxx11_defaulted_functions ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release ]
+   [ run cardinal_b_spline_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] $(float128_type) ]
+   [ run jacobi_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] $(float128_type) ]
+   [ run gegenbauer_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] $(float128_type) ]
+   [ run daubechies_scaling_test.cpp /boost/hana//boost_hana : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
+   [ run daubechies_wavelet_test.cpp /boost/hana//boost_hana : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
+   [ run fourier_transform_daubechies_test.cpp  : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] ]
+   [ run wavelet_transform_test.cpp /boost/hana//boost_hana : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
+   [ run agm_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run rsqrt_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run cohen_acceleration_test.cpp  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
    [ compile compile_test/filters_daubechies_incl_test.cpp : [ requires cxx17_if_constexpr cxx17_std_apply ]  ]
    [ compile compile_test/sf_daubechies_scaling_incl_test.cpp : [ requires cxx17_if_constexpr cxx17_std_apply ]  ]
    [ run whittaker_shannon_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] ]
    [ run cardinal_quadratic_b_spline_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] ]
-   [ run cardinal_quintic_b_spline_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run makima_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run pchip_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run septic_hermite_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run quintic_hermite_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run cubic_hermite_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
+   [ run cardinal_quintic_b_spline_test.cpp : : :  [ requires cxx11_auto_declarations cxx11_constexpr cxx11_smart_ptr cxx11_defaulted_functions ] $(float128_type) ]
+   [ run makima_test.cpp /boost/circular_buffer//boost_circular_buffer : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run pchip_test.cpp /boost/circular_buffer//boost_circular_buffer : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run septic_hermite_test.cpp  : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run quintic_hermite_test.cpp /boost/circular_buffer//boost_circular_buffer : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run cubic_hermite_test.cpp /boost/circular_buffer//boost_circular_buffer : : :  [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
    [ run bilinear_uniform_test.cpp  : : : [ requires cxx17_if_constexpr cxx17_std_apply ]  ]
-   [ run bezier_polynomial_test.cpp  : : : [ requires cxx17_if_constexpr cxx17_std_apply ]  [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] ]
-   [ run catmull_rom_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=1 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_1 ]
-   [ run catmull_rom_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=2 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_2 ]
-   [ run catmull_rom_test.cpp ../../test/build//boost_unit_test_framework : : : <define>TEST=3 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_3 ]
+   [ run bezier_polynomial_test.cpp  : : : [ requires cxx17_if_constexpr cxx17_std_apply ]  $(float128_type) ]
+   [ run catmull_rom_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=1 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_1 ]
+   [ run catmull_rom_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=2 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_2 ]
+   [ run catmull_rom_test.cpp /boost/test//boost_unit_test_framework : : : <define>TEST=3 [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] : catmull_rom_test_3 ]
    [ run compile_test/interpolators_catmull_rom_incl_test.cpp compile_test_main  : : : [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] ]
    [ run compile_test/interpolators_catmull_rom_concept_test.cpp compile_test_main   : : : [ requires cxx11_hdr_array cxx11_hdr_initializer_list ] ]
    [ run test_standalone_asserts.cpp ]
@@ -1080,118 +1098,118 @@ test-suite interpolators :
 ;
 
 test-suite quadrature :
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST1 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] :
    tanh_sinh_quadrature_test_1 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST1A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST1A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] :
    tanh_sinh_quadrature_test_1a ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST1B [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST1B $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] :
    tanh_sinh_quadrature_test_1b ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST2 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST2 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] :
    tanh_sinh_quadrature_test_2 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST2A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST2A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] :
    tanh_sinh_quadrature_test_2a ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST3 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST3 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_3 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST3A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST3A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_3a ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST4 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST4 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_4 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST5 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST5 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_5 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST6 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <toolset>msvc:<cxxflags>/bigobj <define>TEST6 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_6 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST6A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST6A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_6a ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST7 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST7 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_7 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST8 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST8 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_8 ]
-   [ run  tanh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
+   [ run  tanh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
      : : : release <toolset>msvc:<cxxflags>/bigobj <define>TEST9
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax sfinae_expr ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] :
    tanh_sinh_quadrature_test_9 ]
 
    [ run tanh_sinh_mpfr.cpp ../tools//mpfr ../tools//gmp : : : [ check-target-builds ../config//has_mpfr : : <build>no ] [ check-target-builds ../config//has_gmp : : <build>no ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
-   [ run sinh_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <define>TEST1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] : exp_sinh_quadrature_test_1 ]
+   [ run sinh_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release $(float128_type) [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <define>TEST1 $(float128_type) [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] : exp_sinh_quadrature_test_1 ]
 
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST2 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST2 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] : exp_sinh_quadrature_test_2 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : <define>TEST3 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : <define>TEST3 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_3 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST4 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST4 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_4 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST5 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST5 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_5 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST6 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST6 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_6 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST7 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST7 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_7 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST8 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST8 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_8 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST9 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST9 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_9 ]
-   [ run exp_sinh_quadrature_test.cpp ../../test/build//boost_unit_test_framework
-     : : : release <define>TEST10 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run exp_sinh_quadrature_test.cpp /boost/test//boost_unit_test_framework
+     : : : release <define>TEST10 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : exp_sinh_quadrature_test_10 ]
 
-   [ run gauss_quadrature_test.cpp : : : <define>TEST1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_quadrature_test.cpp : : : <define>TEST1 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release : gauss_quadrature_test_1 ]
-   [ run gauss_quadrature_test.cpp : : : <define>TEST2 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_quadrature_test.cpp : : : <define>TEST2 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : gauss_quadrature_test_2 ]
-   [ run gauss_quadrature_test.cpp : : : <define>TEST3 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_quadrature_test.cpp : : : <define>TEST3 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : gauss_quadrature_test_3 ]
-   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST1 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release : gauss_kronrod_quadrature_test_1 ]
-   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST1A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST1A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : gauss_kronrod_quadrature_test_1a ]
-   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST2 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST2 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : gauss_kronrod_quadrature_test_2 ]
-   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST3 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run gauss_kronrod_quadrature_test.cpp : : : <define>TEST3 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : gauss_kronrod_quadrature_test_3 ]
-   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST1 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST1 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release : adaptive_gauss_quadrature_test_1 ]
-   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST1A [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST1A $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : adaptive_gauss_quadrature_test_1a ]
-   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST2 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST2 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : adaptive_gauss_quadrature_test_2 ]
-   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST3 [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
+   [ run adaptive_gauss_kronrod_quadrature_test.cpp : : : <define>TEST3 $(float128_type)
      [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : adaptive_gauss_quadrature_test_3 ]
 
    [ run naive_monte_carlo_test.cpp : : :
@@ -1294,28 +1312,28 @@ test-suite quadrature :
    [ compile compile_test/gauss_concept_test.cpp : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ compile compile_test/gauss_kronrod_concept_test.cpp : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_smart_ptr cxx11_unified_initialization_syntax ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run git_issue_898.cpp ]
-   [ run git_issue_1075.cpp : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
+   [ run git_issue_1075.cpp : : : $(float128_type) ]
 
-   [ run test_trapezoidal.cpp ../../test/build//boost_unit_test_framework : : :
+   [ run test_trapezoidal.cpp /boost/test//boost_unit_test_framework : : :
       release [ requires cxx11_lambdas cxx11_auto_declarations cxx11_decltype cxx11_unified_initialization_syntax cxx11_variadic_templates ]
-      [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>"-Bstatic -lquadmath -Bdynamic" ] ]
+      $(float128_type) ]
 ;
 
 test-suite autodiff :
-   [ run test_numerical_differentiation.cpp ../../test/build//boost_unit_test_framework  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx11_auto_declarations cxx11_constexpr ] ]
+   [ run test_numerical_differentiation.cpp /boost/test//boost_unit_test_framework  : : : <toolset>msvc:<cxxflags>/bigobj [ requires cxx11_auto_declarations cxx11_constexpr ] ]
    [ run  compile_test/diff_numerical_differentiation_incl_test.cpp compile_test_main  : : : [ requires cxx11_auto_declarations cxx11_constexpr ] ]
    [ compile  compile_test/diff_numerical_differentiation_concept_test.cpp  : [ requires cxx11_auto_declarations cxx11_constexpr ] ]
-   [ run test_autodiff_1.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_2.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_3.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_4.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_5.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_6.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_7.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ run test_autodiff_8.cpp ../../test/build//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ check-target-builds ../config//is_ci_standalone_run "Standalone CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ compile compile_test/diff_autodiff_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ compile compile_test/diff_finite_difference_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
-   [ compile compile_test/diff_lanczos_smoothing_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ requires cxx17_if_constexpr cxx17_std_apply ] [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_1.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_2.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_3.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_4.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_5.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_6.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_7.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ run test_autodiff_8.cpp /boost/test//boost_unit_test_framework : : : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ check-target-builds ../config//is_ci_standalone_run "Standalone CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ compile compile_test/diff_autodiff_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ compile compile_test/diff_finite_difference_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
+   [ compile compile_test/diff_lanczos_smoothing_incl_test.cpp : <toolset>gcc-mingw:<cxxflags>-Wa,-mbig-obj <debug-symbols>off <toolset>msvc:<cxxflags>/bigobj release [ requires cxx17_if_constexpr cxx17_std_apply ] $(float128_type) [ check-target-builds ../config//is_cygwin_run "Cygwin CI run" : <build>no ] [ requires cxx11_inline_namespaces ] ]
 ;
 
 #
@@ -1324,18 +1342,18 @@ test-suite autodiff :
 #  too much time:
 #
 test-suite long-running-tests :
-   [ run test_0F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] : test_0F1_3 ]
-   [ run test_0F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release : test_0F1_4 ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_real_concept ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_quad ]
-   [ run test_1F1.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_dec_40 ]
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_quad ]
-   [ run test_1F1_regularized.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_regularized_dec_40 ]
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_log_quad ]
-   [ run test_1F1_log.cpp ../../test/build//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_log_dec_40 ]
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <define>BOOST_MATH_TEST_FLOAT128 <linkflags>"-Bstatic -lquadmath -Bdynamic" ] <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_pFq_quad ]
-   [ run test_pFq.cpp ../../test/build//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_pFq_dec_40 ]
-   [ run test_pFq_precision.cpp ../tools//mpfr ../tools//gmp ../../test/build//boost_unit_test_framework /boost/system//boost_system /boost/chrono//boost_chrono : : : [ check-target-builds ../config//has_mpfr : : <build>no ] [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] release <toolset>clang:<cxxflags>-Wno-literal-range ]
+   [ run test_0F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=3 release $(float128_type) : test_0F1_3 ]
+   [ run test_0F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=4 release : test_0F1_4 ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=5 <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_real_concept ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_quad ]
+   [ run test_1F1.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_dec_40 ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] <toolset>clang:<cxxflags>-Wno-literal-range : test_1F1_regularized_quad ]
+   [ run test_1F1_regularized.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_regularized_dec_40 ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release $(float128_type) <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_log_quad ]
+   [ run test_1F1_log.cpp /boost/test//boost_unit_test_framework : : : release [ requires cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_1F1_log_dec_40 ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=6 release $(float128_type) <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_pFq_quad ]
+   [ run test_pFq.cpp /boost/test//boost_unit_test_framework : : : [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] <define>TEST=7 release <toolset>clang:<cxxflags>-Wno-literal-range [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : test_pFq_dec_40 ]
+   [ run test_pFq_precision.cpp ../tools//mpfr ../tools//gmp /boost/test//boost_unit_test_framework /boost/system//boost_system /boost/chrono//boost_chrono : : : [ check-target-builds ../config//has_mpfr : : <build>no ] [ requires cxx11_hdr_initializer_list cxx11_auto_declarations cxx11_lambdas cxx11_unified_initialization_syntax cxx11_smart_ptr ] release <toolset>clang:<cxxflags>-Wno-literal-range ]
    [ run test_constant_generate.cpp : : : release <define>USE_CPP_FLOAT=1 <exception-handling>off:<build>no  ]
 ;
 
@@ -1353,9 +1371,7 @@ rule get_float128_tests
            : # command line
            : # input files
            : # requirements
-            [ check-target-builds ../config//has_intel_quad "Intel _Quad datatype support" : <cxxflags>-Qoption,cpp,--extended_float_type <define>BOOST_MATH_USE_FLOAT128 ]
-            [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ]
-            [ check-target-builds ../config//has_128bit_floatmax_t "128-bit floatmax_t" : : <build>no ]
+            $(float128_type)
             <define>BOOST_ALL_NO_LIB
            : $(source:B)_floatmax_t ] ;
      }
@@ -1508,7 +1524,7 @@ test-suite concepts :
    [ compile compile_test/std_real_concept_check.cpp  : <define>EMULATE128 [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] : std_real_concept_check_128 ]
    [ run  compile_test/cstdfloat_concept_check_1.cpp
       : : : [ check-target-builds ../config//has_intel_quad "Intel _Quad datatype support" : <cxxflags>-Qoption,cpp,--extended_float_type ]
-            [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
+            $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/cstdfloat_concept_check_2.cpp  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/cstdfloat_concept_check_3.cpp  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/cstdfloat_concept_check_4.cpp  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
@@ -1517,7 +1533,7 @@ test-suite concepts :
    [ compile  compile_test/cstdfloat_iostream_incl_test.cpp : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ compile  compile_test/cstdfloat_limits_incl_test.cpp : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ compile  compile_test/cstdfloat_types_incl_test.cpp : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
-   [ run  test_cstdfloat.cpp ../../test/build//boost_unit_test_framework  : : : [ check-target-builds ../config//has_float128 "GCC libquadmath and __float128 support" : <linkflags>-lquadmath ] [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
+   [ run  test_cstdfloat.cpp /boost/test//boost_unit_test_framework  : : : $(float128_type) [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/sf_airy_incl_test.cpp compile_test_main  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/sf_hankel_incl_test.cpp compile_test_main  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
    [ run  compile_test/sf_jacobi_incl_test.cpp compile_test_main  : : : [ check-target-builds ../config//is_ci_sanitizer_run "Sanitizer CI run" : <build>no ] ]
diff --git a/test/float128/log1p_expm1_test.cpp b/test/float128/log1p_expm1_test.cpp
index 7948614403..c46d5b099a 100644
--- a/test/float128/log1p_expm1_test.cpp
+++ b/test/float128/log1p_expm1_test.cpp
@@ -14,7 +14,7 @@
 
 #include "table_type.hpp"
 
-#include "libs/math/test/log1p_expm1_test.hpp"
+#include "log1p_expm1_test.hpp"
 
 //
 // DESCRIPTION:
diff --git a/test/float128/powm1_sqrtp1m1_test.cpp b/test/float128/powm1_sqrtp1m1_test.cpp
index 73972bb7a0..bfc219bcc6 100644
--- a/test/float128/powm1_sqrtp1m1_test.cpp
+++ b/test/float128/powm1_sqrtp1m1_test.cpp
@@ -16,7 +16,7 @@
 
 #include "table_type.hpp"
 
-#include "libs/math/test/powm1_sqrtp1m1_test.hpp"
+#include "powm1_sqrtp1m1_test.hpp"
 
 //
 // DESCRIPTION:
diff --git a/test/float128/table_type.hpp b/test/float128/table_type.hpp
index 6560762db4..7e5c07b248 100644
--- a/test/float128/table_type.hpp
+++ b/test/float128/table_type.hpp
@@ -5,7 +5,7 @@
 
 #ifndef BOOST_MP_TABLE_TYPE
 
-#include <libs/math/test/table_type.hpp>
+#include <table_type.hpp>
 
 #define SC_(x) BOOST_FLOATMAX_C(x)
 
diff --git a/test/float128/test_bessel_i.cpp b/test/float128/test_bessel_i.cpp
index 952cc9d6a6..7e0374cdfc 100644
--- a/test/float128/test_bessel_i.cpp
+++ b/test/float128/test_bessel_i.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/bessel.hpp>
-#include "libs/math/test/test_bessel_i.hpp"
+#include "test_bessel_i.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_bessel_j.cpp b/test/float128/test_bessel_j.cpp
index 7afeeebeb4..f3bab11fd7 100644
--- a/test/float128/test_bessel_j.cpp
+++ b/test/float128/test_bessel_j.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/bessel.hpp>
-#include "libs/math/test/test_bessel_j.hpp"
+#include "test_bessel_j.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_bessel_k.cpp b/test/float128/test_bessel_k.cpp
index a5ec1e2b4e..7f7144649f 100644
--- a/test/float128/test_bessel_k.cpp
+++ b/test/float128/test_bessel_k.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/bessel.hpp>
-#include "libs/math/test/test_bessel_k.hpp"
+#include "test_bessel_k.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_bessel_y.cpp b/test/float128/test_bessel_y.cpp
index 55bdf56e71..240d7785a1 100644
--- a/test/float128/test_bessel_y.cpp
+++ b/test/float128/test_bessel_y.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/bessel.hpp>
-#include "libs/math/test/test_bessel_y.hpp"
+#include "test_bessel_y.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_beta.cpp b/test/float128/test_beta.cpp
index 6cfddd566a..ecdf347964 100644
--- a/test/float128/test_beta.cpp
+++ b/test/float128/test_beta.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/beta.hpp>
-#include "libs/math/test/test_beta.hpp"
+#include "test_beta.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_binomial_coeff.cpp b/test/float128/test_binomial_coeff.cpp
index be208f4f55..392150b06f 100644
--- a/test/float128/test_binomial_coeff.cpp
+++ b/test/float128/test_binomial_coeff.cpp
@@ -12,7 +12,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/binomial.hpp>
-#include "libs/math/test/test_binomial_coeff.hpp"
+#include "test_binomial_coeff.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_carlson.cpp b/test/float128/test_carlson.cpp
index 1458493732..0954816c36 100644
--- a/test/float128/test_carlson.cpp
+++ b/test/float128/test_carlson.cpp
@@ -11,7 +11,7 @@
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/special_functions/ellint_rj.hpp>
 #include <boost/math/special_functions/ellint_rg.hpp>
-#include "libs/math/test/test_carlson.hpp"
+#include "test_carlson.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_cbrt.cpp b/test/float128/test_cbrt.cpp
index d6690bdd98..7b53b8a434 100644
--- a/test/float128/test_cbrt.cpp
+++ b/test/float128/test_cbrt.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/cbrt.hpp>
-#include "libs/math/test/test_cbrt.hpp"
+#include "test_cbrt.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_digamma.cpp b/test/float128/test_digamma.cpp
index 9856223bef..5702ccf73b 100644
--- a/test/float128/test_digamma.cpp
+++ b/test/float128/test_digamma.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/digamma.hpp>
-#include "libs/math/test/test_digamma.hpp"
+#include "test_digamma.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ellint_1.cpp b/test/float128/test_ellint_1.cpp
index 5c259e9405..90f9e1bed5 100644
--- a/test/float128/test_ellint_1.cpp
+++ b/test/float128/test_ellint_1.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/ellint_1.hpp>
-#include "libs/math/test/test_ellint_1.hpp"
+#include "test_ellint_1.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ellint_2.cpp b/test/float128/test_ellint_2.cpp
index 8b05124670..3f43e8c1dc 100644
--- a/test/float128/test_ellint_2.cpp
+++ b/test/float128/test_ellint_2.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/ellint_2.hpp>
-#include "libs/math/test/test_ellint_2.hpp"
+#include "test_ellint_2.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ellint_3.cpp b/test/float128/test_ellint_3.cpp
index e462683888..644dd1cbb8 100644
--- a/test/float128/test_ellint_3.cpp
+++ b/test/float128/test_ellint_3.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/ellint_3.hpp>
-#include "libs/math/test/test_ellint_3.hpp"
+#include "test_ellint_3.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_erf.cpp b/test/float128/test_erf.cpp
index 90efd139e7..5f3bcaa46a 100644
--- a/test/float128/test_erf.cpp
+++ b/test/float128/test_erf.cpp
@@ -8,7 +8,7 @@
 #define TEST_UDT
 
 #include <boost/math/special_functions/erf.hpp>
-#include "libs/math/test/test_erf.hpp"
+#include "test_erf.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_expint.cpp b/test/float128/test_expint.cpp
index 73a1f6bb5f..ff9ece822d 100644
--- a/test/float128/test_expint.cpp
+++ b/test/float128/test_expint.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/expint.hpp>
-#include "libs/math/test/test_expint.hpp"
+#include "test_expint.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_gamma.cpp b/test/float128/test_gamma.cpp
index ddaae2adf0..bcec76083e 100644
--- a/test/float128/test_gamma.cpp
+++ b/test/float128/test_gamma.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/gamma.hpp>
-#include "libs/math/test/test_gamma.hpp"
+#include "test_gamma.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_hermite.cpp b/test/float128/test_hermite.cpp
index f933c6d27f..3b6fcdfb5d 100644
--- a/test/float128/test_hermite.cpp
+++ b/test/float128/test_hermite.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/hermite.hpp>
-#include "libs/math/test/test_hermite.hpp"
+#include "test_hermite.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ibeta.cpp b/test/float128/test_ibeta.cpp
index 708a6950de..c46da77665 100644
--- a/test/float128/test_ibeta.cpp
+++ b/test/float128/test_ibeta.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/beta.hpp>
-#include "libs/math/test/test_ibeta.hpp"
+#include "test_ibeta.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ibeta_inv_1.cpp b/test/float128/test_ibeta_inv_1.cpp
index 68049024f3..2fc059740c 100644
--- a/test/float128/test_ibeta_inv_1.cpp
+++ b/test/float128/test_ibeta_inv_1.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/beta.hpp>
-#include "libs/math/test/test_ibeta_inv.hpp"
+#include "test_ibeta_inv.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_ibeta_inv_ab_4.cpp b/test/float128/test_ibeta_inv_ab_4.cpp
index 3e0bc85816..d02a99f26f 100644
--- a/test/float128/test_ibeta_inv_ab_4.cpp
+++ b/test/float128/test_ibeta_inv_ab_4.cpp
@@ -11,7 +11,7 @@
 #define FULL_TEST
 
 #include <boost/math/special_functions/beta.hpp>
-#include "libs/math/test/test_ibeta_inv_ab.hpp"
+#include "test_ibeta_inv_ab.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_igamma.cpp b/test/float128/test_igamma.cpp
index d533254841..7a987c643e 100644
--- a/test/float128/test_igamma.cpp
+++ b/test/float128/test_igamma.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/gamma.hpp>
-#include "libs/math/test/test_igamma.hpp"
+#include "test_igamma.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_igamma_inv.cpp b/test/float128/test_igamma_inv.cpp
index 122db9d42e..bc9b4289e2 100644
--- a/test/float128/test_igamma_inv.cpp
+++ b/test/float128/test_igamma_inv.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/gamma.hpp>
-#include "libs/math/test/test_igamma_inv.hpp"
+#include "test_igamma_inv.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_igamma_inva.cpp b/test/float128/test_igamma_inva.cpp
index 0a244c2f45..19daa7cfa7 100644
--- a/test/float128/test_igamma_inva.cpp
+++ b/test/float128/test_igamma_inva.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/gamma.hpp>
-#include "libs/math/test/test_igamma_inva.hpp"
+#include "test_igamma_inva.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_laguerre.cpp b/test/float128/test_laguerre.cpp
index 04ae016b94..dfa475448c 100644
--- a/test/float128/test_laguerre.cpp
+++ b/test/float128/test_laguerre.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/laguerre.hpp>
-#include "libs/math/test/test_laguerre.hpp"
+#include "test_laguerre.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_legendre.cpp b/test/float128/test_legendre.cpp
index 463c2d90a7..e6de9644a7 100644
--- a/test/float128/test_legendre.cpp
+++ b/test/float128/test_legendre.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/legendre.hpp>
-#include "libs/math/test/test_legendre.hpp"
+#include "test_legendre.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_polygamma.cpp b/test/float128/test_polygamma.cpp
index e62cef9af6..1ff41e34f1 100644
--- a/test/float128/test_polygamma.cpp
+++ b/test/float128/test_polygamma.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/polygamma.hpp>
-#include "libs/math/test/test_polygamma.hpp"
+#include "test_polygamma.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_tgamma_ratio.cpp b/test/float128/test_tgamma_ratio.cpp
index 9d2568f558..0138ce472f 100644
--- a/test/float128/test_tgamma_ratio.cpp
+++ b/test/float128/test_tgamma_ratio.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/gamma.hpp>
-#include "libs/math/test/test_tgamma_ratio.hpp"
+#include "test_tgamma_ratio.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_trigamma.cpp b/test/float128/test_trigamma.cpp
index 8862b53d00..3ab2f9473b 100644
--- a/test/float128/test_trigamma.cpp
+++ b/test/float128/test_trigamma.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/trigamma.hpp>
-#include "libs/math/test/test_trigamma.hpp"
+#include "test_trigamma.hpp"
 
 void expected_results()
 {
diff --git a/test/float128/test_zeta.cpp b/test/float128/test_zeta.cpp
index 4dcdf19cc1..67aebfbff5 100644
--- a/test/float128/test_zeta.cpp
+++ b/test/float128/test_zeta.cpp
@@ -7,7 +7,7 @@
 #include "table_type.hpp"
 
 #include <boost/math/special_functions/zeta.hpp>
-#include "libs/math/test/test_zeta.hpp"
+#include "test_zeta.hpp"
 
 void expected_results()
 {
diff --git a/test/test_bernoulli_constants.cpp b/test/test_bernoulli_constants.cpp
index f5ae15a3ee..0c5c81b62f 100644
--- a/test/test_bernoulli_constants.cpp
+++ b/test/test_bernoulli_constants.cpp
@@ -22,114 +22,114 @@ void test(const char* name)
 {
    std::cout << "Testing type " << name << ":\n";
 
-   static const typename table_type<T>::type data[] = 
+   static const typename table_type<T>::type data[] =
    {
       /* First 50 from 2 to 100 inclusive: */
       /* TABLE[N[BernoulliB[n], 200], {n,2,100,2}] */
 
-      SC_(0.1666666666666666666666666666666666666666), 
-      SC_(-0.0333333333333333333333333333333333333333), 
-      SC_(0.0238095238095238095238095238095238095238), 
-      SC_(-0.0333333333333333333333333333333333333333), 
-      SC_(0.0757575757575757575757575757575757575757), 
-      SC_(-0.2531135531135531135531135531135531135531), 
-      SC_(1.1666666666666666666666666666666666666666), 
-      SC_(-7.0921568627450980392156862745098039215686), 
-      SC_(54.9711779448621553884711779448621553884711), 
-      SC_(-529.1242424242424242424242424242424242424242), 
-      SC_(6192.1231884057971014492753623188405797101449), 
-      SC_(-86580.2531135531135531135531135531135531135531), 
-      SC_(1.4255171666666666666666666666666666666666e6), 
-      SC_(-2.7298231067816091954022988505747126436781e7), 
-      SC_(6.0158087390064236838430386817483591677140e8), 
-      SC_(-1.5116315767092156862745098039215686274509e10), 
-      SC_(4.2961464306116666666666666666666666666666e11), 
-      SC_(-1.3711655205088332772159087948561632772159e13), 
-      SC_(4.8833231897359316666666666666666666666666e14), 
-      SC_(-1.9296579341940068148632668144863266814486e16), 
-      SC_(8.4169304757368261500055370985603543743078e17), 
-      SC_(-4.0338071854059455413076811594202898550724e19), 
-      SC_(2.1150748638081991605601453900709219858156e21), 
-      SC_(-1.2086626522296525934602731193708252531781e23), 
-      SC_(7.5008667460769643668557200757575757575757e24), 
-      SC_(-5.0387781014810689141378930305220125786163e26), 
-      SC_(3.6528776484818123335110430842971177944862e28), 
-      SC_(-2.8498769302450882226269146432910678160919e30), 
-      SC_(2.3865427499683627644645981919219214971751e32), 
-      SC_(-2.1399949257225333665810744765191097392674e34), 
-      SC_(2.0500975723478097569921733095672310251666e36), 
-      SC_(-2.0938005911346378409095185290027970184709e38), 
-      SC_(2.2752696488463515559649260352769264581469e40), 
-      SC_(-2.6257710286239576047303049736158202081449e42), 
-      SC_(3.2125082102718032518204792304264985243521e44), 
-      SC_(-4.1598278166794710913917074495262358936689e46), 
-      SC_(5.6920695482035280023883456219121058644480e48), 
-      SC_(-8.2183629419784575692290653468617333014550e50), 
-      SC_(1.2502904327166993016732339829702895524177e53), 
-      SC_(-2.0015583233248370274925329198813298768724e55), 
-      SC_(3.3674982915364374233396676903338753016219e57), 
-      SC_(-5.9470970503135447718660496844051540840579e59), 
-      SC_(1.1011910323627977559564130790437691604630e62), 
-      SC_(-2.1355259545253501188658385019041065678973e64), 
-      SC_(4.3328896986641192419616613059379206218451e66), 
-      SC_(-9.1885528241669328226200555215501897138960e68), 
-      SC_(2.0346896776329074493455027990220020065975e71), 
-      SC_(-4.7003833958035731078575255535006060654596e73), 
-      SC_(1.1318043445484249270675186257733934267890e76), 
+      SC_(0.1666666666666666666666666666666666666666),
+      SC_(-0.0333333333333333333333333333333333333333),
+      SC_(0.0238095238095238095238095238095238095238),
+      SC_(-0.0333333333333333333333333333333333333333),
+      SC_(0.0757575757575757575757575757575757575757),
+      SC_(-0.2531135531135531135531135531135531135531),
+      SC_(1.1666666666666666666666666666666666666666),
+      SC_(-7.0921568627450980392156862745098039215686),
+      SC_(54.9711779448621553884711779448621553884711),
+      SC_(-529.1242424242424242424242424242424242424242),
+      SC_(6192.1231884057971014492753623188405797101449),
+      SC_(-86580.2531135531135531135531135531135531135531),
+      SC_(1.4255171666666666666666666666666666666666e6),
+      SC_(-2.7298231067816091954022988505747126436781e7),
+      SC_(6.0158087390064236838430386817483591677140e8),
+      SC_(-1.5116315767092156862745098039215686274509e10),
+      SC_(4.2961464306116666666666666666666666666666e11),
+      SC_(-1.3711655205088332772159087948561632772159e13),
+      SC_(4.8833231897359316666666666666666666666666e14),
+      SC_(-1.9296579341940068148632668144863266814486e16),
+      SC_(8.4169304757368261500055370985603543743078e17),
+      SC_(-4.0338071854059455413076811594202898550724e19),
+      SC_(2.1150748638081991605601453900709219858156e21),
+      SC_(-1.2086626522296525934602731193708252531781e23),
+      SC_(7.5008667460769643668557200757575757575757e24),
+      SC_(-5.0387781014810689141378930305220125786163e26),
+      SC_(3.6528776484818123335110430842971177944862e28),
+      SC_(-2.8498769302450882226269146432910678160919e30),
+      SC_(2.3865427499683627644645981919219214971751e32),
+      SC_(-2.1399949257225333665810744765191097392674e34),
+      SC_(2.0500975723478097569921733095672310251666e36),
+      SC_(-2.0938005911346378409095185290027970184709e38),
+      SC_(2.2752696488463515559649260352769264581469e40),
+      SC_(-2.6257710286239576047303049736158202081449e42),
+      SC_(3.2125082102718032518204792304264985243521e44),
+      SC_(-4.1598278166794710913917074495262358936689e46),
+      SC_(5.6920695482035280023883456219121058644480e48),
+      SC_(-8.2183629419784575692290653468617333014550e50),
+      SC_(1.2502904327166993016732339829702895524177e53),
+      SC_(-2.0015583233248370274925329198813298768724e55),
+      SC_(3.3674982915364374233396676903338753016219e57),
+      SC_(-5.9470970503135447718660496844051540840579e59),
+      SC_(1.1011910323627977559564130790437691604630e62),
+      SC_(-2.1355259545253501188658385019041065678973e64),
+      SC_(4.3328896986641192419616613059379206218451e66),
+      SC_(-9.1885528241669328226200555215501897138960e68),
+      SC_(2.0346896776329074493455027990220020065975e71),
+      SC_(-4.7003833958035731078575255535006060654596e73),
+      SC_(1.1318043445484249270675186257733934267890e76),
       SC_(-2.8382249570693706959264156336481764738284e78),
 
       /* next 50 from 102 to 200: */
       /* TABLE[N[BernoulliB[n], 200], {n,102,200,2}] */
 
-      SC_(7.4064248979678850629750827140920984176879e80), 
-      SC_(-2.0096454802756604483465619672715363186867e83), 
-      SC_(5.6657170050805941445719346030519356961419e85), 
-      SC_(-1.6584511154136216915823713374319912301494e88), 
-      SC_(5.0368859950492377419289421915180154812442e90), 
-      SC_(-1.5861468237658186369363401572966438782740e93), 
-      SC_(5.1756743617545626984073240682507122561240e95), 
-      SC_(-1.7488921840217117339690025877618159145141e98), 
-      SC_(6.1160519994952185255824525264264167780767e100), 
-      SC_(-2.2122776912707834942288323456712932445573e103), 
-      SC_(8.2722776798770969854221062459984595731204e105), 
-      SC_(-3.1958925111415709583591634369180814873526e108), 
-      SC_(1.2750082223387792982310024302926679866957e111), 
-      SC_(-5.2500923086774133899402824624565175446919e113), 
-      SC_(2.2301817894241625209869298198838728143738e116), 
-      SC_(-9.7684521930955204438633513398980239301166e118), 
-      SC_(4.4098361978452954272272622874813169191875e121), 
-      SC_(-2.0508570886464088839729337727583015486456e124), 
-      SC_(9.8214433279791277107572969602097521041491e126), 
-      SC_(-4.8412600798208880508789196709963412761130e129), 
-      SC_(2.4553088801480982609783467404088690399673e132), 
-      SC_(-1.2806926804084747548782513278601785721811e135), 
-      SC_(6.8676167104668581192101888598464400436092e137), 
-      SC_(-3.7846468581969104694978995416379556814489e140), 
-      SC_(2.1426101250665291550871323135148272096660e143), 
-      SC_(-1.2456727137183695007019642961637607219458e146), 
-      SC_(7.4345787551000152543679668394052061311780e148), 
-      SC_(-4.5535795304641704894063333223321274876772e151), 
-      SC_(2.8612112816858868345363847251017232522918e154), 
-      SC_(-1.8437723552033869727688202653628785487541e157), 
-      SC_(1.2181154536221046699501316506599521355817e160), 
-      SC_(-8.2482187185314121548481845729689344730141e162), 
-      SC_(5.7225877937832943329651649814297861591868e165), 
-      SC_(-4.0668530525059104726767969383115865560219e168), 
-      SC_(2.9596092064642050062875269581585187042637e171), 
-      SC_(-2.2049522565189457509031175227344598483637e174), 
-      SC_(1.6812597072889599805831152515136066575446e177), 
-      SC_(-1.3116736213556957648645280635581715300443e180), 
-      SC_(1.0467894009478038082183285392982308964382e183), 
-      SC_(-8.5432893578833707718598254629908277459327e185), 
-      SC_(7.1287821322486542352288406677143822472124e188), 
-      SC_(-6.0802931455535899300084711868647745846198e191), 
-      SC_(5.2996776424849923930094291004324726622848e194), 
-      SC_(-4.7194259168745862644364622901337991110376e197), 
-      SC_(4.2928413791402981089416829654107466904552e200), 
-      SC_(-3.9876744968232207443447765554293879510665e203), 
-      SC_(3.7819780419358882713894418116139332789822e206), 
-      SC_(-3.6614233683681191243685808215119734875519e209), 
-      SC_(3.6176090272372862348855460929891408947754e212), 
+      SC_(7.4064248979678850629750827140920984176879e80),
+      SC_(-2.0096454802756604483465619672715363186867e83),
+      SC_(5.6657170050805941445719346030519356961419e85),
+      SC_(-1.6584511154136216915823713374319912301494e88),
+      SC_(5.0368859950492377419289421915180154812442e90),
+      SC_(-1.5861468237658186369363401572966438782740e93),
+      SC_(5.1756743617545626984073240682507122561240e95),
+      SC_(-1.7488921840217117339690025877618159145141e98),
+      SC_(6.1160519994952185255824525264264167780767e100),
+      SC_(-2.2122776912707834942288323456712932445573e103),
+      SC_(8.2722776798770969854221062459984595731204e105),
+      SC_(-3.1958925111415709583591634369180814873526e108),
+      SC_(1.2750082223387792982310024302926679866957e111),
+      SC_(-5.2500923086774133899402824624565175446919e113),
+      SC_(2.2301817894241625209869298198838728143738e116),
+      SC_(-9.7684521930955204438633513398980239301166e118),
+      SC_(4.4098361978452954272272622874813169191875e121),
+      SC_(-2.0508570886464088839729337727583015486456e124),
+      SC_(9.8214433279791277107572969602097521041491e126),
+      SC_(-4.8412600798208880508789196709963412761130e129),
+      SC_(2.4553088801480982609783467404088690399673e132),
+      SC_(-1.2806926804084747548782513278601785721811e135),
+      SC_(6.8676167104668581192101888598464400436092e137),
+      SC_(-3.7846468581969104694978995416379556814489e140),
+      SC_(2.1426101250665291550871323135148272096660e143),
+      SC_(-1.2456727137183695007019642961637607219458e146),
+      SC_(7.4345787551000152543679668394052061311780e148),
+      SC_(-4.5535795304641704894063333223321274876772e151),
+      SC_(2.8612112816858868345363847251017232522918e154),
+      SC_(-1.8437723552033869727688202653628785487541e157),
+      SC_(1.2181154536221046699501316506599521355817e160),
+      SC_(-8.2482187185314121548481845729689344730141e162),
+      SC_(5.7225877937832943329651649814297861591868e165),
+      SC_(-4.0668530525059104726767969383115865560219e168),
+      SC_(2.9596092064642050062875269581585187042637e171),
+      SC_(-2.2049522565189457509031175227344598483637e174),
+      SC_(1.6812597072889599805831152515136066575446e177),
+      SC_(-1.3116736213556957648645280635581715300443e180),
+      SC_(1.0467894009478038082183285392982308964382e183),
+      SC_(-8.5432893578833707718598254629908277459327e185),
+      SC_(7.1287821322486542352288406677143822472124e188),
+      SC_(-6.0802931455535899300084711868647745846198e191),
+      SC_(5.2996776424849923930094291004324726622848e194),
+      SC_(-4.7194259168745862644364622901337991110376e197),
+      SC_(4.2928413791402981089416829654107466904552e200),
+      SC_(-3.9876744968232207443447765554293879510665e203),
+      SC_(3.7819780419358882713894418116139332789822e206),
+      SC_(-3.6614233683681191243685808215119734875519e209),
+      SC_(3.6176090272372862348855460929891408947754e212),
       SC_(-3.6470772645191354362138308865549944904868e215),
    };
 
diff --git a/test/test_nonfinite_io.cpp b/test/test_nonfinite_io.cpp
index b917549810..855843c715 100644
--- a/test/test_nonfinite_io.cpp
+++ b/test/test_nonfinite_io.cpp
@@ -14,8 +14,8 @@
 #define BOOST_TEST_MAIN
 
 #include <boost/test/unit_test.hpp>
-#include <libs/math/test/almost_equal.ipp> // Similar to BOOST_CLOSE_FRACTION.
-#include <libs/math/test/s_.ipp> // To create test strings like std::basic_string<CharType> s = S_("0 -0"); 
+#include <almost_equal.ipp> // Similar to BOOST_CLOSE_FRACTION.
+#include <s_.ipp> // To create test strings like std::basic_string<CharType> s = S_("0 -0"); 
 #include <boost/math/special_functions/nonfinite_num_facets.hpp>
 
 #include <locale>
diff --git a/tools/Jamfile.v2 b/tools/Jamfile.v2
index 4a986620b7..56155ec3cc 100644
--- a/tools/Jamfile.v2
+++ b/tools/Jamfile.v2
@@ -1,6 +1,6 @@
 # Copyright John Maddock 2010
-# Distributed under the Boost Software License, Version 1.0. 
-# (See accompanying file LICENSE_1_0.txt or copy at 
+# Distributed under the Boost Software License, Version 1.0.
+# (See accompanying file LICENSE_1_0.txt or copy at
 # http://www.boost.org/LICENSE_1_0.txt.
 # \math_toolkit\libs\math\test\jamfile.v2
 # Runs all math toolkit tests, functions & distributions,
@@ -9,45 +9,47 @@
 # bring in the rules for testing
 import modules ;
 import path ;
-import ../../config/checks/config : requires ;
+import-search /boost/config/checks ;
+import config : requires ;
 
-project  
-    : requirements 
+project
+    : requirements
       <toolset>gcc:<cxxflags>-Wno-missing-braces
       <toolset>darwin:<cxxflags>-Wno-missing-braces
       <toolset>acc:<cxxflags>+W2068,2461,2236,4070,4069
-      <toolset>intel-win:<cxxflags>-nologo 
-      <toolset>intel-win:<linkflags>-nologo 
+      <toolset>intel-win:<cxxflags>-nologo
+      <toolset>intel-win:<linkflags>-nologo
       <toolset>msvc:<warnings>all
       <toolset>msvc:<asynch-exceptions>on
       <toolset>msvc:<cxxflags>/wd4996
-      <toolset>msvc:<cxxflags>/wd4512 
-      <toolset>msvc:<cxxflags>/wd4610 
-      <toolset>msvc:<cxxflags>/wd4510 
-      <toolset>msvc:<cxxflags>/wd4127 
+      <toolset>msvc:<cxxflags>/wd4512
+      <toolset>msvc:<cxxflags>/wd4610
+      <toolset>msvc:<cxxflags>/wd4510
+      <toolset>msvc:<cxxflags>/wd4127
       <toolset>msvc:<cxxflags>/wd4701 # needed for lexical cast - temporary.
       <link>static
       <toolset>borland:<runtime-link>static
-      <include>../../..
       <define>BOOST_ALL_NO_LIB=1
       <define>BOOST_UBLAS_UNSUPPORTED_COMPILER=0
       <include>.
       <include>../include_private
+      <library>/boost/multiprecision//boost_multiprecision
+      <library>/boost/algorithm//boost_algorithm
     ;
 
-lib gmp ;
-lib mpfr ;
-lib mpfi ;
-lib quadmath ;
+searched-lib gmp : : <link>shared ;
+searched-lib mpfr : : <link>shared ;
+searched-lib mpfi : : <link>shared ;
+searched-lib quadmath : : <link>shared ;
 
 exe bessel_data : bessel_data.cpp :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install bessel_data_install : bessel_data : <location>bin ;
 
-exe ellint_f_data : ellint_f_data.cpp ;
+exe ellint_f_data : ellint_f_data.cpp /boost/test//included ;
 install ellint_f_data_install : ellint_f_data : <location>bin ;
 
-exe heuman_lambda_data : heuman_lambda_data.cpp ;
+exe heuman_lambda_data : heuman_lambda_data.cpp /boost/test//included ;
 install heuman_lambda_data_install : heuman_lambda_data : <location>bin ;
 
 exe hyp_2f2_data : hyp_2f2_data.cpp ;
@@ -56,24 +58,24 @@ install hyp_2f2_data_install : hyp_2f2_data : <location>bin ;
 exe laguerre_data : laguerre_data.cpp ;
 install laguerre_data_install : laguerre_data : <location>bin ;
 
-exe bessel_derivative_data : bessel_derivative_data.cpp :
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] 
+exe bessel_derivative_data : bessel_derivative_data.cpp /boost/test//included :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ]
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install bessel_derivative_data_install : bessel_derivative_data : <location>bin ;
 
-exe ellint_k_data : ellint_k_data.cpp ;
+exe ellint_k_data : ellint_k_data.cpp /boost/test//included ;
 install ellint_k_data_install : ellint_k_data : <location>bin ;
 
 exe hyp_0f2_data : hyp_0f2_data.cpp ;
 install hyp_0f2_data_install : hyp_0f2_data : <location>bin ;
 
-exe hypergeometric_dist_data : hypergeometric_dist_data.cpp : 
-[ check-target-builds ../config//is_ci_standalone_run : <build>no ] 
+exe hypergeometric_dist_data : hypergeometric_dist_data.cpp :
+[ check-target-builds ../config//is_ci_standalone_run : <build>no ]
 [ requires cxx11_hdr_random ] ;
 install hypergeometric_dist_data_install : hypergeometric_dist_data : <location>bin ;
 
-exe legendre_data : legendre_data.cpp : 
+exe legendre_data : legendre_data.cpp :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install legendre_data_install : legendre_data : <location>bin ;
 
@@ -81,13 +83,13 @@ exe beta_data : beta_data.cpp :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install beta_data_install : beta_data : <location>bin ;
 
-exe ellint_pi2_data : ellint_pi2_data.cpp ;
+exe ellint_pi2_data : ellint_pi2_data.cpp /boost/test//included ;
 install ellint_pi2_data_install : ellint_pi2_data : <location>bin ;
 
-exe hyp_1f1_big_data : hyp_1f1_big_data.cpp : 
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ] 
+exe hyp_1f1_big_data : hyp_1f1_big_data.cpp :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ]
 [ requires cxx11_decltype ] ;
 install hyp_1f1_big_data_install : hyp_1f1_big_data : <location>bin ;
 
@@ -98,68 +100,68 @@ install ibeta_data_install : ibeta_data : <location>bin ;
 exe log1p_expm1_data : log1p_expm1_data.cpp ;
 install log1p_expm1_data_install : log1p_expm1_data : <location>bin ;
 
-exe carlson_ellint_data : carlson_ellint_data.cpp ;
+exe carlson_ellint_data : carlson_ellint_data.cpp /boost/test//included ;
 install carlson_ellint_data_install : carlson_ellint_data : <location>bin ;
 
-exe ellint_pi3_data : ellint_pi3_data.cpp ;
+exe ellint_pi3_data : ellint_pi3_data.cpp /boost/test//included ;
 install ellint_pi3_data_install : ellint_pi3_data : <location>bin ;
 
-exe hyp_1f1_data : hyp_1f1_data.cpp : 
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ] 
+exe hyp_1f1_data : hyp_1f1_data.cpp :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ]
 [ requires cxx11_decltype ] ;
 install hyp_1f1_data_install : hyp_1f1_data : <location>bin ;
 
-exe ibeta_derivative_data : ibeta_derivative_data.cpp :
+exe ibeta_derivative_data : ibeta_derivative_data.cpp /boost/math//testing :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install ibeta_derivative_data_install : ibeta_derivative_data : <location>bin ;
 
-exe sinc_data : sinc_data.cpp ;
+exe sinc_data : sinc_data.cpp /boost/test//included ;
 install sinc_data_install : sinc_data : <location>bin ;
 
 exe cbrt_data : cbrt_data.cpp ;
 install cbrt_data_install : cbrt_data : <location>bin ;
 
-exe erf_data : erf_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe erf_data : erf_data.cpp : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install erf_data_install : erf_data : <location>bin ;
 
-exe hyp_1f1_log_big_data : hyp_1f1_log_big_data.cpp : 
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ] 
+exe hyp_1f1_log_big_data : hyp_1f1_log_big_data.cpp :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ]
 [ requires cxx11_decltype ] ;
 install hyp_1f1_log_big_data_install : hyp_1f1_log_big_data : <location>bin ;
 
-exe ibeta_inv_data : ibeta_inv_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe ibeta_inv_data : ibeta_inv_data.cpp : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install ibeta_inv_data_install : ibeta_inv_data : <location>bin ;
 
 exe spherical_harmonic_data : spherical_harmonic_data.cpp :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install spherical_harmonic_data_install : spherical_harmonic_data : <location>bin ;
 
-exe digamma_data : digamma_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe digamma_data : digamma_data.cpp /boost/test//included : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install digamma_data_install : digamma_data : <location>bin ;
 
 exe expint_data : expint_data.cpp ;
 install expint_data_install : expint_data : <location>bin ;
 
-exe hyp_1f1_reg_big_data : hyp_1f1_reg_big_data.cpp : 
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ] 
+exe hyp_1f1_reg_big_data : hyp_1f1_reg_big_data.cpp :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfi : <source>gmp <source>mpfr <source>mpfi : <build>no ]
 [ requires cxx11_decltype ] ;
 install hyp_1f1_reg_big_data_install : hyp_1f1_reg_big_data : <location>bin ;
 
-exe ibeta_invab_data : ibeta_invab_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe ibeta_invab_data : ibeta_invab_data.cpp : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install ibeta_invab_data_install : ibeta_invab_data : <location>bin ;
 
-exe tgamma_large_data : tgamma_large_data.cpp : 
-[ check-target-builds ../../multiprecision/config//has_gmp : <source>gmp : <build>no ] 
-[ check-target-builds ../../multiprecision/config//has_mpfr : <source>mpfr : <build>no ] ;
+exe tgamma_large_data : tgamma_large_data.cpp /boost/test//included :
+[ check-target-builds /boost/multiprecision/config//has_gmp : <source>gmp : <build>no ]
+[ check-target-builds /boost/multiprecision/config//has_mpfr : <source>mpfr : <build>no ] ;
 install tgamma_large_data_install : tgamma_large_data : <location>bin ;
 
-exe ellint_d_data : ellint_d_data.cpp ;
+exe ellint_d_data : ellint_d_data.cpp /boost/test//included ;
 install ellint_d_data_install : ellint_d_data : <location>bin ;
 
 exe expint_i_data : expint_i_data.cpp ;
@@ -168,17 +170,17 @@ install expint_i_data_install : expint_i_data : <location>bin ;
 exe hyp_1f2_data : hyp_1f2_data.cpp ;
 install hyp_1f2_data_install : hyp_1f2_data : <location>bin ;
 
-exe igamma_data : igamma_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe igamma_data : igamma_data.cpp : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install igamma_data_install : igamma_data : <location>bin ;
 
-exe tgamma_ratio_data : tgamma_ratio_data.cpp : 
+exe tgamma_ratio_data : tgamma_ratio_data.cpp :
 [ check-target-builds ../config//is_ci_standalone_run : <build>no ] ;
 install tgamma_ratio_data_install : tgamma_ratio_data : <location>bin ;
 
-exe ellint_d2_data : ellint_d2_data.cpp ;
+exe ellint_d2_data : ellint_d2_data.cpp /boost/test//included ;
 install ellint_d2_data_install : ellint_d2_data : <location>bin ;
 
-exe gamma_P_inva_data : gamma_P_inva_data.cpp : [ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
+exe gamma_P_inva_data : gamma_P_inva_data.cpp : [ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ] ;
 install gamma_P_inva_data_install : gamma_P_inva_data : <location>bin ;
 
 exe hyp_2f0_data : hyp_2f0_data.cpp ;
@@ -190,7 +192,7 @@ install inv_hyp_data_install : inv_hyp_data : <location>bin ;
 exe trig_data : trig_data.cpp ;
 install trig_data_install : trig_data : <location>bin ;
 
-exe ellint_e_data : ellint_e_data.cpp ;
+exe ellint_e_data : ellint_e_data.cpp /boost/test//included ;
 install ellint_e_data_install : ellint_e_data : <location>bin ;
 
 exe hermite_data : hermite_data.cpp ;
@@ -199,10 +201,10 @@ install hermite_data_install : hermite_data : <location>bin ;
 exe hyp_2f1_data : hyp_2f1_data.cpp ;
 install hyp_2f1_data_install : hyp_2f1_data : <location>bin ;
 
-exe jacobi_theta_data : jacobi_theta_data.cpp ;
+exe jacobi_theta_data : jacobi_theta_data.cpp /boost/test//included ;
 install jacobi_theta_data_install : jacobi_theta_data : <location>bin ;
 
-exe jacobi_zeta_data : jacobi_zeta_data.cpp ;
+exe jacobi_zeta_data : jacobi_zeta_data.cpp /boost/test//included ;
 install jacobi_zeta_data_install : jacobi_zeta_data : <location>bin ;
 
 exe zeta_data : zeta_data.cpp :
@@ -215,8 +217,8 @@ install generate_test_values_install : generate_test_values : <location>bin ;
 exe igamma_temme_large_coef : igamma_temme_large_coef.cpp ;
 install igamma_temme_large_coef_install : igamma_temme_large_coef : <location>bin ;
 
-exe lanczos_generator : lanczos_generator.cpp ../../chrono/build//boost_chrono ../../system/build//boost_system : 
-[ check-target-builds ../../multiprecision/config//has_float128 : <source>quadmath : <build>no ] 
+exe lanczos_generator : lanczos_generator.cpp /boost/chrono//boost_chrono /boost/system//boost_system :
+[ check-target-builds /boost/multiprecision/config//has_float128 : <source>quadmath : <build>no ]
 [ requires cxx11_nullptr ] ;
 install lanczos_generator_install : lanczos_generator : <location>bin ;
 
@@ -228,11 +230,11 @@ install generate_rational_test_install : generate_rational_test : <location>bin
 
 #for local source in [ glob *_data.cpp ] generate_test_values.cpp igamma_temme_large_coef.cpp lanczos_generator.cpp factorial_tables.cpp generate_rational_test.cpp
 #{
-#   exe $(source:B) : $(source) : [ check-target-builds ../../multiprecision/config//has_gmp : <define>HAS_GMP <source>gmp : <build>no ] [ check-target-builds ../../multiprecision/config//has_mpfr : <define>HAS_MPFR <source>mpfr : <build>no ] [ check-target-builds ../../multiprecision/config//has_mpfi : <define>HAS_MPFI <source>gmp <source>mpfr <source>mpfi ] ;
+#   exe $(source:B) : $(source) : [ check-target-builds /boost/multiprecision/config//has_gmp : <define>HAS_GMP <source>gmp : <build>no ] [ check-target-builds /boost/multiprecision/config//has_mpfr : <define>HAS_MPFR <source>mpfr : <build>no ] [ check-target-builds /boost/multiprecision/config//has_mpfi : <define>HAS_MPFI <source>gmp <source>mpfr <source>mpfi ] ;
 #   install $(source:B)_bin : $(source:B) : <location>bin ;
 #}
 
 exe generate_rational_code : generate_rational_code.cpp ;
-exe process_perf_results : process_perf_results.cpp ;
+exe process_perf_results : process_perf_results.cpp /boost/format//boost_format ;
 
 install bin : generate_rational_code process_perf_results ;
diff --git a/tools/ibeta_derivative_data.cpp b/tools/ibeta_derivative_data.cpp
index f00fe46785..27d647410d 100644
--- a/tools/ibeta_derivative_data.cpp
+++ b/tools/ibeta_derivative_data.cpp
@@ -17,11 +17,11 @@ using namespace boost::math::tools;
 using namespace boost::math;
 using namespace std;
 
-#include <libs/math/test/table_type.hpp>
+#include <table_type.hpp>
 
 #define T double
 #define SC_(x) static_cast<double>(x)
-#include <libs/math/test/ibeta_int_data.ipp>
+#include <ibeta_int_data.ipp>
 
 int main(int, char* [])
 {
diff --git a/tools/nc_t_data.cpp b/tools/nc_t_data.cpp
index 90b9e61558..ff3b994739 100644
--- a/tools/nc_t_data.cpp
+++ b/tools/nc_t_data.cpp
@@ -24,7 +24,7 @@
 #include <boost/multiprecision/mpfr.hpp>
 #include <fstream>
 
-#include <libs/math/test/table_type.hpp>
+#include <table_type.hpp>
 
 using namespace boost::math::tools;
 using namespace boost::math;
@@ -91,7 +91,7 @@ int main(int, char* [])
    boost::math::quadrature::exp_sinh<big_t> integrator(10);
    using T = float;
 
-#include <libs/math/test/nct.ipp>
+#include <nct.ipp>
 
 
    for (unsigned i = 0; i < nct.size(); ++i)
@@ -127,7 +127,7 @@ int main(int, char* [])
       std::cout << cdf << "), SC_(" << ccdf << ") }}," << std::endl;
    }
 
-#include <libs/math/test/nct_small_delta.ipp>
+#include <nct_small_delta.ipp>
    for (unsigned i = 0; i < nct_small_delta.size(); ++i)
    {
       big_t error1, error2;

From e9cd6c96fd5c9606e3238b3a4ed3bbce1f945c7f Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Fri, 6 Sep 2024 12:10:09 -0400
Subject: [PATCH 375/399] Add GPU support to normal dist

Add SYCL testing of normal dist

Add CUDA testing of normal dist

Add NVRTC testing of normal dist

NVRTC fixes

Move headers for NVRTC support

Add GPU support to inverse gaussian dist

Add NVRTC testing of inverse Gaussian dist

Add CUDA testing of inverse gaussian dist

Add SYCL testing of inverse gaussian dist

Add GPU support to lognormal dist

Add SYCL testing of lognormal dist

Add CUDA testing of lognormal dist

Add nvrtc testing of lognormal dist

Add GPU support to negative binomial dist

Avoid float_prior on GPU platform

Add NVRTC testing of negative binomial dist

Fix ambiguous use of nextafter

Add CUDA testing of negative binomial dist

Fix float_prior workaround

Add SYCL testing of negative binomial dist

Add GPU support to non_central_beta dist

Add SYCL testing of nc beta dist

Add CUDA testing of nc beta dist

Enable generic dist handling on GPU

Add GPU support to brent_find_minima

Add NVRTC testing of nc beta dist

Add utility header

Replace non-functional macro with new function

Add GPU support to non central chi squared dist

Add SYCL testing of non central chi squared dist

Add missing macro definition

Markup generic quantile finder

Add CUDA testing of non central chi squared dist

Add NVRTC testing of non central chi squared dist

Add GPU support to the non-central f dist

Add SYCL testing of ncf

Add CUDA testing of ncf dist

Add NVRTC testing of ncf dist

Add GPU support to students_t dist

Add SYCL testing of students_t dist

Add CUDA testing of students_t

Add NVRTC testing of students_t dist

Workaround for header cycle

Add GPU support to pareto dist

Add SYCL testing of pareto dist

Add CUDA testing of pareto dist

Add NVRTC testing of pareto dist

Add missing header

Add GPU support to poisson dist

Add SYCL testing of poisson dist

Add CUDA testing of poisson dist

Add NVRTC testing of poisson dist

Add forward decl for NVRTC platform

Add GPU support to rayleigh dist

Add CUDA testing of rayleigh dist

Add SYCL testing of rayleigh dist

Add NVRTC testing of rayleigh dist

Add GPU support to triangular dist

Add SYCL testing of triangular dist

Add NVRTC testing of triangular dist

Add CUDA testing of triangular dist

Add GPU support to the uniform dist

Add CUDA testing of uniform dist

Add SYCL testing of uniform dist

Add NVRTC testing of uniform dist

Fix missing header

Add markers to docs
---
 doc/distributions/inverse_gaussian.qbk        |  16 +-
 doc/distributions/lognormal.qbk               |  14 +-
 doc/distributions/nc_beta.qbk                 |  18 +-
 doc/distributions/nc_chi_squared.qbk          |  35 ++--
 doc/distributions/nc_f.qbk                    |  18 +-
 doc/distributions/negative_binomial.qbk       |  30 +--
 doc/distributions/normal.qbk                  |  22 +-
 doc/distributions/pareto.qbk                  |  14 +-
 doc/distributions/poisson.qbk                 |  10 +-
 doc/distributions/rayleigh.qbk                |  10 +-
 doc/distributions/students_t.qbk              |  14 +-
 doc/distributions/triangular.qbk              |  18 +-
 doc/distributions/uniform.qbk                 |  14 +-
 .../detail/common_error_handling.hpp          |   7 +-
 .../distributions/detail/generic_mode.hpp     |  15 +-
 .../distributions/detail/generic_quantile.hpp |  16 +-
 .../detail/inv_discrete_quantile.hpp          |   8 +-
 .../math/distributions/inverse_gaussian.hpp   |  88 ++++----
 .../boost/math/distributions/lognormal.hpp    |  62 +++---
 .../math/distributions/negative_binomial.hpp  |  88 ++++----
 .../math/distributions/non_central_beta.hpp   | 117 ++++++-----
 .../distributions/non_central_chi_squared.hpp | 147 +++++++-------
 .../math/distributions/non_central_f.hpp      |  60 +++---
 include/boost/math/distributions/normal.hpp   |  82 ++++----
 include/boost/math/distributions/pareto.hpp   |  89 ++++----
 include/boost/math/distributions/poisson.hpp  |  70 +++----
 include/boost/math/distributions/rayleigh.hpp |  88 ++++----
 .../boost/math/distributions/students_t.hpp   |  80 ++++----
 .../boost/math/distributions/triangular.hpp   |  82 ++++----
 include/boost/math/distributions/uniform.hpp  |  55 ++---
 .../boost/math/policies/error_handling.hpp    |   4 +-
 .../special_functions/detail/gamma_inva.hpp   |   9 +-
 .../detail/t_distribution_inv.hpp             |  13 ++
 .../boost/math/special_functions/math_fwd.hpp |   2 +-
 include/boost/math/tools/config.hpp           |   1 +
 include/boost/math/tools/minima.hpp           |  32 ++-
 include/boost/math/tools/utility.hpp          |  69 +++++++
 test/cuda_jamfile                             |  91 +++++++++
 test/nvrtc_jamfile                            |  91 +++++++++
 test/sycl_jamfile                             |  13 ++
 test/test_inverse_gaussian.cpp                |   8 +-
 test/test_inverse_gaussian_cdf_double.cu      | 110 ++++++++++
 test/test_inverse_gaussian_cdf_float.cu       | 110 ++++++++++
 ...test_inverse_gaussian_cdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 .../test_inverse_gaussian_cdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_inverse_gaussian_pdf_double.cu      | 110 ++++++++++
 test/test_inverse_gaussian_pdf_float.cu       | 110 ++++++++++
 ...test_inverse_gaussian_pdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 .../test_inverse_gaussian_pdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_inverse_gaussian_quan_double.cu     | 110 ++++++++++
 test/test_inverse_gaussian_quan_float.cu      | 110 ++++++++++
 ...est_inverse_gaussian_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...test_inverse_gaussian_quan_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_lognormal.cpp                       |   7 +-
 test/test_lognormal_cdf_double.cu             | 110 ++++++++++
 test/test_lognormal_cdf_float.cu              | 110 ++++++++++
 test/test_lognormal_cdf_nvrtc_double.cpp      | 191 ++++++++++++++++++
 test/test_lognormal_cdf_nvrtc_float.cpp       | 191 ++++++++++++++++++
 test/test_lognormal_pdf_double.cu             | 110 ++++++++++
 test/test_lognormal_pdf_float.cu              | 110 ++++++++++
 test/test_lognormal_pdf_nvrtc_double.cpp      | 191 ++++++++++++++++++
 test/test_lognormal_pdf_nvrtc_float.cpp       | 191 ++++++++++++++++++
 test/test_lognormal_quan_double.cu            | 110 ++++++++++
 test/test_lognormal_quan_float.cu             | 110 ++++++++++
 test/test_lognormal_quan_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_lognormal_quan_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_nc_beta.cpp                         |   9 +
 test/test_nc_beta.hpp                         |   4 +-
 test/test_nc_beta_cdf_double.cu               | 110 ++++++++++
 test/test_nc_beta_cdf_float.cu                | 110 ++++++++++
 test/test_nc_beta_cdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_nc_beta_cdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_nc_beta_pdf_double.cu               | 110 ++++++++++
 test/test_nc_beta_pdf_float.cu                | 110 ++++++++++
 test/test_nc_beta_pdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_nc_beta_pdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_nc_beta_quan_double.cu              | 110 ++++++++++
 test/test_nc_beta_quan_float.cu               | 110 ++++++++++
 test/test_nc_beta_quan_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_nc_beta_quan_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_nc_chi_squared.cpp                  |  14 +-
 test/test_nc_chi_squared.hpp                  |   8 +-
 test/test_nc_chi_squared_cdf_double.cu        | 110 ++++++++++
 test/test_nc_chi_squared_cdf_float.cu         | 110 ++++++++++
 test/test_nc_chi_squared_cdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_nc_chi_squared_cdf_nvrtc_float.cpp  | 191 ++++++++++++++++++
 test/test_nc_chi_squared_pdf_double.cu        | 110 ++++++++++
 test/test_nc_chi_squared_pdf_float.cu         | 110 ++++++++++
 test/test_nc_chi_squared_pdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_nc_chi_squared_pdf_nvrtc_float.cpp  | 191 ++++++++++++++++++
 test/test_nc_chi_squared_quan_double.cu       | 110 ++++++++++
 test/test_nc_chi_squared_quan_float.cu        | 110 ++++++++++
 .../test_nc_chi_squared_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 test/test_nc_chi_squared_quan_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_nc_f.cpp                            |   8 +-
 test/test_nc_f_cdf_double.cu                  | 110 ++++++++++
 test/test_nc_f_cdf_float.cu                   | 110 ++++++++++
 test/test_nc_f_cdf_nvrtc_double.cpp           | 191 ++++++++++++++++++
 test/test_nc_f_cdf_nvrtc_float.cpp            | 191 ++++++++++++++++++
 test/test_nc_f_pdf_double.cu                  | 110 ++++++++++
 test/test_nc_f_pdf_float.cu                   | 110 ++++++++++
 test/test_nc_f_pdf_nvrtc_double.cpp           | 191 ++++++++++++++++++
 test/test_nc_f_pdf_nvrtc_float.cpp            | 191 ++++++++++++++++++
 test/test_nc_f_quan_double.cu                 | 117 +++++++++++
 test/test_nc_f_quan_float.cu                  | 110 ++++++++++
 test/test_nc_f_quan_nvrtc_double.cpp          | 191 ++++++++++++++++++
 test/test_nc_f_quan_nvrtc_float.cpp           | 191 ++++++++++++++++++
 test/test_negative_binomial.cpp               |   6 +-
 test/test_negative_binomial_cdf_double.cu     | 110 ++++++++++
 test/test_negative_binomial_cdf_float.cu      | 110 ++++++++++
 ...est_negative_binomial_cdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...test_negative_binomial_cdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_negative_binomial_pdf_double.cu     | 110 ++++++++++
 test/test_negative_binomial_pdf_float.cu      | 110 ++++++++++
 ...est_negative_binomial_pdf_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...test_negative_binomial_pdf_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_negative_binomial_quan_double.cu    | 110 ++++++++++
 test/test_negative_binomial_quan_float.cu     | 110 ++++++++++
 ...st_negative_binomial_quan_nvrtc_double.cpp | 191 ++++++++++++++++++
 ...est_negative_binomial_quan_nvrtc_float.cpp | 191 ++++++++++++++++++
 test/test_normal.cpp                          |  11 +-
 test/test_normal_cdf_double.cu                | 110 ++++++++++
 test/test_normal_cdf_float.cu                 | 110 ++++++++++
 test/test_normal_cdf_nvrtc_double.cpp         | 191 ++++++++++++++++++
 test/test_normal_cdf_nvrtc_float.cpp          | 191 ++++++++++++++++++
 test/test_normal_pdf_double.cu                | 110 ++++++++++
 test/test_normal_pdf_float.cu                 | 110 ++++++++++
 test/test_normal_pdf_nvrtc_double.cpp         | 191 ++++++++++++++++++
 test/test_normal_pdf_nvrtc_float.cpp          | 191 ++++++++++++++++++
 test/test_normal_quan_double.cu               | 110 ++++++++++
 test/test_normal_quan_float.cu                | 110 ++++++++++
 test/test_normal_quan_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_normal_quan_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_pareto.cpp                          |  10 +-
 test/test_pareto_cdf_double.cu                | 110 ++++++++++
 test/test_pareto_cdf_float.cu                 | 110 ++++++++++
 test/test_pareto_cdf_nvrtc_double.cpp         | 191 ++++++++++++++++++
 test/test_pareto_cdf_nvrtc_float.cpp          | 191 ++++++++++++++++++
 test/test_pareto_pdf_double.cu                | 110 ++++++++++
 test/test_pareto_pdf_float.cu                 | 110 ++++++++++
 test/test_pareto_pdf_nvrtc_double.cpp         | 191 ++++++++++++++++++
 test/test_pareto_pdf_nvrtc_float.cpp          | 191 ++++++++++++++++++
 test/test_pareto_quan_double.cu               | 110 ++++++++++
 test/test_pareto_quan_float.cu                | 110 ++++++++++
 test/test_pareto_quan_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_pareto_quan_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_poisson.cpp                         |  12 +-
 test/test_poisson_cdf_double.cu               | 110 ++++++++++
 test/test_poisson_cdf_float.cu                | 110 ++++++++++
 test/test_poisson_cdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_poisson_cdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_poisson_pdf_double.cu               | 110 ++++++++++
 test/test_poisson_pdf_float.cu                | 110 ++++++++++
 test/test_poisson_pdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_poisson_pdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_poisson_quan_double.cu              | 110 ++++++++++
 test/test_poisson_quan_float.cu               | 110 ++++++++++
 test/test_poisson_quan_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_poisson_quan_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_rayleigh.cpp                        |   9 +-
 test/test_rayleigh_cdf_double.cu              | 110 ++++++++++
 test/test_rayleigh_cdf_float.cu               | 110 ++++++++++
 test/test_rayleigh_cdf_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_rayleigh_cdf_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_rayleigh_pdf_double.cu              | 110 ++++++++++
 test/test_rayleigh_pdf_float.cu               | 110 ++++++++++
 test/test_rayleigh_pdf_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_rayleigh_pdf_nvrtc_float.cpp        | 191 ++++++++++++++++++
 test/test_rayleigh_quan_double.cu             | 110 ++++++++++
 test/test_rayleigh_quan_float.cu              | 109 ++++++++++
 test/test_rayleigh_quan_nvrtc_double.cpp      | 191 ++++++++++++++++++
 test/test_rayleigh_quan_nvrtc_float.cpp       | 191 ++++++++++++++++++
 test/test_students_t.cpp                      |  14 +-
 test/test_students_t_cdf_double.cu            | 109 ++++++++++
 test/test_students_t_cdf_float.cu             | 109 ++++++++++
 test/test_students_t_cdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_students_t_cdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_students_t_pdf_double.cu            | 109 ++++++++++
 test/test_students_t_pdf_float.cu             | 109 ++++++++++
 test/test_students_t_pdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_students_t_pdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_students_t_quan_double.cu           | 109 ++++++++++
 test/test_students_t_quan_float.cu            | 109 ++++++++++
 test/test_students_t_quan_nvrtc_double.cpp    | 191 ++++++++++++++++++
 test/test_students_t_quan_nvrtc_float.cpp     | 191 ++++++++++++++++++
 test/test_triangular.cpp                      |  12 +-
 test/test_triangular_cdf_double.cu            | 113 +++++++++++
 test/test_triangular_cdf_float.cu             | 113 +++++++++++
 test/test_triangular_cdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_triangular_cdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_triangular_pdf_double.cu            | 113 +++++++++++
 test/test_triangular_pdf_float.cu             | 113 +++++++++++
 test/test_triangular_pdf_nvrtc_double.cpp     | 191 ++++++++++++++++++
 test/test_triangular_pdf_nvrtc_float.cpp      | 191 ++++++++++++++++++
 test/test_triangular_quan_double.cu           | 113 +++++++++++
 test/test_triangular_quan_float.cu            | 113 +++++++++++
 test/test_triangular_quan_nvrtc_double.cpp    | 191 ++++++++++++++++++
 test/test_triangular_quan_nvrtc_float.cpp     | 191 ++++++++++++++++++
 test/test_uniform.cpp                         |   9 +-
 test/test_uniform_cdf_double.cu               | 113 +++++++++++
 test/test_uniform_cdf_float.cu                | 113 +++++++++++
 test/test_uniform_cdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_uniform_cdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_uniform_pdf_double.cu               | 113 +++++++++++
 test/test_uniform_pdf_float.cu                | 113 +++++++++++
 test/test_uniform_pdf_nvrtc_double.cpp        | 191 ++++++++++++++++++
 test/test_uniform_pdf_nvrtc_float.cpp         | 191 ++++++++++++++++++
 test/test_uniform_quan_double.cu              | 113 +++++++++++
 test/test_uniform_quan_float.cu               | 113 +++++++++++
 test/test_uniform_quan_nvrtc_double.cpp       | 191 ++++++++++++++++++
 test/test_uniform_quan_nvrtc_float.cpp        | 191 ++++++++++++++++++
 211 files changed, 24666 insertions(+), 701 deletions(-)
 create mode 100644 include/boost/math/tools/utility.hpp
 create mode 100644 test/test_inverse_gaussian_cdf_double.cu
 create mode 100644 test/test_inverse_gaussian_cdf_float.cu
 create mode 100644 test/test_inverse_gaussian_cdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gaussian_cdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_gaussian_pdf_double.cu
 create mode 100644 test/test_inverse_gaussian_pdf_float.cu
 create mode 100644 test/test_inverse_gaussian_pdf_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gaussian_pdf_nvrtc_float.cpp
 create mode 100644 test/test_inverse_gaussian_quan_double.cu
 create mode 100644 test/test_inverse_gaussian_quan_float.cu
 create mode 100644 test/test_inverse_gaussian_quan_nvrtc_double.cpp
 create mode 100644 test/test_inverse_gaussian_quan_nvrtc_float.cpp
 create mode 100644 test/test_lognormal_cdf_double.cu
 create mode 100644 test/test_lognormal_cdf_float.cu
 create mode 100644 test/test_lognormal_cdf_nvrtc_double.cpp
 create mode 100644 test/test_lognormal_cdf_nvrtc_float.cpp
 create mode 100644 test/test_lognormal_pdf_double.cu
 create mode 100644 test/test_lognormal_pdf_float.cu
 create mode 100644 test/test_lognormal_pdf_nvrtc_double.cpp
 create mode 100644 test/test_lognormal_pdf_nvrtc_float.cpp
 create mode 100644 test/test_lognormal_quan_double.cu
 create mode 100644 test/test_lognormal_quan_float.cu
 create mode 100644 test/test_lognormal_quan_nvrtc_double.cpp
 create mode 100644 test/test_lognormal_quan_nvrtc_float.cpp
 create mode 100644 test/test_nc_beta_cdf_double.cu
 create mode 100644 test/test_nc_beta_cdf_float.cu
 create mode 100644 test/test_nc_beta_cdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_beta_cdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_beta_pdf_double.cu
 create mode 100644 test/test_nc_beta_pdf_float.cu
 create mode 100644 test/test_nc_beta_pdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_beta_pdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_beta_quan_double.cu
 create mode 100644 test/test_nc_beta_quan_float.cu
 create mode 100644 test/test_nc_beta_quan_nvrtc_double.cpp
 create mode 100644 test/test_nc_beta_quan_nvrtc_float.cpp
 create mode 100644 test/test_nc_chi_squared_cdf_double.cu
 create mode 100644 test/test_nc_chi_squared_cdf_float.cu
 create mode 100644 test/test_nc_chi_squared_cdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_chi_squared_cdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_chi_squared_pdf_double.cu
 create mode 100644 test/test_nc_chi_squared_pdf_float.cu
 create mode 100644 test/test_nc_chi_squared_pdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_chi_squared_pdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_chi_squared_quan_double.cu
 create mode 100644 test/test_nc_chi_squared_quan_float.cu
 create mode 100644 test/test_nc_chi_squared_quan_nvrtc_double.cpp
 create mode 100644 test/test_nc_chi_squared_quan_nvrtc_float.cpp
 create mode 100644 test/test_nc_f_cdf_double.cu
 create mode 100644 test/test_nc_f_cdf_float.cu
 create mode 100644 test/test_nc_f_cdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_f_cdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_f_pdf_double.cu
 create mode 100644 test/test_nc_f_pdf_float.cu
 create mode 100644 test/test_nc_f_pdf_nvrtc_double.cpp
 create mode 100644 test/test_nc_f_pdf_nvrtc_float.cpp
 create mode 100644 test/test_nc_f_quan_double.cu
 create mode 100644 test/test_nc_f_quan_float.cu
 create mode 100644 test/test_nc_f_quan_nvrtc_double.cpp
 create mode 100644 test/test_nc_f_quan_nvrtc_float.cpp
 create mode 100644 test/test_negative_binomial_cdf_double.cu
 create mode 100644 test/test_negative_binomial_cdf_float.cu
 create mode 100644 test/test_negative_binomial_cdf_nvrtc_double.cpp
 create mode 100644 test/test_negative_binomial_cdf_nvrtc_float.cpp
 create mode 100644 test/test_negative_binomial_pdf_double.cu
 create mode 100644 test/test_negative_binomial_pdf_float.cu
 create mode 100644 test/test_negative_binomial_pdf_nvrtc_double.cpp
 create mode 100644 test/test_negative_binomial_pdf_nvrtc_float.cpp
 create mode 100644 test/test_negative_binomial_quan_double.cu
 create mode 100644 test/test_negative_binomial_quan_float.cu
 create mode 100644 test/test_negative_binomial_quan_nvrtc_double.cpp
 create mode 100644 test/test_negative_binomial_quan_nvrtc_float.cpp
 create mode 100644 test/test_normal_cdf_double.cu
 create mode 100644 test/test_normal_cdf_float.cu
 create mode 100644 test/test_normal_cdf_nvrtc_double.cpp
 create mode 100644 test/test_normal_cdf_nvrtc_float.cpp
 create mode 100644 test/test_normal_pdf_double.cu
 create mode 100644 test/test_normal_pdf_float.cu
 create mode 100644 test/test_normal_pdf_nvrtc_double.cpp
 create mode 100644 test/test_normal_pdf_nvrtc_float.cpp
 create mode 100644 test/test_normal_quan_double.cu
 create mode 100644 test/test_normal_quan_float.cu
 create mode 100644 test/test_normal_quan_nvrtc_double.cpp
 create mode 100644 test/test_normal_quan_nvrtc_float.cpp
 create mode 100644 test/test_pareto_cdf_double.cu
 create mode 100644 test/test_pareto_cdf_float.cu
 create mode 100644 test/test_pareto_cdf_nvrtc_double.cpp
 create mode 100644 test/test_pareto_cdf_nvrtc_float.cpp
 create mode 100644 test/test_pareto_pdf_double.cu
 create mode 100644 test/test_pareto_pdf_float.cu
 create mode 100644 test/test_pareto_pdf_nvrtc_double.cpp
 create mode 100644 test/test_pareto_pdf_nvrtc_float.cpp
 create mode 100644 test/test_pareto_quan_double.cu
 create mode 100644 test/test_pareto_quan_float.cu
 create mode 100644 test/test_pareto_quan_nvrtc_double.cpp
 create mode 100644 test/test_pareto_quan_nvrtc_float.cpp
 create mode 100644 test/test_poisson_cdf_double.cu
 create mode 100644 test/test_poisson_cdf_float.cu
 create mode 100644 test/test_poisson_cdf_nvrtc_double.cpp
 create mode 100644 test/test_poisson_cdf_nvrtc_float.cpp
 create mode 100644 test/test_poisson_pdf_double.cu
 create mode 100644 test/test_poisson_pdf_float.cu
 create mode 100644 test/test_poisson_pdf_nvrtc_double.cpp
 create mode 100644 test/test_poisson_pdf_nvrtc_float.cpp
 create mode 100644 test/test_poisson_quan_double.cu
 create mode 100644 test/test_poisson_quan_float.cu
 create mode 100644 test/test_poisson_quan_nvrtc_double.cpp
 create mode 100644 test/test_poisson_quan_nvrtc_float.cpp
 create mode 100644 test/test_rayleigh_cdf_double.cu
 create mode 100644 test/test_rayleigh_cdf_float.cu
 create mode 100644 test/test_rayleigh_cdf_nvrtc_double.cpp
 create mode 100644 test/test_rayleigh_cdf_nvrtc_float.cpp
 create mode 100644 test/test_rayleigh_pdf_double.cu
 create mode 100644 test/test_rayleigh_pdf_float.cu
 create mode 100644 test/test_rayleigh_pdf_nvrtc_double.cpp
 create mode 100644 test/test_rayleigh_pdf_nvrtc_float.cpp
 create mode 100644 test/test_rayleigh_quan_double.cu
 create mode 100644 test/test_rayleigh_quan_float.cu
 create mode 100644 test/test_rayleigh_quan_nvrtc_double.cpp
 create mode 100644 test/test_rayleigh_quan_nvrtc_float.cpp
 create mode 100644 test/test_students_t_cdf_double.cu
 create mode 100644 test/test_students_t_cdf_float.cu
 create mode 100644 test/test_students_t_cdf_nvrtc_double.cpp
 create mode 100644 test/test_students_t_cdf_nvrtc_float.cpp
 create mode 100644 test/test_students_t_pdf_double.cu
 create mode 100644 test/test_students_t_pdf_float.cu
 create mode 100644 test/test_students_t_pdf_nvrtc_double.cpp
 create mode 100644 test/test_students_t_pdf_nvrtc_float.cpp
 create mode 100644 test/test_students_t_quan_double.cu
 create mode 100644 test/test_students_t_quan_float.cu
 create mode 100644 test/test_students_t_quan_nvrtc_double.cpp
 create mode 100644 test/test_students_t_quan_nvrtc_float.cpp
 create mode 100644 test/test_triangular_cdf_double.cu
 create mode 100644 test/test_triangular_cdf_float.cu
 create mode 100644 test/test_triangular_cdf_nvrtc_double.cpp
 create mode 100644 test/test_triangular_cdf_nvrtc_float.cpp
 create mode 100644 test/test_triangular_pdf_double.cu
 create mode 100644 test/test_triangular_pdf_float.cu
 create mode 100644 test/test_triangular_pdf_nvrtc_double.cpp
 create mode 100644 test/test_triangular_pdf_nvrtc_float.cpp
 create mode 100644 test/test_triangular_quan_double.cu
 create mode 100644 test/test_triangular_quan_float.cu
 create mode 100644 test/test_triangular_quan_nvrtc_double.cpp
 create mode 100644 test/test_triangular_quan_nvrtc_float.cpp
 create mode 100644 test/test_uniform_cdf_double.cu
 create mode 100644 test/test_uniform_cdf_float.cu
 create mode 100644 test/test_uniform_cdf_nvrtc_double.cpp
 create mode 100644 test/test_uniform_cdf_nvrtc_float.cpp
 create mode 100644 test/test_uniform_pdf_double.cu
 create mode 100644 test/test_uniform_pdf_float.cu
 create mode 100644 test/test_uniform_pdf_nvrtc_double.cpp
 create mode 100644 test/test_uniform_pdf_nvrtc_float.cpp
 create mode 100644 test/test_uniform_quan_double.cu
 create mode 100644 test/test_uniform_quan_float.cu
 create mode 100644 test/test_uniform_quan_nvrtc_double.cpp
 create mode 100644 test/test_uniform_quan_nvrtc_float.cpp

diff --git a/doc/distributions/inverse_gaussian.qbk b/doc/distributions/inverse_gaussian.qbk
index 6187a3835b..99ca4d7c25 100644
--- a/doc/distributions/inverse_gaussian.qbk
+++ b/doc/distributions/inverse_gaussian.qbk
@@ -12,11 +12,11 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
 
-      inverse_gaussian_distribution(RealType mean = 1, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED inverse_gaussian_distribution(RealType mean = 1, RealType scale = 1);
 
-      RealType mean()const; // mean default 1.
-      RealType scale()const; // Optional scale, default 1 (unscaled).
-      RealType shape()const; // Shape = scale/mean.
+      BOOST_MATH_GPU_ENABLED RealType mean()const; // mean default 1.
+      BOOST_MATH_GPU_ENABLED RealType scale()const; // Optional scale, default 1 (unscaled).
+      BOOST_MATH_GPU_ENABLED RealType shape()const; // Shape = scale/mean.
    };
    typedef inverse_gaussian_distribution<double> inverse_gaussian;
 
@@ -90,7 +90,7 @@ Another related parameterisation, the __wald_distrib (where mean [mu] is unity)
 
 [h4 Member Functions]
 
-   inverse_gaussian_distribution(RealType df = 1, RealType scale = 1); // optionally scaled.
+   BOOST_MATH_GPU_ENABLED inverse_gaussian_distribution(RealType df = 1, RealType scale = 1); // optionally scaled.
 
 Constructs an inverse_gaussian distribution with [mu] mean,
 and scale [lambda], with both default values 1.
@@ -98,11 +98,11 @@ and scale [lambda], with both default values 1.
 Requires that both the mean [mu] parameter and scale [lambda] are greater than zero,
 otherwise calls __domain_error.
 
-   RealType mean()const; 
+   BOOST_MATH_GPU_ENABLED RealType mean()const; 
    
 Returns the mean [mu] parameter of this distribution.
 
-   RealType scale()const; 
+   BOOST_MATH_GPU_ENABLED RealType scale()const; 
    
 Returns the scale [lambda] parameter of this distribution.
 
@@ -110,6 +110,8 @@ Returns the scale [lambda] parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variate is \[0,+[infin]).
 [note Unlike some definitions, this implementation supports a random variate 
diff --git a/doc/distributions/lognormal.qbk b/doc/distributions/lognormal.qbk
index 6e76043570..901b59ed82 100644
--- a/doc/distributions/lognormal.qbk
+++ b/doc/distributions/lognormal.qbk
@@ -17,10 +17,10 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      lognormal_distribution(RealType location = 0, RealType scale = 1);
+      BOOST_MATH_GPU_ENABLED lognormal_distribution(RealType location = 0, RealType scale = 1);
       // Accessors:
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
    
    }} // namespaces
@@ -51,7 +51,7 @@ The next graph illustrates the effect of the scale parameter on the PDF:
 
 [h4 Member Functions]
 
-   lognormal_distribution(RealType location = 0, RealType scale = 1);
+   BOOST_MATH_GPU_ENABLED lognormal_distribution(RealType location = 0, RealType scale = 1);
    
 Constructs a lognormal distribution with location /location/ and 
 scale /scale/.
@@ -65,11 +65,11 @@ logarithm of the random variate.
 Requires that the scale parameter is greater than zero, otherwise calls
 __domain_error.
 
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
    
 Returns the /location/ parameter of this distribution.
    
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
       
 Returns the /scale/ parameter of this distribution.
 
@@ -77,6 +77,8 @@ Returns the /scale/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0,+[infin]\].
 
diff --git a/doc/distributions/nc_beta.qbk b/doc/distributions/nc_beta.qbk
index 8e2c816559..478b545020 100644
--- a/doc/distributions/nc_beta.qbk
+++ b/doc/distributions/nc_beta.qbk
@@ -18,14 +18,14 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_beta_distribution(RealType alpha, RealType beta, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_beta_distribution(RealType alpha, RealType beta, RealType lambda);
 
       // Accessor to shape parameters:
-      RealType alpha()const;
-      RealType beta()const;
+      BOOST_MATH_GPU_ENABLED RealType alpha()const;
+      BOOST_MATH_GPU_ENABLED RealType beta()const;
 
       // Accessor to non-centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
    };
 
    }} // namespaces
@@ -59,22 +59,22 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_beta_distribution(RealType a, RealType b, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_beta_distribution(RealType a, RealType b, RealType lambda);
 
 Constructs a noncentral beta distribution with shape parameters /a/ and /b/
 and non-centrality parameter /lambda/.
 
 Requires a > 0, b > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType alpha()const;
+      BOOST_MATH_GPU_ENABLED RealType alpha()const;
 
 Returns the parameter /a/ from which this object was constructed.
 
-      RealType beta()const;
+      BOOST_MATH_GPU_ENABLED RealType beta()const;
 
 Returns the parameter /b/ from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
 Returns the parameter /lambda/ from which this object was constructed.
 
@@ -83,6 +83,8 @@ Returns the parameter /lambda/ from which this object was constructed.
 Most of the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 are supported: __cdf, __pdf, __quantile, __mean, __variance, __sd,
 __median, __mode, __hazard, __chf, __range and __support.
+For this distribution these functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 Mean and variance are implemented using hypergeometric pfq functions and relations given in
 [@http://reference.wolfram.com/mathematica/ref/NoncentralBetaDistribution.html Wolfram Noncentral Beta Distribution].
diff --git a/doc/distributions/nc_chi_squared.qbk b/doc/distributions/nc_chi_squared.qbk
index 72235db6a3..9ab0f6f8d2 100644
--- a/doc/distributions/nc_chi_squared.qbk
+++ b/doc/distributions/nc_chi_squared.qbk
@@ -18,22 +18,22 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_chi_squared_distribution(RealType v, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_chi_squared_distribution(RealType v, RealType lambda);
 
       // Accessor to degrees of freedom parameter v:
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
       // Accessor to non centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
       // Parameter finders:
-      static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
       template <class A, class B, class C>
-      static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
 
-      static RealType find_non_centrality(RealType v, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(RealType v, RealType x, RealType p);
       template <class A, class B, class C>
-      static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
    };
 
    }} // namespaces
@@ -70,43 +70,42 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_chi_squared_distribution(RealType v, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_chi_squared_distribution(RealType v, RealType lambda);
 
 Constructs a Chi-Squared distribution with [nu] degrees of freedom
 and non-centrality parameter /lambda/.
 
 Requires [nu] > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
 Returns the parameter [nu] from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
 
 Returns the parameter /lambda/ from which this object was constructed.
 
-
-   static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(RealType lambda, RealType x, RealType p);
 
 This function returns the number of degrees of freedom [nu] such that:
 `cdf(non_central_chi_squared<RealType, Policy>(v, lambda), x) == p`
 
-   template <class A, class B, class C>
-   static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
+      template <class A, class B, class C>
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c);
 
 When called with argument `boost::math::complement(lambda, x, q)`
 this function returns the number of degrees of freedom [nu] such that:
 
 `cdf(complement(non_central_chi_squared<RealType, Policy>(v, lambda), x)) == q`.
 
-   static RealType find_non_centrality(RealType v, RealType x, RealType p);
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(RealType v, RealType x, RealType p);
 
 This function returns the non centrality parameter /lambda/ such that:
 
 `cdf(non_central_chi_squared<RealType, Policy>(v, lambda), x) == p`
 
-   template <class A, class B, class C>
-   static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
+      template <class A, class B, class C>
+      BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(const complemented3_type<A,B,C>& c);
 
 When called with argument `boost::math::complement(v, x, q)`
 this function returns the non centrality parameter /lambda/ such that:
@@ -117,6 +116,8 @@ this function returns the non centrality parameter /lambda/ such that:
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 
diff --git a/doc/distributions/nc_f.qbk b/doc/distributions/nc_f.qbk
index 6436c34336..d31c8116bc 100644
--- a/doc/distributions/nc_f.qbk
+++ b/doc/distributions/nc_f.qbk
@@ -18,14 +18,14 @@
       typedef Policy    policy_type;
 
       // Constructor:
-      non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
 
       // Accessor to degrees_of_freedom parameters v1 & v2:
-      RealType degrees_of_freedom1()const;
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
 
       // Accessor to non-centrality parameter lambda:
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
    };
    
    }} // namespaces
@@ -55,22 +55,22 @@ for different values of [lambda]:
 
 [h4 Member Functions]
 
-      non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
+      BOOST_MATH_GPU_ENABLED non_central_f_distribution(RealType v1, RealType v2, RealType lambda);
       
 Constructs a non-central beta distribution with parameters /v1/ and /v2/
 and non-centrality parameter /lambda/.
 
 Requires /v1/ > 0, /v2/ > 0 and lambda >= 0, otherwise calls __domain_error.
 
-      RealType degrees_of_freedom1()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const;
       
 Returns the parameter /v1/ from which this object was constructed.
 
-      RealType degrees_of_freedom2()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const;
       
 Returns the parameter /v2/ from which this object was constructed.
 
-      RealType non_centrality()const;
+      BOOST_MATH_GPU_ENABLED RealType non_centrality()const;
       
 Returns the non-centrality parameter /lambda/ from which this object was constructed.
 
@@ -78,6 +78,8 @@ Returns the non-centrality parameter /lambda/ from which this object was constru
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, +[infin]\].
 
diff --git a/doc/distributions/negative_binomial.qbk b/doc/distributions/negative_binomial.qbk
index ee61beef3d..5a23ce23aa 100644
--- a/doc/distributions/negative_binomial.qbk
+++ b/doc/distributions/negative_binomial.qbk
@@ -17,28 +17,28 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Constructor from successes and success_fraction:
-      negative_binomial_distribution(RealType r, RealType p);
+      BOOST_MATH_GPU_ENABLED negative_binomial_distribution(RealType r, RealType p);
 
       // Parameter accessors:
-      RealType success_fraction() const;
-      RealType successes() const;
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const;
+      BOOST_MATH_GPU_ENABLED RealType successes() const;
 
       // Bounds on success fraction:
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability); // alpha
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
          RealType trials,
          RealType successes,
          RealType probability); // alpha
 
       // Estimate min/max number of trials:
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
          RealType k,     // Number of failures.
          RealType p,     // Success fraction.
          RealType probability); // Probability threshold alpha.
@@ -112,7 +112,7 @@ poisson([lambda]) = lim [sub r [rarr] [infin]] negative_binomial(r, r / ([lambda
 
 [h5 Construct]
 
-   negative_binomial_distribution(RealType r, RealType p);
+   BOOST_MATH_GPU_ENABLED negative_binomial_distribution(RealType r, RealType p);
 
 Constructor: /r/ is the total number of successes, /p/ is the
 probability of success of a single trial.
@@ -121,11 +121,11 @@ Requires: `r > 0` and `0 <= p <= 1`.
 
 [h5 Accessors]
 
-   RealType success_fraction() const; // successes / trials (0 <= p <= 1)
+   BOOST_MATH_GPU_ENABLED RealType success_fraction() const; // successes / trials (0 <= p <= 1)
 
 Returns the parameter /p/ from which this distribution was constructed.
 
-   RealType successes() const; // required successes (r > 0)
+   BOOST_MATH_GPU_ENABLED RealType successes() const; // required successes (r > 0)
 
 Returns the parameter /r/ from which this distribution was constructed.
 
@@ -134,7 +134,7 @@ see __binomial_distrib for more discussion.
 
 [h5 Lower Bound on Parameter p]
 
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
         RealType failures,
         RealType successes,
         RealType probability) // (0 <= alpha <= 1), 0.05 equivalent to 95% confidence.
@@ -170,7 +170,7 @@ Computational statistics and data analysis, 2005, vol. 48, no3, 605-621].
 
 [h5 Upper Bound on Parameter p]
 
-   static RealType find_upper_bound_on_p(
+   BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
       RealType trials,
       RealType successes,
       RealType alpha); // (0 <= alpha <= 1), 0.05 equivalent to 95% confidence.
@@ -206,7 +206,7 @@ Computational statistics and data analysis, 2005, vol. 48, no3, 605-621].
 
 [h5 Estimating Number of Trials to Ensure at Least a Certain Number of Failures]
 
-   static RealType find_minimum_number_of_trials(
+   BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
       RealType k,     // number of failures.
       RealType p,     // success fraction.
       RealType alpha); // probability threshold (0.05 equivalent to 95%).
@@ -236,7 +236,7 @@ of observing k failures or fewer.
 
 [h5 Estimating Number of Trials to Ensure a Maximum Number of Failures or Less]
 
-   static RealType find_maximum_number_of_trials(
+   BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
       RealType k,     // number of failures.
       RealType p,     // success fraction.
       RealType alpha); // probability threshold (0.05 equivalent to 95%).
@@ -266,6 +266,8 @@ of observing more than k failures.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 However it's worth taking a moment to define what these actually mean in
 the context of this distribution:
diff --git a/doc/distributions/normal.qbk b/doc/distributions/normal.qbk
index eefe4e967b..8e0f0c8fba 100644
--- a/doc/distributions/normal.qbk
+++ b/doc/distributions/normal.qbk
@@ -17,13 +17,13 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      normal_distribution(RealType mean = 0, RealType sd = 1);
+      BOOST_MATH_GPU_ENABLED normal_distribution(RealType mean = 0, RealType sd = 1);
       // Accessors:
-      RealType mean()const; // location.
-      RealType standard_deviation()const; // scale.
+      BOOST_MATH_GPU_ENABLED RealType mean()const; // location.
+      BOOST_MATH_GPU_ENABLED RealType standard_deviation()const; // scale.
       // Synonyms, provided to allow generic use of find_location and find_scale.
-      RealType location()const;
-      RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType location()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
    };
 
    }} // namespaces
@@ -53,20 +53,20 @@ and illustrated by this graph
 
 [h4 Member Functions]
 
-   normal_distribution(RealType mean = 0, RealType sd = 1);
+   BOOST_MATH_GPU_ENABLED normal_distribution(RealType mean = 0, RealType sd = 1);
 
 Constructs a normal distribution with mean /mean/ and
 standard deviation /sd/.
 
 Requires /sd/ > 0, otherwise __domain_error is called.
 
-   RealType mean()const;
-   RealType location()const;
+   BOOST_MATH_GPU_ENABLED RealType mean()const;
+   BOOST_MATH_GPU_ENABLED RealType location()const;
 
 both return the /mean/ of this distribution.
 
-   RealType standard_deviation()const;
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType standard_deviation()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 both return the /standard deviation/ of this distribution.
 (Redundant location and scale function are provided to match other similar distributions,
@@ -76,6 +76,8 @@ allowing the functions find_location and find_scale to be used generically).
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[-[max_value], +[min_value]\].
 However, the pdf of +[infin] and -[infin] = 0 is also supported,
diff --git a/doc/distributions/pareto.qbk b/doc/distributions/pareto.qbk
index 6a89b0dbc5..0161282ec9 100644
--- a/doc/distributions/pareto.qbk
+++ b/doc/distributions/pareto.qbk
@@ -17,10 +17,10 @@
    public:
       typedef RealType value_type;
       // Constructor:
-      pareto_distribution(RealType scale = 1, RealType shape = 1)
+      BOOST_MATH_GPU_ENABLED pareto_distribution(RealType scale = 1, RealType shape = 1)
       // Accessors:
-      RealType scale()const;
-      RealType shape()const;
+      BOOST_MATH_GPU_ENABLED RealType scale()const;
+      BOOST_MATH_GPU_ENABLED RealType shape()const;
    };
 
    }} // namespaces
@@ -50,7 +50,7 @@ And this graph illustrates how the PDF varies with the shape parameter [alpha]:
 
 [h4 Member Functions]
 
-   pareto_distribution(RealType scale = 1, RealType shape = 1);
+   BOOST_MATH_GPU_ENABLED pareto_distribution(RealType scale = 1, RealType shape = 1);
 
 Constructs a [@http://en.wikipedia.org/wiki/pareto_distribution
 pareto distribution] with shape /shape/ and scale /scale/.
@@ -58,11 +58,11 @@ pareto distribution] with shape /shape/ and scale /scale/.
 Requires that the /shape/ and /scale/ parameters are both greater than zero,
 otherwise calls __domain_error.
 
-   RealType scale()const;
+   BOOST_MATH_GPU_ENABLED RealType scale()const;
 
 Returns the /scale/ parameter of this distribution.
 
-   RealType shape()const;
+   BOOST_MATH_GPU_ENABLED RealType shape()const;
 
 Returns the /shape/ parameter of this distribution.
 
@@ -70,6 +70,8 @@ Returns the /shape/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The supported domain of the random variable is \[scale, [infin]\].
 
diff --git a/doc/distributions/poisson.qbk b/doc/distributions/poisson.qbk
index 01cfb13cc5..533a6d6bad 100644
--- a/doc/distributions/poisson.qbk
+++ b/doc/distributions/poisson.qbk
@@ -17,8 +17,8 @@
     typedef RealType value_type;
     typedef Policy   policy_type;
     
-    poisson_distribution(RealType mean = 1); // Constructor.
-    RealType mean()const; // Accessor.
+    BOOST_MATH_GPU_ENABLED poisson_distribution(RealType mean = 1); // Constructor.
+    BOOST_MATH_GPU_ENABLED RealType mean()const; // Accessor.
   }
    
   }} // namespaces boost::math
@@ -47,11 +47,11 @@ The following graph illustrates how the PDF varies with the parameter [lambda]:
 
 [h4 Member Functions]
 
-   poisson_distribution(RealType mean = 1);
+   BOOST_MATH_GPU_ENABLED poisson_distribution(RealType mean = 1);
    
 Constructs a poisson distribution with mean /mean/.
 
-   RealType mean()const;
+   BOOST_MATH_GPU_ENABLED RealType mean()const;
    
 Returns the /mean/ of this distribution.
    
@@ -59,6 +59,8 @@ Returns the /mean/ of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, [infin]\].
 
diff --git a/doc/distributions/rayleigh.qbk b/doc/distributions/rayleigh.qbk
index 609b654da7..a28d5f577b 100644
--- a/doc/distributions/rayleigh.qbk
+++ b/doc/distributions/rayleigh.qbk
@@ -18,9 +18,9 @@
       typedef RealType value_type;
       typedef Policy   policy_type;
       // Construct:
-      rayleigh_distribution(RealType sigma = 1)
+      BOOST_MATH_GPU_ENABLED rayleigh_distribution(RealType sigma = 1)
       // Accessors:
-      RealType sigma()const;
+      BOOST_MATH_GPU_ENABLED RealType sigma()const;
    };
 
    }} // namespaces
@@ -58,7 +58,7 @@ and [@http://en.wikipedia.org/wiki/Weibull_distribution Weibull] distributions a
 
 [h4 Member Functions]
 
-   rayleigh_distribution(RealType sigma = 1);
+   BOOST_MATH_GPU_ENABLED rayleigh_distribution(RealType sigma = 1);
 
 Constructs a [@http://en.wikipedia.org/wiki/Rayleigh_distribution
 Rayleigh distribution] with [sigma] /sigma/.
@@ -66,7 +66,7 @@ Rayleigh distribution] with [sigma] /sigma/.
 Requires that the [sigma] parameter is greater than zero,
 otherwise calls __domain_error.
 
-   RealType sigma()const;
+   BOOST_MATH_GPU_ENABLED RealType sigma()const;
 
 Returns the /sigma/ parameter of this distribution.
 
@@ -74,6 +74,8 @@ Returns the /sigma/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[0, max_value\].
 
diff --git a/doc/distributions/students_t.qbk b/doc/distributions/students_t.qbk
index 9701ce9fca..3396048c5f 100644
--- a/doc/distributions/students_t.qbk
+++ b/doc/distributions/students_t.qbk
@@ -17,13 +17,13 @@
       typedef Policy   policy_type;
 
       // Constructor:
-      students_t_distribution(const RealType& v);
+      BOOST_MATH_GPU_ENABLED students_t_distribution(const RealType& v);
 
       // Accessor:
-      RealType degrees_of_freedom()const;
+      BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
       // degrees of freedom estimation:
-      static RealType find_degrees_of_freedom(
+      BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(
          RealType difference_from_mean,
          RealType alpha,
          RealType beta,
@@ -62,7 +62,7 @@ illustrates how the PDF varies with the degrees of freedom [nu]:
 
 [h4 Member Functions]
 
-   students_t_distribution(const RealType& v);
+   BOOST_MATH_GPU_ENABLED students_t_distribution(const RealType& v);
 
 Constructs a Student's t-distribution with /v/ degrees of freedom.
 
@@ -71,11 +71,11 @@ otherwise calls __domain_error.  Note that
 non-integral degrees of freedom are supported,
 and are meaningful under certain circumstances.
 
-   RealType degrees_of_freedom()const;
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const;
 
 returns the number of degrees of freedom of this distribution.
 
-   static RealType find_degrees_of_freedom(
+   BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(
       RealType difference_from_mean,
       RealType alpha,
       RealType beta,
@@ -110,6 +110,8 @@ NIST Engineering Statistics Handbook].
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \[-[infin], +[infin]\].
 
diff --git a/doc/distributions/triangular.qbk b/doc/distributions/triangular.qbk
index cd48f3310a..f32514f652 100644
--- a/doc/distributions/triangular.qbk
+++ b/doc/distributions/triangular.qbk
@@ -17,12 +17,12 @@
        typedef RealType value_type;
        typedef Policy   policy_type;
 
-       triangular_distribution(RealType lower = -1, RealType mode = 0, RealType upper = 1); // Constructor.
+       BOOST_MATH_GPU_ENABLED triangular_distribution(RealType lower = -1, RealType mode = 0, RealType upper = 1); // Constructor.
           : m_lower(lower), m_mode(mode), m_upper(upper) // Default is -1, 0, +1 symmetric triangular distribution.
        // Accessor functions.
-       RealType lower()const;
-       RealType mode()const;
-       RealType upper()const;
+       BOOST_MATH_GPU_ENABLED RealType lower()const;
+       BOOST_MATH_GPU_ENABLED RealType mode()const;
+       BOOST_MATH_GPU_ENABLED RealType upper()const;
     }; // class triangular_distribution
 
    }} // namespaces
@@ -77,7 +77,7 @@ and cumulative distribution function
 
 [h4 Member Functions]
 
-   triangular_distribution(RealType lower = 0, RealType mode = 0 RealType upper = 1);
+   BOOST_MATH_GPU_ENABLED triangular_distribution(RealType lower = 0, RealType mode = 0 RealType upper = 1);
 
 Constructs a [@http://en.wikipedia.org/wiki/triangular_distribution triangular distribution]
 with lower  /lower/ (a) and upper /upper/ (b).
@@ -99,15 +99,15 @@ So, for example, to compute a variance using __WolframAlpha, use
 
 The parameters of a distribution can be obtained using these member functions:
 
-   RealType lower()const;
+   BOOST_MATH_GPU_ENABLED RealType lower()const;
 
 Returns the ['lower] parameter of this distribution (default -1).
 
-   RealType mode()const;
+   BOOST_MATH_GPU_ENABLED RealType mode()const;
 
 Returns the ['mode] parameter of this distribution (default 0).
 
-   RealType upper()const;
+   BOOST_MATH_GPU_ENABLED RealType upper()const;
 
 Returns the ['upper] parameter of this distribution (default+1).
 
@@ -115,6 +115,8 @@ Returns the ['upper] parameter of this distribution (default+1).
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions] that are generic to all
 distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is \lower\ to \upper\,
 and the supported range is lower <= x <= upper.
diff --git a/doc/distributions/uniform.qbk b/doc/distributions/uniform.qbk
index 58c11735d6..56c965877e 100644
--- a/doc/distributions/uniform.qbk
+++ b/doc/distributions/uniform.qbk
@@ -16,11 +16,11 @@
     public:
        typedef RealType value_type;
 
-       uniform_distribution(RealType lower = 0, RealType upper = 1); // Constructor.
+       BOOST_MATH_GPU_ENABLED uniform_distribution(RealType lower = 0, RealType upper = 1); // Constructor.
           : m_lower(lower), m_upper(upper) // Default is standard uniform distribution.
        // Accessor functions.
-       RealType lower()const;
-       RealType upper()const;
+       BOOST_MATH_GPU_ENABLED RealType lower()const;
+       BOOST_MATH_GPU_ENABLED RealType upper()const;
     }; // class uniform_distribution
    
    }} // namespaces
@@ -66,7 +66,7 @@ Likewise for the CDF:
 
 [h4 Member Functions]
 
-   uniform_distribution(RealType lower = 0, RealType upper = 1);
+   BOOST_MATH_GPU_ENABLED uniform_distribution(RealType lower = 0, RealType upper = 1);
    
 Constructs a [@http://en.wikipedia.org/wiki/uniform_distribution 
 uniform distribution] with lower  /lower/ (a) and upper /upper/ (b).
@@ -74,11 +74,11 @@ uniform distribution] with lower  /lower/ (a) and upper /upper/ (b).
 Requires that the /lower/ and /upper/ parameters are both finite;
 otherwise if infinity or NaN then calls __domain_error.
 
-   RealType lower()const;
+   BOOST_MATH_GPU_ENABLED RealType lower()const;
    
 Returns the /lower/ parameter of this distribution.
    
-   RealType upper()const;
+   BOOST_MATH_GPU_ENABLED RealType upper()const;
       
 Returns the /upper/ parameter of this distribution.
 
@@ -86,6 +86,8 @@ Returns the /upper/ parameter of this distribution.
 
 All the [link math_toolkit.dist_ref.nmp usual non-member accessor functions]
 that are generic to all distributions are supported: __usual_accessors.
+For this distribution all non-member accessor functions are marked with `BOOST_MATH_GPU_ENABLED` and can
+be run on both host and device.
 
 The domain of the random variable is any finite value,
 but the supported range is only /lower/ <= x <= /upper/.
diff --git a/include/boost/math/distributions/detail/common_error_handling.hpp b/include/boost/math/distributions/detail/common_error_handling.hpp
index 9922396d5f..06e3c105bd 100644
--- a/include/boost/math/distributions/detail/common_error_handling.hpp
+++ b/include/boost/math/distributions/detail/common_error_handling.hpp
@@ -11,6 +11,7 @@
 #define BOOST_MATH_DISTRIBUTIONS_COMMON_ERROR_HANDLING_HPP
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/fpclassify.hpp>
 // using boost::math::isfinite;
@@ -187,11 +188,7 @@ BOOST_MATH_GPU_ENABLED inline bool check_non_centrality(
       RealType* result,
       const Policy& pol)
 {
-   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
-   static const RealType upper_limit = static_cast<RealType>((std::numeric_limits<long long>::max)()) - boost::math::policies::get_max_root_iterations<Policy>();
-   #else
-   constexpr RealType upper_limit = static_cast<RealType>(LONG_LONG_MAX) - boost::math::policies::get_max_root_iterations<Policy>();
-   #endif
+   BOOST_MATH_STATIC const RealType upper_limit = static_cast<RealType>((boost::math::numeric_limits<long long>::max)()) - boost::math::policies::get_max_root_iterations<Policy>();
 
    if((ncp < 0) || !(boost::math::isfinite)(ncp) || ncp > upper_limit)
    {
diff --git a/include/boost/math/distributions/detail/generic_mode.hpp b/include/boost/math/distributions/detail/generic_mode.hpp
index 19c8b2af01..9306c815da 100644
--- a/include/boost/math/distributions/detail/generic_mode.hpp
+++ b/include/boost/math/distributions/detail/generic_mode.hpp
@@ -8,19 +8,22 @@
 #ifndef BOOST_MATH_DISTRIBUTIONS_DETAIL_MODE_HPP
 #define BOOST_MATH_DISTRIBUTIONS_DETAIL_MODE_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/tools/minima.hpp> // function minimization for mode
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/distributions/fwd.hpp>
+#include <boost/math/policies/policy.hpp>
 
 namespace boost{ namespace math{ namespace detail{
 
 template <class Dist>
 struct pdf_minimizer
 {
-   pdf_minimizer(const Dist& d)
+   BOOST_MATH_GPU_ENABLED pdf_minimizer(const Dist& d)
       : dist(d) {}
 
-   typename Dist::value_type operator()(const typename Dist::value_type& x)
+   BOOST_MATH_GPU_ENABLED typename Dist::value_type operator()(const typename Dist::value_type& x)
    {
       return -pdf(dist, x);
    }
@@ -29,7 +32,7 @@ struct pdf_minimizer
 };
 
 template <class Dist>
-typename Dist::value_type generic_find_mode(const Dist& dist, typename Dist::value_type guess, const char* function, typename Dist::value_type step = 0)
+BOOST_MATH_GPU_ENABLED typename Dist::value_type generic_find_mode(const Dist& dist, typename Dist::value_type guess, const char* function, typename Dist::value_type step = 0)
 {
    BOOST_MATH_STD_USING
    typedef typename Dist::value_type value_type;
@@ -70,7 +73,7 @@ typename Dist::value_type generic_find_mode(const Dist& dist, typename Dist::val
       v = pdf(dist, lower_bound);
    }while(maxval < v);
 
-   std::uintmax_t max_iter = policies::get_max_root_iterations<policy_type>();
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<policy_type>();
 
    value_type result = tools::brent_find_minima(
       pdf_minimizer<Dist>(dist), 
@@ -90,7 +93,7 @@ typename Dist::value_type generic_find_mode(const Dist& dist, typename Dist::val
 // As above,but confined to the interval [0,1]:
 //
 template <class Dist>
-typename Dist::value_type generic_find_mode_01(const Dist& dist, typename Dist::value_type guess, const char* function)
+BOOST_MATH_GPU_ENABLED typename Dist::value_type generic_find_mode_01(const Dist& dist, typename Dist::value_type guess, const char* function)
 {
    BOOST_MATH_STD_USING
    typedef typename Dist::value_type value_type;
@@ -121,7 +124,7 @@ typename Dist::value_type generic_find_mode_01(const Dist& dist, typename Dist::
       v = pdf(dist, lower_bound);
    }while(maxval < v);
 
-   std::uintmax_t max_iter = policies::get_max_root_iterations<policy_type>();
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<policy_type>();
 
    value_type result = tools::brent_find_minima(
       pdf_minimizer<Dist>(dist), 
diff --git a/include/boost/math/distributions/detail/generic_quantile.hpp b/include/boost/math/distributions/detail/generic_quantile.hpp
index 438ac952f0..917532566f 100644
--- a/include/boost/math/distributions/detail/generic_quantile.hpp
+++ b/include/boost/math/distributions/detail/generic_quantile.hpp
@@ -6,6 +6,10 @@
 #ifndef BOOST_MATH_DISTIBUTIONS_DETAIL_GENERIC_QUANTILE_HPP
 #define BOOST_MATH_DISTIBUTIONS_DETAIL_GENERIC_QUANTILE_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
+
 namespace boost{ namespace math{ namespace detail{
 
 template <class Dist>
@@ -14,10 +18,10 @@ struct generic_quantile_finder
    using value_type = typename Dist::value_type;
    using policy_type = typename Dist::policy_type;
 
-   generic_quantile_finder(const Dist& d, value_type t, bool c)
+   BOOST_MATH_GPU_ENABLED generic_quantile_finder(const Dist& d, value_type t, bool c)
       : dist(d), target(t), comp(c) {}
 
-   value_type operator()(const value_type& x)
+   BOOST_MATH_GPU_ENABLED value_type operator()(const value_type& x)
    {
       return comp ?
          value_type(target - cdf(complement(dist, x)))
@@ -31,7 +35,7 @@ struct generic_quantile_finder
 };
 
 template <class T, class Policy>
-inline T check_range_result(const T& x, const Policy& pol, const char* function)
+BOOST_MATH_GPU_ENABLED inline T check_range_result(const T& x, const Policy& pol, const char* function)
 {
    if((x >= 0) && (x < tools::min_value<T>()))
    {
@@ -49,7 +53,7 @@ inline T check_range_result(const T& x, const Policy& pol, const char* function)
 }
 
 template <class Dist>
-typename Dist::value_type generic_quantile(const Dist& dist, const typename Dist::value_type& p, const typename Dist::value_type& guess, bool comp, const char* function)
+BOOST_MATH_GPU_ENABLED typename Dist::value_type generic_quantile(const Dist& dist, const typename Dist::value_type& p, const typename Dist::value_type& guess, bool comp, const char* function)
 {
    using value_type = typename Dist::value_type;
    using policy_type = typename Dist::policy_type;
@@ -78,8 +82,8 @@ typename Dist::value_type generic_quantile(const Dist& dist, const typename Dist
 
    generic_quantile_finder<Dist> f(dist, p, comp);
    tools::eps_tolerance<value_type> tol(policies::digits<value_type, forwarding_policy>() - 3);
-   std::uintmax_t max_iter = policies::get_max_root_iterations<forwarding_policy>();
-   std::pair<value_type, value_type> ir = tools::bracket_and_solve_root(
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<forwarding_policy>();
+   boost::math::pair<value_type, value_type> ir = tools::bracket_and_solve_root(
       f, guess, value_type(2), true, tol, max_iter, forwarding_policy());
    value_type result = ir.first + (ir.second - ir.first) / 2;
    if(max_iter >= policies::get_max_root_iterations<forwarding_policy>())
diff --git a/include/boost/math/distributions/detail/inv_discrete_quantile.hpp b/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
index f688345b79..ac4a2b2318 100644
--- a/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
+++ b/include/boost/math/distributions/detail/inv_discrete_quantile.hpp
@@ -87,7 +87,7 @@ BOOST_MATH_GPU_ENABLED typename Dist::value_type
    typedef typename Dist::value_type value_type;
    typedef typename Dist::policy_type policy_type;
 
-   static const char* function = "boost::math::do_inverse_discrete_quantile<%1%>";
+   constexpr auto function = "boost::math::do_inverse_discrete_quantile<%1%>";
 
    BOOST_MATH_STD_USING
 
@@ -310,7 +310,11 @@ BOOST_MATH_GPU_ENABLED inline typename Dist::value_type round_to_floor(const Dis
    //
    while(result != 0)
    {
+      #ifdef BOOST_MATH_HAS_GPU_SUPPORT
+      cc = floor(::nextafter(result, -tools::max_value<typename Dist::value_type>()));
+      #else
       cc = floor(float_prior(result));
+      #endif
       if(cc < support(d).first)
          break;
       pp = c ? cdf(complement(d, cc)) : cdf(d, cc);
@@ -343,7 +347,7 @@ BOOST_MATH_GPU_ENABLED inline typename Dist::value_type round_to_ceil(const Dist
    while(true)
    {
       #ifdef BOOST_MATH_HAS_GPU_SUPPORT
-      cc = ceil(nextafter(result, tools::max_value<typename Dist::value_type>()));
+      cc = ceil(::nextafter(result, tools::max_value<typename Dist::value_type>()));
       #else
       cc = ceil(float_next(result));
       #endif
diff --git a/include/boost/math/distributions/inverse_gaussian.hpp b/include/boost/math/distributions/inverse_gaussian.hpp
index b31d1c9257..20d3b6bdd5 100644
--- a/include/boost/math/distributions/inverse_gaussian.hpp
+++ b/include/boost/math/distributions/inverse_gaussian.hpp
@@ -1,6 +1,6 @@
 //  Copyright John Maddock 2010.
 //  Copyright Paul A. Bristow 2010.
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -49,17 +49,17 @@
 
 // http://www.statsci.org/s/inverse_gaussian.s  and http://www.statsci.org/s/inverse_gaussian.html
 
-//#include <boost/math/distributions/fwd.hpp>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/special_functions/erf.hpp> // for erf/erfc.
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/normal.hpp>
 #include <boost/math/distributions/gamma.hpp> // for gamma function
-
 #include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/roots.hpp>
-
-#include <utility>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost{ namespace math{
 
@@ -70,10 +70,10 @@ class inverse_gaussian_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit inverse_gaussian_distribution(RealType l_mean = 1, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED explicit inverse_gaussian_distribution(RealType l_mean = 1, RealType l_scale = 1)
       : m_mean(l_mean), m_scale(l_scale)
    { // Default is a 1,1 inverse_gaussian distribution.
-     static const char* function = "boost::math::inverse_gaussian_distribution<%1%>::inverse_gaussian_distribution";
+     constexpr auto function = "boost::math::inverse_gaussian_distribution<%1%>::inverse_gaussian_distribution";
 
      RealType result;
      detail::check_scale(function, l_scale, &result, Policy());
@@ -81,22 +81,22 @@ class inverse_gaussian_distribution
      detail::check_x_gt0(function, l_mean, &result, Policy());
    }
 
-   RealType mean()const
+   BOOST_MATH_GPU_ENABLED RealType mean()const
    { // alias for location.
       return m_mean; // aka mu
    }
 
    // Synonyms, provided to allow generic use of find_location and find_scale.
-   RealType location()const
+   BOOST_MATH_GPU_ENABLED RealType location()const
    { // location, aka mu.
       return m_mean;
    }
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    { // scale, aka lambda.
       return m_scale;
    }
 
-   RealType shape()const
+   BOOST_MATH_GPU_ENABLED RealType shape()const
    { // shape, aka phi = lambda/mu.
       return m_scale / m_mean;
    }
@@ -119,29 +119,29 @@ inverse_gaussian_distribution(RealType,RealType)->inverse_gaussian_distribution<
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const inverse_gaussian_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const inverse_gaussian_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x, zero to max.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0.), max_value<RealType>()); // - to + max value.
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0.), max_value<RealType>()); // - to + max value.
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const inverse_gaussian_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const inverse_gaussian_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x, zero to max.
   // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0.),  max_value<RealType>()); // - to + max value.
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0.),  max_value<RealType>()); // - to + max value.
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
 { // Probability Density Function
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType scale = dist.scale();
    RealType mean = dist.mean();
    RealType result = 0;
-   static const char* function = "boost::math::pdf(const inverse_gaussian_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const inverse_gaussian_distribution<%1%>&, %1%)";
    if(false == detail::check_scale(function, scale, &result, Policy()))
    {
       return result;
@@ -171,14 +171,14 @@ inline RealType pdf(const inverse_gaussian_distribution<RealType, Policy>& dist,
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
 { // Probability Density Function
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType scale = dist.scale();
    RealType mean = dist.mean();
-   RealType result = -std::numeric_limits<RealType>::infinity();
-   static const char* function = "boost::math::logpdf(const inverse_gaussian_distribution<%1%>&, %1%)";
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
+   constexpr auto function = "boost::math::logpdf(const inverse_gaussian_distribution<%1%>&, %1%)";
    if(false == detail::check_scale(function, scale, &result, Policy()))
    {
       return result;
@@ -198,7 +198,7 @@ inline RealType logpdf(const inverse_gaussian_distribution<RealType, Policy>& di
 
    if (x == 0)
    {
-     return std::numeric_limits<RealType>::quiet_NaN(); // Convenient, even if not defined mathematically. log(0)
+     return boost::math::numeric_limits<RealType>::quiet_NaN(); // Convenient, even if not defined mathematically. log(0)
    }
 
    const RealType two_pi = boost::math::constants::two_pi<RealType>();
@@ -208,13 +208,13 @@ inline RealType logpdf(const inverse_gaussian_distribution<RealType, Policy>& di
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& x)
 { // Cumulative Density Function.
    BOOST_MATH_STD_USING  // for ADL of std functions.
 
    RealType scale = dist.scale();
    RealType mean = dist.mean();
-   static const char* function = "boost::math::cdf(const inverse_gaussian_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const inverse_gaussian_distribution<%1%>&, %1%)";
    RealType result = 0;
    if(false == detail::check_scale(function, scale, &result, Policy()))
    {
@@ -257,11 +257,11 @@ template <class RealType, class Policy>
 struct inverse_gaussian_quantile_functor
 { 
 
-  inverse_gaussian_quantile_functor(const boost::math::inverse_gaussian_distribution<RealType, Policy> dist, RealType const& p)
+  BOOST_MATH_GPU_ENABLED inverse_gaussian_quantile_functor(const boost::math::inverse_gaussian_distribution<RealType, Policy> dist, RealType const& p)
     : distribution(dist), prob(p)
   {
   }
-  boost::math::tuple<RealType, RealType> operator()(RealType const& x)
+  BOOST_MATH_GPU_ENABLED boost::math::tuple<RealType, RealType> operator()(RealType const& x)
   {
     RealType c = cdf(distribution, x);
     RealType fx = c - prob;  // Difference cdf - value - to minimize.
@@ -277,11 +277,11 @@ struct inverse_gaussian_quantile_functor
 template <class RealType, class Policy>
 struct inverse_gaussian_quantile_complement_functor
 { 
-    inverse_gaussian_quantile_complement_functor(const boost::math::inverse_gaussian_distribution<RealType, Policy> dist, RealType const& p)
+  BOOST_MATH_GPU_ENABLED inverse_gaussian_quantile_complement_functor(const boost::math::inverse_gaussian_distribution<RealType, Policy> dist, RealType const& p)
     : distribution(dist), prob(p)
   {
   }
-  boost::math::tuple<RealType, RealType> operator()(RealType const& x)
+  BOOST_MATH_GPU_ENABLED boost::math::tuple<RealType, RealType> operator()(RealType const& x)
   {
     RealType c = cdf(complement(distribution, x));
     RealType fx = c - prob;  // Difference cdf - value - to minimize.
@@ -298,7 +298,7 @@ struct inverse_gaussian_quantile_complement_functor
 namespace detail
 {
   template <class RealType>
-  inline RealType guess_ig(RealType p, RealType mu = 1, RealType lambda = 1)
+  BOOST_MATH_GPU_ENABLED inline RealType guess_ig(RealType p, RealType mu = 1, RealType lambda = 1)
   { // guess at random variate value x for inverse gaussian quantile.
     BOOST_MATH_STD_USING
     using boost::math::policies::policy;
@@ -350,14 +350,14 @@ namespace detail
 } // namespace detail
 
 template <class RealType, class Policy>
-inline RealType quantile(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const inverse_gaussian_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions.
    // No closed form exists so guess and use Newton Raphson iteration.
 
    RealType mean = dist.mean();
    RealType scale = dist.scale();
-   static const char* function = "boost::math::quantile(const inverse_gaussian_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const inverse_gaussian_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(false == detail::check_scale(function, scale, &result, Policy()))
@@ -388,7 +388,7 @@ inline RealType quantile(const inverse_gaussian_distribution<RealType, Policy>&
   // digits used to control how accurate to try to make the result.
   // To allow user to control accuracy versus speed,
   int get_digits = policies::digits<RealType, Policy>();// get digits from policy, 
-  std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>(); // and max iterations.
+  boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>(); // and max iterations.
   using boost::math::tools::newton_raphson_iterate;
   result =
     newton_raphson_iterate(inverse_gaussian_quantile_functor<RealType, Policy>(dist, p), guess, min, max, get_digits, max_iter);
@@ -401,14 +401,14 @@ inline RealType quantile(const inverse_gaussian_distribution<RealType, Policy>&
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<inverse_gaussian_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<inverse_gaussian_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions.
 
    RealType scale = c.dist.scale();
    RealType mean = c.dist.mean();
    RealType x = c.param;
-   static const char* function = "boost::math::cdf(const complement(inverse_gaussian_distribution<%1%>&), %1%)";
+   constexpr auto function = "boost::math::cdf(const complement(inverse_gaussian_distribution<%1%>&), %1%)";
 
    RealType result = 0;
    if(false == detail::check_scale(function, scale, &result, Policy()))
@@ -437,13 +437,13 @@ inline RealType cdf(const complemented2_type<inverse_gaussian_distribution<RealT
 } // cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<inverse_gaussian_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<inverse_gaussian_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType scale = c.dist.scale();
    RealType mean = c.dist.mean();
-   static const char* function = "boost::math::quantile(const complement(inverse_gaussian_distribution<%1%>&), %1%)";
+   constexpr auto function = "boost::math::quantile(const complement(inverse_gaussian_distribution<%1%>&), %1%)";
    RealType result = 0;
    if(false == detail::check_scale(function, scale, &result, Policy()))
       return result;
@@ -464,7 +464,7 @@ inline RealType quantile(const complemented2_type<inverse_gaussian_distribution<
   // int digits = std::numeric_limits<RealType>::digits; // Maximum possible binary digits accuracy for type T.
   // digits used to control how accurate to try to make the result.
   int get_digits = policies::digits<RealType, Policy>();
-  std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+  boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
   using boost::math::tools::newton_raphson_iterate;
   result = newton_raphson_iterate(inverse_gaussian_quantile_complement_functor<RealType, Policy>(c.dist, q), guess, min, max, get_digits, max_iter);
   if (max_iter >= policies::get_max_root_iterations<Policy>())
@@ -476,25 +476,25 @@ inline RealType quantile(const complemented2_type<inverse_gaussian_distribution<
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType mean(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const inverse_gaussian_distribution<RealType, Policy>& dist)
 { // aka mu
    return dist.mean();
 }
 
 template <class RealType, class Policy>
-inline RealType scale(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType scale(const inverse_gaussian_distribution<RealType, Policy>& dist)
 { // aka lambda
    return dist.scale();
 }
 
 template <class RealType, class Policy>
-inline RealType shape(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType shape(const inverse_gaussian_distribution<RealType, Policy>& dist)
 { // aka phi
    return dist.shape();
 }
 
 template <class RealType, class Policy>
-inline RealType standard_deviation(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType standard_deviation(const inverse_gaussian_distribution<RealType, Policy>& dist)
 {
   BOOST_MATH_STD_USING
   RealType scale = dist.scale();
@@ -504,7 +504,7 @@ inline RealType standard_deviation(const inverse_gaussian_distribution<RealType,
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const inverse_gaussian_distribution<RealType, Policy>& dist)
 {
   BOOST_MATH_STD_USING
   RealType scale = dist.scale();
@@ -515,7 +515,7 @@ inline RealType mode(const inverse_gaussian_distribution<RealType, Policy>& dist
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const inverse_gaussian_distribution<RealType, Policy>& dist)
 {
   BOOST_MATH_STD_USING
   RealType scale = dist.scale();
@@ -525,7 +525,7 @@ inline RealType skewness(const inverse_gaussian_distribution<RealType, Policy>&
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const inverse_gaussian_distribution<RealType, Policy>& dist)
 {
   RealType scale = dist.scale();
   RealType  mean = dist.mean();
@@ -534,7 +534,7 @@ inline RealType kurtosis(const inverse_gaussian_distribution<RealType, Policy>&
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const inverse_gaussian_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const inverse_gaussian_distribution<RealType, Policy>& dist)
 {
   RealType scale = dist.scale();
   RealType  mean = dist.mean();
diff --git a/include/boost/math/distributions/lognormal.hpp b/include/boost/math/distributions/lognormal.hpp
index 3c8f576e56..dfc3e4b2a2 100644
--- a/include/boost/math/distributions/lognormal.hpp
+++ b/include/boost/math/distributions/lognormal.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,12 +11,15 @@
 // http://mathworld.wolfram.com/LogNormalDistribution.html
 // http://en.wikipedia.org/wiki/Lognormal_distribution
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/normal.hpp>
 #include <boost/math/special_functions/expm1.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
-
-#include <utility>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/constants/constants.hpp>
 
 namespace boost{ namespace math
 {
@@ -23,7 +27,7 @@ namespace detail
 {
 
   template <class RealType, class Policy>
-  inline bool check_lognormal_x(
+  BOOST_MATH_GPU_ENABLED inline bool check_lognormal_x(
         const char* function,
         RealType const& x,
         RealType* result, const Policy& pol)
@@ -48,7 +52,7 @@ class lognormal_distribution
    typedef RealType value_type;
    typedef Policy policy_type;
 
-   lognormal_distribution(RealType l_location = 0, RealType l_scale = 1)
+   BOOST_MATH_GPU_ENABLED lognormal_distribution(RealType l_location = 0, RealType l_scale = 1)
       : m_location(l_location), m_scale(l_scale)
    {
       RealType result;
@@ -56,12 +60,12 @@ class lognormal_distribution
       detail::check_location("boost::math::lognormal_distribution<%1%>::lognormal_distribution", l_location, &result, Policy());
    }
 
-   RealType location()const
+   BOOST_MATH_GPU_ENABLED RealType location()const
    {
       return m_location;
    }
 
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    {
       return m_scale;
    }
@@ -83,29 +87,29 @@ lognormal_distribution(RealType,RealType)->lognormal_distribution<typename boost
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const lognormal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const lognormal_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x is >0 to +infinity.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const lognormal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const lognormal_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-RealType pdf(const lognormal_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED RealType pdf(const lognormal_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType mu = dist.location();
    RealType sigma = dist.scale();
 
-   static const char* function = "boost::math::pdf(const lognormal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const lognormal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(0 == detail::check_scale(function, sigma, &result, Policy()))
@@ -129,11 +133,11 @@ RealType pdf(const lognormal_distribution<RealType, Policy>& dist, const RealTyp
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const lognormal_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const lognormal_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const lognormal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const lognormal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(0 == detail::check_scale(function, dist.scale(), &result, Policy()))
@@ -151,11 +155,11 @@ inline RealType cdf(const lognormal_distribution<RealType, Policy>& dist, const
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const lognormal_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const lognormal_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const lognormal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const lognormal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(0 == detail::check_scale(function, dist.scale(), &result, Policy()))
@@ -175,11 +179,11 @@ inline RealType quantile(const lognormal_distribution<RealType, Policy>& dist, c
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<lognormal_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<lognormal_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::cdf(const lognormal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const lognormal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(0 == detail::check_scale(function, c.dist.scale(), &result, Policy()))
@@ -197,11 +201,11 @@ inline RealType cdf(const complemented2_type<lognormal_distribution<RealType, Po
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<lognormal_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<lognormal_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
-   static const char* function = "boost::math::quantile(const lognormal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const lognormal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(0 == detail::check_scale(function, c.dist.scale(), &result, Policy()))
@@ -221,7 +225,7 @@ inline RealType quantile(const complemented2_type<lognormal_distribution<RealTyp
 }
 
 template <class RealType, class Policy>
-inline RealType mean(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -238,7 +242,7 @@ inline RealType mean(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType variance(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -255,7 +259,7 @@ inline RealType variance(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -272,7 +276,7 @@ inline RealType mode(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType median(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
    RealType mu = dist.location();
@@ -280,7 +284,7 @@ inline RealType median(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -300,7 +304,7 @@ inline RealType skewness(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -318,7 +322,7 @@ inline RealType kurtosis(const lognormal_distribution<RealType, Policy>& dist)
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const lognormal_distribution<RealType, Policy>& dist)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
@@ -336,9 +340,9 @@ inline RealType kurtosis_excess(const lognormal_distribution<RealType, Policy>&
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const lognormal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const lognormal_distribution<RealType, Policy>& dist)
 {
-   using std::log;
+   BOOST_MATH_STD_USING
    RealType mu = dist.location();
    RealType sigma = dist.scale();
    return mu + log(constants::two_pi<RealType>()*constants::e<RealType>()*sigma*sigma)/2;
diff --git a/include/boost/math/distributions/negative_binomial.hpp b/include/boost/math/distributions/negative_binomial.hpp
index 18eec09939..f520c94803 100644
--- a/include/boost/math/distributions/negative_binomial.hpp
+++ b/include/boost/math/distributions/negative_binomial.hpp
@@ -44,6 +44,10 @@
 #ifndef BOOST_MATH_SPECIAL_NEGATIVE_BINOMIAL_HPP
 #define BOOST_MATH_SPECIAL_NEGATIVE_BINOMIAL_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for ibeta(a, b, x) == Ix(a, b).
 #include <boost/math/distributions/complement.hpp> // complement.
@@ -51,9 +55,7 @@
 #include <boost/math/special_functions/fpclassify.hpp> // isnan.
 #include <boost/math/tools/roots.hpp> // for root finding.
 #include <boost/math/distributions/detail/inv_discrete_quantile.hpp>
-
-#include <limits> // using std::numeric_limits;
-#include <utility>
+#include <boost/math/policies/error_handling.hpp>
 
 #if defined (BOOST_MSVC)
 #  pragma warning(push)
@@ -70,7 +72,7 @@ namespace boost
     {
       // Common error checking routines for negative binomial distribution functions:
       template <class RealType, class Policy>
-      inline bool check_successes(const char* function, const RealType& r, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_successes(const char* function, const RealType& r, RealType* result, const Policy& pol)
       {
         if( !(boost::math::isfinite)(r) || (r <= 0) )
         {
@@ -82,7 +84,7 @@ namespace boost
         return true;
       }
       template <class RealType, class Policy>
-      inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_success_fraction(const char* function, const RealType& p, RealType* result, const Policy& pol)
       {
         if( !(boost::math::isfinite)(p) || (p < 0) || (p > 1) )
         {
@@ -94,13 +96,13 @@ namespace boost
         return true;
       }
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& r, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& r, const RealType& p, RealType* result, const Policy& pol)
       {
         return check_success_fraction(function, p, result, pol)
           && check_successes(function, r, result, pol);
       }
       template <class RealType, class Policy>
-      inline bool check_dist_and_k(const char* function, const RealType& r, const RealType& p, RealType k, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function, const RealType& r, const RealType& p, RealType k, RealType* result, const Policy& pol)
       {
         if(check_dist(function, r, p, result, pol) == false)
         {
@@ -117,7 +119,7 @@ namespace boost
       } // Check_dist_and_k
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, const RealType& r, RealType p, RealType prob, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, const RealType& r, RealType p, RealType prob, RealType* result, const Policy& pol)
       {
         if((check_dist(function, r, p, result, pol) && detail::check_probability(function, prob, result, pol)) == false)
         {
@@ -134,7 +136,7 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      negative_binomial_distribution(RealType r, RealType p) : m_r(r), m_p(p)
+      BOOST_MATH_GPU_ENABLED negative_binomial_distribution(RealType r, RealType p) : m_r(r), m_p(p)
       { // Constructor.
         RealType result;
         negative_binomial_detail::check_dist(
@@ -145,21 +147,21 @@ namespace boost
       } // negative_binomial_distribution constructor.
 
       // Private data getter class member functions.
-      RealType success_fraction() const
+      BOOST_MATH_GPU_ENABLED RealType success_fraction() const
       { // Probability of success as fraction in range 0 to 1.
         return m_p;
       }
-      RealType successes() const
+      BOOST_MATH_GPU_ENABLED RealType successes() const
       { // Total number of successes r.
         return m_r;
       }
 
-      static RealType find_lower_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_lower_bound_on_p(
         RealType trials,
         RealType successes,
         RealType alpha) // alpha 0.05 equivalent to 95% for one-sided test.
       {
-        static const char* function = "boost::math::negative_binomial<%1%>::find_lower_bound_on_p";
+        constexpr auto function = "boost::math::negative_binomial<%1%>::find_lower_bound_on_p";
         RealType result = 0;  // of error checks.
         RealType failures = trials - successes;
         if(false == detail::check_probability(function, alpha, &result, Policy())
@@ -179,12 +181,12 @@ namespace boost
         return ibeta_inv(successes, failures + 1, alpha, static_cast<RealType*>(nullptr), Policy());
       } // find_lower_bound_on_p
 
-      static RealType find_upper_bound_on_p(
+      BOOST_MATH_GPU_ENABLED static RealType find_upper_bound_on_p(
         RealType trials,
         RealType successes,
         RealType alpha) // alpha 0.05 equivalent to 95% for one-sided test.
       {
-        static const char* function = "boost::math::negative_binomial<%1%>::find_upper_bound_on_p";
+        constexpr auto function = "boost::math::negative_binomial<%1%>::find_upper_bound_on_p";
         RealType result = 0;  // of error checks.
         RealType failures = trials - successes;
         if(false == negative_binomial_detail::check_dist_and_k(
@@ -210,12 +212,12 @@ namespace boost
       // Estimate number of trials :
       // "How many trials do I need to be P% sure of seeing k or fewer failures?"
 
-      static RealType find_minimum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_minimum_number_of_trials(
         RealType k,     // number of failures (k >= 0).
         RealType p,     // success fraction 0 <= p <= 1.
         RealType alpha) // risk level threshold 0 <= alpha <= 1.
       {
-        static const char* function = "boost::math::negative_binomial<%1%>::find_minimum_number_of_trials";
+        constexpr auto function = "boost::math::negative_binomial<%1%>::find_minimum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == negative_binomial_detail::check_dist_and_k(
@@ -227,12 +229,12 @@ namespace boost
         return result + k;
       } // RealType find_number_of_failures
 
-      static RealType find_maximum_number_of_trials(
+      BOOST_MATH_GPU_ENABLED static RealType find_maximum_number_of_trials(
         RealType k,     // number of failures (k >= 0).
         RealType p,     // success fraction 0 <= p <= 1.
         RealType alpha) // risk level threshold 0 <= alpha <= 1.
       {
-        static const char* function = "boost::math::negative_binomial<%1%>::find_maximum_number_of_trials";
+        constexpr auto function = "boost::math::negative_binomial<%1%>::find_maximum_number_of_trials";
         // Error checks:
         RealType result = 0;
         if(false == negative_binomial_detail::check_dist_and_k(
@@ -257,22 +259,22 @@ namespace boost
     #endif
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const negative_binomial_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const negative_binomial_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable k.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // max_integer?
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // max_integer?
     }
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const negative_binomial_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const negative_binomial_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable k.
        // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>()); // max_integer?
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>()); // max_integer?
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const negative_binomial_distribution<RealType, Policy>& dist)
     { // Mean of Negative Binomial distribution = r(1-p)/p.
       return dist.successes() * (1 - dist.success_fraction() ) / dist.success_fraction();
     } // mean
@@ -285,14 +287,14 @@ namespace boost
     // Now implemented via quantile(half) in derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType mode(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const negative_binomial_distribution<RealType, Policy>& dist)
     { // Mode of Negative Binomial distribution = floor[(r-1) * (1 - p)/p]
       BOOST_MATH_STD_USING // ADL of std functions.
       return floor((dist.successes() -1) * (1 - dist.success_fraction()) / dist.success_fraction());
     } // mode
 
     template <class RealType, class Policy>
-    inline RealType skewness(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const negative_binomial_distribution<RealType, Policy>& dist)
     { // skewness of Negative Binomial distribution = 2-p / (sqrt(r(1-p))
       BOOST_MATH_STD_USING // ADL of std functions.
       RealType p = dist.success_fraction();
@@ -303,7 +305,7 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const negative_binomial_distribution<RealType, Policy>& dist)
     { // kurtosis of Negative Binomial distribution
       // http://en.wikipedia.org/wiki/Negative_binomial is kurtosis_excess so add 3
       RealType p = dist.success_fraction();
@@ -312,7 +314,7 @@ namespace boost
     } // kurtosis
 
      template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const negative_binomial_distribution<RealType, Policy>& dist)
     { // kurtosis excess of Negative Binomial distribution
       // http://mathworld.wolfram.com/Kurtosis.html table of kurtosis_excess
       RealType p = dist.success_fraction();
@@ -321,7 +323,7 @@ namespace boost
     } // kurtosis_excess
 
     template <class RealType, class Policy>
-    inline RealType variance(const negative_binomial_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const negative_binomial_distribution<RealType, Policy>& dist)
     { // Variance of Binomial distribution = r (1-p) / p^2.
       return  dist.successes() * (1 - dist.success_fraction())
         / (dist.success_fraction() * dist.success_fraction());
@@ -335,11 +337,11 @@ namespace boost
     // chf of Negative Binomial distribution provided by derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType pdf(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& k)
     { // Probability Density/Mass Function.
       BOOST_FPU_EXCEPTION_GUARD
 
-      static const char* function = "boost::math::pdf(const negative_binomial_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const negative_binomial_distribution<%1%>&, %1%)";
 
       RealType r = dist.successes();
       RealType p = dist.success_fraction();
@@ -361,9 +363,9 @@ namespace boost
     } // negative_binomial_pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& k)
     { // Cumulative Distribution Function of Negative Binomial.
-      static const char* function = "boost::math::cdf(const negative_binomial_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::cdf(const negative_binomial_distribution<%1%>&, %1%)";
       using boost::math::ibeta; // Regularized incomplete beta function.
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
@@ -387,10 +389,10 @@ namespace boost
     } // cdf Cumulative Distribution Function Negative Binomial.
 
       template <class RealType, class Policy>
-      inline RealType cdf(const complemented2_type<negative_binomial_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<negative_binomial_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function Negative Binomial.
 
-      static const char* function = "boost::math::cdf(const negative_binomial_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::cdf(const negative_binomial_distribution<%1%>&, %1%)";
       using boost::math::ibetac; // Regularized incomplete beta function complement.
       // k argument may be integral, signed, or unsigned, or floating point.
       // If necessary, it has already been promoted from an integral type.
@@ -421,7 +423,7 @@ namespace boost
     } // cdf Cumulative Distribution Function Negative Binomial.
 
     template <class RealType, class Policy>
-    inline RealType quantile(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& P)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const negative_binomial_distribution<RealType, Policy>& dist, const RealType& P)
     { // Quantile, percentile/100 or Percent Point Negative Binomial function.
       // Return the number of expected failures k for a given probability p.
 
@@ -429,7 +431,7 @@ namespace boost
       // MAthCAD pnbinom return smallest k such that negative_binomial(k, n, p) >= probability.
       // k argument may be integral, signed, or unsigned, or floating point.
       // BUT Cephes/CodeCogs says: finds argument p (0 to 1) such that cdf(k, n, p) = y
-      static const char* function = "boost::math::quantile(const negative_binomial_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::quantile(const negative_binomial_distribution<%1%>&, %1%)";
       BOOST_MATH_STD_USING // ADL of std functions.
 
       RealType p = dist.success_fraction();
@@ -484,7 +486,7 @@ namespace boost
          //
          // Cornish-Fisher Negative binomial approximation not accurate in this area:
          //
-         guess = (std::min)(RealType(r * 2), RealType(10));
+         guess = BOOST_MATH_GPU_SAFE_MIN(RealType(r * 2), RealType(10));
       }
       else
          factor = (1-P < sqrt(tools::epsilon<RealType>())) ? 2 : (guess < 20 ? 1.2f : 1.1f);
@@ -492,7 +494,7 @@ namespace boost
       //
       // Max iterations permitted:
       //
-      std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+      boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
       typedef typename Policy::discrete_quantile_type discrete_type;
       return detail::inverse_discrete_quantile(
          dist,
@@ -506,11 +508,11 @@ namespace boost
     } // RealType quantile(const negative_binomial_distribution dist, p)
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<negative_binomial_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<negative_binomial_distribution<RealType, Policy>, RealType>& c)
     {  // Quantile or Percent Point Binomial function.
        // Return the number of expected failures k for a given
        // complement of the probability Q = 1 - P.
-       static const char* function = "boost::math::quantile(const negative_binomial_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::quantile(const negative_binomial_distribution<%1%>&, %1%)";
        BOOST_MATH_STD_USING
 
        // Error checks:
@@ -571,7 +573,7 @@ namespace boost
           //
           // Cornish-Fisher Negative binomial approximation not accurate in this area:
           //
-          guess = (std::min)(RealType(r * 2), RealType(10));
+          guess = BOOST_MATH_GPU_SAFE_MIN(RealType(r * 2), RealType(10));
        }
        else
           factor = (Q < sqrt(tools::epsilon<RealType>())) ? 2 : (guess < 20 ? 1.2f : 1.1f);
@@ -579,7 +581,7 @@ namespace boost
        //
        // Max iterations permitted:
        //
-       std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+       boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
        typedef typename Policy::discrete_quantile_type discrete_type;
        return detail::inverse_discrete_quantile(
           dist,
diff --git a/include/boost/math/distributions/non_central_beta.hpp b/include/boost/math/distributions/non_central_beta.hpp
index a8c8af868a..9dd7d5e60b 100644
--- a/include/boost/math/distributions/non_central_beta.hpp
+++ b/include/boost/math/distributions/non_central_beta.hpp
@@ -1,7 +1,7 @@
 // boost\math\distributions\non_central_beta.hpp
 
 // Copyright John Maddock 2008.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -10,6 +10,10 @@
 #ifndef BOOST_MATH_SPECIAL_NON_CENTRAL_BETA_HPP
 #define BOOST_MATH_SPECIAL_NON_CENTRAL_BETA_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for incomplete gamma. gamma_q
 #include <boost/math/distributions/complement.hpp> // complements
@@ -20,6 +24,7 @@
 #include <boost/math/special_functions/trunc.hpp>
 #include <boost/math/tools/roots.hpp> // for root finding.
 #include <boost/math/tools/series.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost
 {
@@ -32,14 +37,14 @@ namespace boost
       namespace detail{
 
          template <class T, class Policy>
-         T non_central_beta_p(T a, T b, T lam, T x, T y, const Policy& pol, T init_val = 0)
+         BOOST_MATH_GPU_ENABLED T non_central_beta_p(T a, T b, T lam, T x, T y, const Policy& pol, T init_val = 0)
          {
             BOOST_MATH_STD_USING
                using namespace boost::math;
             //
             // Variables come first:
             //
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T l2 = lam / 2;
             //
@@ -86,7 +91,7 @@ namespace boost
             // direction for recursion:
             //
             T last_term = 0;
-            std::uintmax_t count = k;
+            boost::math::uintmax_t count = k;
             for(auto i = k; i >= 0; --i)
             {
                T term = beta * pois;
@@ -120,7 +125,7 @@ namespace boost
                   break;
                }
                last_term = term;
-               if(static_cast<std::uintmax_t>(count + i - k) > max_iter)
+               if(static_cast<boost::math::uintmax_t>(count + i - k) > max_iter)
                {
                   return policies::raise_evaluation_error("cdf(non_central_beta_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
                }
@@ -129,14 +134,14 @@ namespace boost
          }
 
          template <class T, class Policy>
-         T non_central_beta_q(T a, T b, T lam, T x, T y, const Policy& pol, T init_val = 0)
+         BOOST_MATH_GPU_ENABLED T non_central_beta_q(T a, T b, T lam, T x, T y, const Policy& pol, T init_val = 0)
          {
             BOOST_MATH_STD_USING
                using namespace boost::math;
             //
             // Variables come first:
             //
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T l2 = lam / 2;
             //
@@ -185,7 +190,7 @@ namespace boost
             // of the bulk of the sum:
             //
             T last_term = 0;
-            std::uintmax_t count = 0;
+            boost::math::uintmax_t count = 0;
             for(auto i = k + 1; ; ++i)
             {
                poisf *= l2 / i;
@@ -199,7 +204,7 @@ namespace boost
                   count = i - k;
                   break;
                }
-               if(static_cast<std::uintmax_t>(i - k) > max_iter)
+               if(static_cast<boost::math::uintmax_t>(i - k) > max_iter)
                {
                   return policies::raise_evaluation_error("cdf(non_central_beta_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
                }
@@ -213,7 +218,7 @@ namespace boost
                {
                   break;
                }
-               if(static_cast<std::uintmax_t>(count + k - i) > max_iter)
+               if(static_cast<boost::math::uintmax_t>(count + k - i) > max_iter)
                {
                   return policies::raise_evaluation_error("cdf(non_central_beta_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
                }
@@ -228,7 +233,7 @@ namespace boost
          }
 
          template <class RealType, class Policy>
-         inline RealType non_central_beta_cdf(RealType x, RealType y, RealType a, RealType b, RealType l, bool invert, const Policy&)
+         BOOST_MATH_GPU_ENABLED inline RealType non_central_beta_cdf(RealType x, RealType y, RealType a, RealType b, RealType l, bool invert, const Policy&)
          {
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
@@ -283,10 +288,10 @@ namespace boost
          template <class T, class Policy>
          struct nc_beta_quantile_functor
          {
-            nc_beta_quantile_functor(const non_central_beta_distribution<T,Policy>& d, T t, bool c)
+            BOOST_MATH_GPU_ENABLED nc_beta_quantile_functor(const non_central_beta_distribution<T,Policy>& d, T t, bool c)
                : dist(d), target(t), comp(c) {}
 
-            T operator()(const T& x)
+            BOOST_MATH_GPU_ENABLED T operator()(const T& x)
             {
                return comp ?
                   T(target - cdf(complement(dist, x)))
@@ -305,10 +310,10 @@ namespace boost
          // heuristics.
          //
          template <class F, class T, class Tol, class Policy>
-         std::pair<T, T> bracket_and_solve_root_01(F f, const T& guess, T factor, bool rising, Tol tol, std::uintmax_t& max_iter, const Policy& pol)
+         BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> bracket_and_solve_root_01(F f, const T& guess, T factor, bool rising, Tol tol, boost::math::uintmax_t& max_iter, const Policy& pol)
          {
             BOOST_MATH_STD_USING
-               static const char* function = "boost::math::tools::bracket_and_solve_root_01<%1%>";
+               constexpr auto function = "boost::math::tools::bracket_and_solve_root_01<%1%>";
             //
             // Set up initial brackets:
             //
@@ -319,7 +324,7 @@ namespace boost
             //
             // Set up invocation count:
             //
-            std::uintmax_t count = max_iter - 1;
+            boost::math::uintmax_t count = max_iter - 1;
 
             if((fa < 0) == (guess < 0 ? !rising : rising))
             {
@@ -332,7 +337,7 @@ namespace boost
                   if(count == 0)
                   {
                      b = policies::raise_evaluation_error(function, "Unable to bracket root, last nearest value was %1%", b, pol); // LCOV_EXCL_LINE
-                     return std::make_pair(a, b);
+                     return boost::math::make_pair(a, b);
                   }
                   //
                   // Heuristic: every 20 iterations we double the growth factor in case the
@@ -365,12 +370,12 @@ namespace boost
                      // Escape route just in case the answer is zero!
                      max_iter -= count;
                      max_iter += 1;
-                     return a > 0 ? std::make_pair(T(0), T(a)) : std::make_pair(T(a), T(0));
+                     return a > 0 ? boost::math::make_pair(T(0), T(a)) : boost::math::make_pair(T(a), T(0));
                   }
                   if(count == 0)
                   {
                      a = policies::raise_evaluation_error(function, "Unable to bracket root, last nearest value was %1%", a, pol); // LCOV_EXCL_LINE
-                     return std::make_pair(a, b);
+                     return boost::math::make_pair(a, b);
                   }
                   //
                   // Heuristic: every 20 iterations we double the growth factor in case the
@@ -391,7 +396,7 @@ namespace boost
             }
             max_iter -= count;
             max_iter += 1;
-            std::pair<T, T> r = toms748_solve(
+            boost::math::pair<T, T> r = toms748_solve(
                f,
                (a < 0 ? b : a),
                (a < 0 ? a : b),
@@ -406,9 +411,9 @@ namespace boost
          }
 
          template <class RealType, class Policy>
-         RealType nc_beta_quantile(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& p, bool comp)
+         BOOST_MATH_GPU_ENABLED RealType nc_beta_quantile(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& p, bool comp)
          {
-            static const char* function = "quantile(non_central_beta_distribution<%1%>, %1%)";
+            constexpr auto function = "quantile(non_central_beta_distribution<%1%>, %1%)";
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
                Policy,
@@ -505,9 +510,9 @@ namespace boost
             detail::nc_beta_quantile_functor<value_type, Policy>
                f(non_central_beta_distribution<value_type, Policy>(a, b, l), p, comp);
             tools::eps_tolerance<value_type> tol(policies::digits<RealType, Policy>());
-            std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
 
-            std::pair<value_type, value_type> ir
+            boost::math::pair<value_type, value_type> ir
                = bracket_and_solve_root_01(
                   f, guess, value_type(2.5), true, tol,
                   max_iter, Policy());
@@ -530,7 +535,7 @@ namespace boost
          }
 
          template <class T, class Policy>
-         T non_central_beta_pdf(T a, T b, T lam, T x, T y, const Policy& pol)
+         BOOST_MATH_GPU_ENABLED T non_central_beta_pdf(T a, T b, T lam, T x, T y, const Policy& pol)
          {
             BOOST_MATH_STD_USING
             //
@@ -541,7 +546,7 @@ namespace boost
             //
             // Variables come first:
             //
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T l2 = lam / 2;
             //
@@ -580,7 +585,7 @@ namespace boost
             //
             // Stable backwards recursion first:
             //
-            std::uintmax_t count = k;
+            boost::math::uintmax_t count = k;
             T ratio = 0;
             T old_ratio = 0;
             for(auto i = k; i >= 0; --i)
@@ -615,7 +620,7 @@ namespace boost
                   break;
                }
                old_ratio = ratio;
-               if(static_cast<std::uintmax_t>(count + i - k) > max_iter)
+               if(static_cast<boost::math::uintmax_t>(count + i - k) > max_iter)
                {
                   return policies::raise_evaluation_error("pdf(non_central_beta_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
                }
@@ -624,10 +629,10 @@ namespace boost
          }
 
          template <class RealType, class Policy>
-         RealType nc_beta_pdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
+         BOOST_MATH_GPU_ENABLED RealType nc_beta_pdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
          {
             BOOST_MATH_STD_USING
-            static const char* function = "pdf(non_central_beta_distribution<%1%>, %1%)";
+            constexpr auto function = "pdf(non_central_beta_distribution<%1%>, %1%)";
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
                Policy,
@@ -672,8 +677,8 @@ namespace boost
          struct hypergeometric_2F2_sum
          {
             typedef T result_type;
-            hypergeometric_2F2_sum(T a1_, T a2_, T b1_, T b2_, T z_) : a1(a1_), a2(a2_), b1(b1_), b2(b2_), z(z_), term(1), k(0) {}
-            T operator()()
+            BOOST_MATH_GPU_ENABLED hypergeometric_2F2_sum(T a1_, T a2_, T b1_, T b2_, T z_) : a1(a1_), a2(a2_), b1(b1_), b2(b2_), z(z_), term(1), k(0) {}
+            BOOST_MATH_GPU_ENABLED T operator()()
             {
                T result = term;
                term *= a1 * a2 / (b1 * b2);
@@ -690,14 +695,14 @@ namespace boost
          };
 
          template <class T, class Policy>
-         T hypergeometric_2F2(T a1, T a2, T b1, T b2, T z, const Policy& pol)
+         BOOST_MATH_GPU_ENABLED T hypergeometric_2F2(T a1, T a2, T b1, T b2, T z, const Policy& pol)
          {
             typedef typename policies::evaluation<T, Policy>::type value_type;
 
             const char* function = "boost::math::detail::hypergeometric_2F2<%1%>(%1%,%1%,%1%,%1%,%1%)";
 
             hypergeometric_2F2_sum<value_type> s(a1, a2, b1, b2, z);
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
             value_type result = boost::math::tools::sum_series(s, boost::math::policies::get_epsilon<value_type, Policy>(), max_iter);
 
@@ -714,7 +719,7 @@ namespace boost
          typedef RealType value_type;
          typedef Policy policy_type;
 
-         non_central_beta_distribution(RealType a_, RealType b_, RealType lambda) : a(a_), b(b_), ncp(lambda)
+         BOOST_MATH_GPU_ENABLED non_central_beta_distribution(RealType a_, RealType b_, RealType lambda) : a(a_), b(b_), ncp(lambda)
          {
             const char* function = "boost::math::non_central_beta_distribution<%1%>::non_central_beta_distribution(%1%,%1%)";
             RealType r;
@@ -731,15 +736,15 @@ namespace boost
                Policy());
          } // non_central_beta_distribution constructor.
 
-         RealType alpha() const
+         BOOST_MATH_GPU_ENABLED RealType alpha() const
          { // Private data getter function.
             return a;
          }
-         RealType beta() const
+         BOOST_MATH_GPU_ENABLED RealType beta() const
          { // Private data getter function.
             return b;
          }
-         RealType non_centrality() const
+         BOOST_MATH_GPU_ENABLED RealType non_centrality() const
          { // Private data getter function.
             return ncp;
          }
@@ -760,24 +765,24 @@ namespace boost
       // Non-member functions to give properties of the distribution.
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> range(const non_central_beta_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const non_central_beta_distribution<RealType, Policy>& /* dist */)
       { // Range of permissible values for random variable k.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
       }
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> support(const non_central_beta_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const non_central_beta_distribution<RealType, Policy>& /* dist */)
       { // Range of supported values for random variable k.
          // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), static_cast<RealType>(1));
       }
 
       template <class RealType, class Policy>
-      inline RealType mode(const non_central_beta_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mode(const non_central_beta_distribution<RealType, Policy>& dist)
       { // mode.
-         static const char* function = "mode(non_central_beta_distribution<%1%> const&)";
+         constexpr auto function = "mode(non_central_beta_distribution<%1%> const&)";
 
          RealType a = dist.alpha();
          RealType b = dist.beta();
@@ -812,7 +817,7 @@ namespace boost
       // later:
       //
       template <class RealType, class Policy>
-      inline RealType mean(const non_central_beta_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mean(const non_central_beta_distribution<RealType, Policy>& dist)
       {
          BOOST_MATH_STD_USING
          RealType a = dist.alpha();
@@ -823,7 +828,7 @@ namespace boost
       } // mean
 
       template <class RealType, class Policy>
-      inline RealType variance(const non_central_beta_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType variance(const non_central_beta_distribution<RealType, Policy>& dist)
       { 
          //
          // Relative error of this function may be arbitrarily large... absolute
@@ -843,41 +848,41 @@ namespace boost
       // RealType standard_deviation(const non_central_beta_distribution<RealType, Policy>& dist)
       // standard_deviation provided by derived accessors.
       template <class RealType, class Policy>
-      inline RealType skewness(const non_central_beta_distribution<RealType, Policy>& /*dist*/)
+      BOOST_MATH_GPU_ENABLED inline RealType skewness(const non_central_beta_distribution<RealType, Policy>& /*dist*/)
       { // skewness = sqrt(l).
          const char* function = "boost::math::non_central_beta_distribution<%1%>::skewness()";
          typedef typename Policy::assert_undefined_type assert_type;
          static_assert(assert_type::value == 0, "The Non Central Beta Distribution has no skewness.");
 
          return policies::raise_evaluation_error<RealType>(function, "This function is not yet implemented, the only sensible result is %1%.", // LCOV_EXCL_LINE
-            std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
+            boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
       }
 
       template <class RealType, class Policy>
-      inline RealType kurtosis_excess(const non_central_beta_distribution<RealType, Policy>& /*dist*/)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const non_central_beta_distribution<RealType, Policy>& /*dist*/)
       {
          const char* function = "boost::math::non_central_beta_distribution<%1%>::kurtosis_excess()";
          typedef typename Policy::assert_undefined_type assert_type;
          static_assert(assert_type::value == 0, "The Non Central Beta Distribution has no kurtosis excess.");
 
          return policies::raise_evaluation_error<RealType>(function, "This function is not yet implemented, the only sensible result is %1%.", // LCOV_EXCL_LINE
-            std::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
+            boost::math::numeric_limits<RealType>::quiet_NaN(), Policy()); // infinity?  LCOV_EXCL_LINE
       } // kurtosis_excess
 
       template <class RealType, class Policy>
-      inline RealType kurtosis(const non_central_beta_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const non_central_beta_distribution<RealType, Policy>& dist)
       {
          return kurtosis_excess(dist) + 3;
       }
 
       template <class RealType, class Policy>
-      inline RealType pdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED inline RealType pdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
       { // Probability Density/Mass Function.
          return detail::nc_beta_pdf(dist, x);
       } // pdf
 
       template <class RealType, class Policy>
-      RealType cdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& x)
       {
          const char* function = "boost::math::non_central_beta_distribution<%1%>::cdf(%1%)";
             RealType a = dist.alpha();
@@ -912,7 +917,7 @@ namespace boost
       } // cdf
 
       template <class RealType, class Policy>
-      RealType cdf(const complemented2_type<non_central_beta_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const complemented2_type<non_central_beta_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function
          const char* function = "boost::math::non_central_beta_distribution<%1%>::cdf(%1%)";
          non_central_beta_distribution<RealType, Policy> const& dist = c.dist;
@@ -949,13 +954,13 @@ namespace boost
       } // ccdf
 
       template <class RealType, class Policy>
-      inline RealType quantile(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const non_central_beta_distribution<RealType, Policy>& dist, const RealType& p)
       { // Quantile (or Percent Point) function.
          return detail::nc_beta_quantile(dist, p, false);
       } // quantile
 
       template <class RealType, class Policy>
-      inline RealType quantile(const complemented2_type<non_central_beta_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<non_central_beta_distribution<RealType, Policy>, RealType>& c)
       { // Quantile (or Percent Point) function.
          return detail::nc_beta_quantile(c.dist, c.param, true);
       } // quantile complement.
diff --git a/include/boost/math/distributions/non_central_chi_squared.hpp b/include/boost/math/distributions/non_central_chi_squared.hpp
index f59be9932c..5917b3732d 100644
--- a/include/boost/math/distributions/non_central_chi_squared.hpp
+++ b/include/boost/math/distributions/non_central_chi_squared.hpp
@@ -1,7 +1,7 @@
 // boost\math\distributions\non_central_chi_squared.hpp
 
 // Copyright John Maddock 2008.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -10,6 +10,10 @@
 #ifndef BOOST_MATH_SPECIAL_NON_CENTRAL_CHI_SQUARE_HPP
 #define BOOST_MATH_SPECIAL_NON_CENTRAL_CHI_SQUARE_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp> // for incomplete gamma. gamma_q
 #include <boost/math/special_functions/bessel.hpp> // for cyl_bessel_i
@@ -21,6 +25,7 @@
 #include <boost/math/tools/roots.hpp> // for root finding.
 #include <boost/math/distributions/detail/generic_mode.hpp>
 #include <boost/math/distributions/detail/generic_quantile.hpp>
+#include <boost/math/policies/policy.hpp>
 
 namespace boost
 {
@@ -33,7 +38,7 @@ namespace boost
       namespace detail{
 
          template <class T, class Policy>
-         T non_central_chi_square_q(T x, T f, T theta, const Policy& pol, T init_sum = 0)
+         BOOST_MATH_GPU_ENABLED T non_central_chi_square_q(T x, T f, T theta, const Policy& pol, T init_sum = 0)
          {
             //
             // Computes the complement of the Non-Central Chi-Square
@@ -62,7 +67,7 @@ namespace boost
             T lambda = theta / 2;
             T del = f / 2;
             T y = x / 2;
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T sum = init_sum;
             //
@@ -89,7 +94,7 @@ namespace boost
             // recurrences:
             //
             long long i;
-            for(i = k; static_cast<std::uintmax_t>(i-k) < max_iter; ++i)
+            for(i = k; static_cast<boost::math::uintmax_t>(i-k) < max_iter; ++i)
             {
                T term = poisf * gamf;
                sum += term;
@@ -100,7 +105,7 @@ namespace boost
                   break;
             }
             //Error check:
-            if(static_cast<std::uintmax_t>(i-k) >= max_iter)
+            if(static_cast<boost::math::uintmax_t>(i-k) >= max_iter)
                return policies::raise_evaluation_error("cdf(non_central_chi_squared_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
             //
             // Now backwards iteration: the gamma
@@ -126,7 +131,7 @@ namespace boost
          }
 
          template <class T, class Policy>
-         T non_central_chi_square_p_ding(T x, T f, T theta, const Policy& pol, T init_sum = 0)
+         BOOST_MATH_GPU_ENABLED T non_central_chi_square_p_ding(T x, T f, T theta, const Policy& pol, T init_sum = 0)
          {
             //
             // This is an implementation of:
@@ -155,12 +160,12 @@ namespace boost
             if(sum == 0)
                return sum;
 
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
 
             int i;
             T lterm(0), term(0);
-            for(i = 1; static_cast<std::uintmax_t>(i) < max_iter; ++i)
+            for(i = 1; static_cast<boost::math::uintmax_t>(i) < max_iter; ++i)
             {
                tk = tk * x / (f + 2 * i);
                uk = uk * lambda / i;
@@ -172,14 +177,14 @@ namespace boost
                   break;
             }
             //Error check:
-            if(static_cast<std::uintmax_t>(i) >= max_iter)
+            if(static_cast<boost::math::uintmax_t>(i) >= max_iter)
                return policies::raise_evaluation_error("cdf(non_central_chi_squared_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
             return sum;
          }
 
 
          template <class T, class Policy>
-         T non_central_chi_square_p(T y, T n, T lambda, const Policy& pol, T init_sum)
+         BOOST_MATH_GPU_ENABLED T non_central_chi_square_p(T y, T n, T lambda, const Policy& pol, T init_sum)
          {
             //
             // This is taken more or less directly from:
@@ -198,7 +203,7 @@ namespace boost
             // Special case:
             if(y == 0)
                return 0;
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T errorf(0), errorb(0);
 
@@ -266,23 +271,23 @@ namespace boost
                errorf = poiskf * gamkf;
                sum += errorf;
                ++i;
-            }while((fabs(errorf / sum) > errtol) && (static_cast<std::uintmax_t>(i) < max_iter));
+            }while((fabs(errorf / sum) > errtol) && (static_cast<boost::math::uintmax_t>(i) < max_iter));
 
             //Error check:
-            if(static_cast<std::uintmax_t>(i) >= max_iter)
+            if(static_cast<boost::math::uintmax_t>(i) >= max_iter)
                return policies::raise_evaluation_error("cdf(non_central_chi_squared_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
 
             return sum;
          }
 
          template <class T, class Policy>
-         T non_central_chi_square_pdf(T x, T n, T lambda, const Policy& pol)
+         BOOST_MATH_GPU_ENABLED T non_central_chi_square_pdf(T x, T n, T lambda, const Policy& pol)
          {
             //
             // As above but for the PDF:
             //
             BOOST_MATH_STD_USING
-            std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
             T errtol = boost::math::policies::get_epsilon<T, Policy>();
             T x2 = x / 2;
             T n2 = n / 2;
@@ -298,7 +303,7 @@ namespace boost
                sum += pois;
                if(pois / sum < errtol)
                   break;
-               if(static_cast<std::uintmax_t>(i - k) >= max_iter)
+               if(static_cast<boost::math::uintmax_t>(i - k) >= max_iter)
                   return policies::raise_evaluation_error("pdf(non_central_chi_squared_distribution<%1%>, %1%)", "Series did not converge, closest value was %1%", sum, pol); // LCOV_EXCL_LINE
                pois *= l2 * x2 / ((i + 1) * (n2 + i));
             }
@@ -313,7 +318,7 @@ namespace boost
          }
 
          template <class RealType, class Policy>
-         inline RealType non_central_chi_squared_cdf(RealType x, RealType k, RealType l, bool invert, const Policy&)
+         BOOST_MATH_GPU_ENABLED inline RealType non_central_chi_squared_cdf(RealType x, RealType k, RealType l, bool invert, const Policy&)
          {
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
@@ -373,10 +378,10 @@ namespace boost
          template <class T, class Policy>
          struct nccs_quantile_functor
          {
-            nccs_quantile_functor(const non_central_chi_squared_distribution<T,Policy>& d, T t, bool c)
+            BOOST_MATH_GPU_ENABLED nccs_quantile_functor(const non_central_chi_squared_distribution<T,Policy>& d, T t, bool c)
                : dist(d), target(t), comp(c) {}
 
-            T operator()(const T& x)
+            BOOST_MATH_GPU_ENABLED T operator()(const T& x)
             {
                return comp ?
                   target - cdf(complement(dist, x))
@@ -390,10 +395,10 @@ namespace boost
          };
 
          template <class RealType, class Policy>
-         RealType nccs_quantile(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& p, bool comp)
+         BOOST_MATH_GPU_ENABLED RealType nccs_quantile(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& p, bool comp)
          {
             BOOST_MATH_STD_USING
-            static const char* function = "quantile(non_central_chi_squared_distribution<%1%>, %1%)";
+            constexpr auto function = "quantile(non_central_chi_squared_distribution<%1%>, %1%)";
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
                Policy,
@@ -481,10 +486,10 @@ namespace boost
          }
 
          template <class RealType, class Policy>
-         RealType nccs_pdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
+         BOOST_MATH_GPU_ENABLED RealType nccs_pdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
          {
             BOOST_MATH_STD_USING
-            static const char* function = "pdf(non_central_chi_squared_distribution<%1%>, %1%)";
+            constexpr auto function = "pdf(non_central_chi_squared_distribution<%1%>, %1%)";
             typedef typename policies::evaluation<RealType, Policy>::type value_type;
             typedef typename policies::normalise<
                Policy,
@@ -545,11 +550,11 @@ namespace boost
          template <class RealType, class Policy>
          struct degrees_of_freedom_finder
          {
-            degrees_of_freedom_finder(
+            BOOST_MATH_GPU_ENABLED degrees_of_freedom_finder(
                RealType lam_, RealType x_, RealType p_, bool c)
                : lam(lam_), x(x_), p(p_), comp(c) {}
 
-            RealType operator()(const RealType& v)
+            BOOST_MATH_GPU_ENABLED RealType operator()(const RealType& v)
             {
                non_central_chi_squared_distribution<RealType, Policy> d(v, lam);
                return comp ?
@@ -564,21 +569,21 @@ namespace boost
          };
 
          template <class RealType, class Policy>
-         inline RealType find_degrees_of_freedom(
+         BOOST_MATH_GPU_ENABLED inline RealType find_degrees_of_freedom(
             RealType lam, RealType x, RealType p, RealType q, const Policy& pol)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
             if((p == 0) || (q == 0))
             {
                //
                // Can't a thing if one of p and q is zero:
                //
                return policies::raise_evaluation_error<RealType>(function, "Can't find degrees of freedom when the probability is 0 or 1, only possible answer is %1%", // LCOV_EXCL_LINE
-                  RealType(std::numeric_limits<RealType>::quiet_NaN()), Policy()); // LCOV_EXCL_LINE
+                  RealType(boost::math::numeric_limits<RealType>::quiet_NaN()), Policy()); // LCOV_EXCL_LINE
             }
             degrees_of_freedom_finder<RealType, Policy> f(lam, x, p < q ? p : q, p < q ? false : true);
             tools::eps_tolerance<RealType> tol(policies::digits<RealType, Policy>());
-            std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
             //
             // Pick an initial guess that we know will give us a probability
             // right around 0.5.
@@ -586,7 +591,7 @@ namespace boost
             RealType guess = x - lam;
             if(guess < 1)
                guess = 1;
-            std::pair<RealType, RealType> ir = tools::bracket_and_solve_root(
+            boost::math::pair<RealType, RealType> ir = tools::bracket_and_solve_root(
                f, guess, RealType(2), false, tol, max_iter, pol);
             RealType result = ir.first + (ir.second - ir.first) / 2;
             if(max_iter >= policies::get_max_root_iterations<Policy>())
@@ -600,11 +605,11 @@ namespace boost
          template <class RealType, class Policy>
          struct non_centrality_finder
          {
-            non_centrality_finder(
+            BOOST_MATH_GPU_ENABLED non_centrality_finder(
                RealType v_, RealType x_, RealType p_, bool c)
                : v(v_), x(x_), p(p_), comp(c) {}
 
-            RealType operator()(const RealType& lam)
+            BOOST_MATH_GPU_ENABLED RealType operator()(const RealType& lam)
             {
                non_central_chi_squared_distribution<RealType, Policy> d(v, lam);
                return comp ?
@@ -619,21 +624,21 @@ namespace boost
          };
 
          template <class RealType, class Policy>
-         inline RealType find_non_centrality(
+         BOOST_MATH_GPU_ENABLED inline RealType find_non_centrality(
             RealType v, RealType x, RealType p, RealType q, const Policy& pol)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_non_centrality";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_non_centrality";
             if((p == 0) || (q == 0))
             {
                //
                // Can't do a thing if one of p and q is zero:
                //
                return policies::raise_evaluation_error<RealType>(function, "Can't find non centrality parameter when the probability is 0 or 1, only possible answer is %1%", // LCOV_EXCL_LINE
-                  RealType(std::numeric_limits<RealType>::quiet_NaN()), Policy()); // LCOV_EXCL_LINE
+                  RealType(boost::math::numeric_limits<RealType>::quiet_NaN()), Policy()); // LCOV_EXCL_LINE
             }
             non_centrality_finder<RealType, Policy> f(v, x, p < q ? p : q, p < q ? false : true);
             tools::eps_tolerance<RealType> tol(policies::digits<RealType, Policy>());
-            std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+            boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
             //
             // Pick an initial guess that we know will give us a probability
             // right around 0.5.
@@ -641,7 +646,7 @@ namespace boost
             RealType guess = x - v;
             if(guess < 1)
                guess = 1;
-            std::pair<RealType, RealType> ir = tools::bracket_and_solve_root(
+            boost::math::pair<RealType, RealType> ir = tools::bracket_and_solve_root(
                f, guess, RealType(2), false, tol, max_iter, pol);
             RealType result = ir.first + (ir.second - ir.first) / 2;
             if(max_iter >= policies::get_max_root_iterations<Policy>())
@@ -661,9 +666,9 @@ namespace boost
          typedef RealType value_type;
          typedef Policy policy_type;
 
-         non_central_chi_squared_distribution(RealType df_, RealType lambda) : df(df_), ncp(lambda)
+         BOOST_MATH_GPU_ENABLED non_central_chi_squared_distribution(RealType df_, RealType lambda) : df(df_), ncp(lambda)
          {
-            const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::non_central_chi_squared_distribution(%1%,%1%)";
+            constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::non_central_chi_squared_distribution(%1%,%1%)";
             RealType r;
             detail::check_df(
                function,
@@ -675,17 +680,17 @@ namespace boost
                Policy());
          } // non_central_chi_squared_distribution constructor.
 
-         RealType degrees_of_freedom() const
+         BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom() const
          { // Private data getter function.
             return df;
          }
-         RealType non_centrality() const
+         BOOST_MATH_GPU_ENABLED RealType non_centrality() const
          { // Private data getter function.
             return ncp;
          }
-         static RealType find_degrees_of_freedom(RealType lam, RealType x, RealType p)
+         BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(RealType lam, RealType x, RealType p)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
             typedef typename policies::evaluation<RealType, Policy>::type eval_type;
             typedef typename policies::normalise<
                Policy,
@@ -704,9 +709,9 @@ namespace boost
                function);
          }
          template <class A, class B, class C>
-         static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c)
+         BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(const complemented3_type<A,B,C>& c)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_degrees_of_freedom";
             typedef typename policies::evaluation<RealType, Policy>::type eval_type;
             typedef typename policies::normalise<
                Policy,
@@ -724,9 +729,9 @@ namespace boost
                result,
                function);
          }
-         static RealType find_non_centrality(RealType v, RealType x, RealType p)
+         BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(RealType v, RealType x, RealType p)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_non_centrality";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_non_centrality";
             typedef typename policies::evaluation<RealType, Policy>::type eval_type;
             typedef typename policies::normalise<
                Policy,
@@ -745,9 +750,9 @@ namespace boost
                function);
          }
          template <class A, class B, class C>
-         static RealType find_non_centrality(const complemented3_type<A,B,C>& c)
+         BOOST_MATH_GPU_ENABLED static RealType find_non_centrality(const complemented3_type<A,B,C>& c)
          {
-            const char* function = "non_central_chi_squared<%1%>::find_non_centrality";
+            constexpr auto function = "non_central_chi_squared<%1%>::find_non_centrality";
             typedef typename policies::evaluation<RealType, Policy>::type eval_type;
             typedef typename policies::normalise<
                Policy,
@@ -781,24 +786,24 @@ namespace boost
       // Non-member functions to give properties of the distribution.
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> range(const non_central_chi_squared_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const non_central_chi_squared_distribution<RealType, Policy>& /* dist */)
       { // Range of permissible values for random variable k.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // Max integer?
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // Max integer?
       }
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> support(const non_central_chi_squared_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const non_central_chi_squared_distribution<RealType, Policy>& /* dist */)
       { // Range of supported values for random variable k.
          // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
       }
 
       template <class RealType, class Policy>
-      inline RealType mean(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mean(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       { // Mean of poisson distribution = lambda.
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::mean()";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::mean()";
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
          RealType r;
@@ -816,9 +821,9 @@ namespace boost
       } // mean
 
       template <class RealType, class Policy>
-      inline RealType mode(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mode(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       { // mode.
-         static const char* function = "mode(non_central_chi_squared_distribution<%1%> const&)";
+         constexpr auto function = "mode(non_central_chi_squared_distribution<%1%> const&)";
 
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
@@ -839,9 +844,9 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType variance(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType variance(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       { // variance.
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::variance()";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::variance()";
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
          RealType r;
@@ -862,9 +867,9 @@ namespace boost
       // standard_deviation provided by derived accessors.
 
       template <class RealType, class Policy>
-      inline RealType skewness(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType skewness(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       { // skewness = sqrt(l).
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::skewness()";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::skewness()";
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
          RealType r;
@@ -883,9 +888,9 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType kurtosis_excess(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       {
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::kurtosis_excess()";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::kurtosis_excess()";
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
          RealType r;
@@ -903,21 +908,21 @@ namespace boost
       } // kurtosis_excess
 
       template <class RealType, class Policy>
-      inline RealType kurtosis(const non_central_chi_squared_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const non_central_chi_squared_distribution<RealType, Policy>& dist)
       {
          return kurtosis_excess(dist) + 3;
       }
 
       template <class RealType, class Policy>
-      inline RealType pdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED inline RealType pdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
       { // Probability Density/Mass Function.
          return detail::nccs_pdf(dist, x);
       } // pdf
 
       template <class RealType, class Policy>
-      RealType cdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& x)
       {
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::cdf(%1%)";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::cdf(%1%)";
          RealType k = dist.degrees_of_freedom();
          RealType l = dist.non_centrality();
          RealType r;
@@ -942,9 +947,9 @@ namespace boost
       } // cdf
 
       template <class RealType, class Policy>
-      RealType cdf(const complemented2_type<non_central_chi_squared_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const complemented2_type<non_central_chi_squared_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function
-         const char* function = "boost::math::non_central_chi_squared_distribution<%1%>::cdf(%1%)";
+         constexpr auto function = "boost::math::non_central_chi_squared_distribution<%1%>::cdf(%1%)";
          non_central_chi_squared_distribution<RealType, Policy> const& dist = c.dist;
          RealType x = c.param;
          RealType k = dist.degrees_of_freedom();
@@ -971,13 +976,13 @@ namespace boost
       } // ccdf
 
       template <class RealType, class Policy>
-      inline RealType quantile(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const non_central_chi_squared_distribution<RealType, Policy>& dist, const RealType& p)
       { // Quantile (or Percent Point) function.
          return detail::nccs_quantile(dist, p, false);
       } // quantile
 
       template <class RealType, class Policy>
-      inline RealType quantile(const complemented2_type<non_central_chi_squared_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<non_central_chi_squared_distribution<RealType, Policy>, RealType>& c)
       { // Quantile (or Percent Point) function.
          return detail::nccs_quantile(c.dist, c.param, true);
       } // quantile complement.
diff --git a/include/boost/math/distributions/non_central_f.hpp b/include/boost/math/distributions/non_central_f.hpp
index e93d03e597..dedd437144 100644
--- a/include/boost/math/distributions/non_central_f.hpp
+++ b/include/boost/math/distributions/non_central_f.hpp
@@ -1,7 +1,7 @@
 // boost\math\distributions\non_central_f.hpp
 
 // Copyright John Maddock 2008.
-
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -10,9 +10,13 @@
 #ifndef BOOST_MATH_SPECIAL_NON_CENTRAL_F_HPP
 #define BOOST_MATH_SPECIAL_NON_CENTRAL_F_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/distributions/non_central_beta.hpp>
 #include <boost/math/distributions/detail/generic_mode.hpp>
 #include <boost/math/special_functions/pow.hpp>
+#include <boost/math/policies/policy.hpp>
 
 namespace boost
 {
@@ -25,9 +29,9 @@ namespace boost
          typedef RealType value_type;
          typedef Policy policy_type;
 
-         non_central_f_distribution(RealType v1_, RealType v2_, RealType lambda) : v1(v1_), v2(v2_), ncp(lambda)
+         BOOST_MATH_GPU_ENABLED non_central_f_distribution(RealType v1_, RealType v2_, RealType lambda) : v1(v1_), v2(v2_), ncp(lambda)
          {
-            const char* function = "boost::math::non_central_f_distribution<%1%>::non_central_f_distribution(%1%,%1%)";
+            constexpr auto function = "boost::math::non_central_f_distribution<%1%>::non_central_f_distribution(%1%,%1%)";
             RealType r;
             detail::check_df(
                function,
@@ -42,15 +46,15 @@ namespace boost
                Policy());
          } // non_central_f_distribution constructor.
 
-         RealType degrees_of_freedom1()const
+         BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom1()const
          {
             return v1;
          }
-         RealType degrees_of_freedom2()const
+         BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom2()const
          {
             return v2;
          }
-         RealType non_centrality() const
+         BOOST_MATH_GPU_ENABLED RealType non_centrality() const
          { // Private data getter function.
             return ncp;
          }
@@ -71,24 +75,24 @@ namespace boost
       // Non-member functions to give properties of the distribution.
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> range(const non_central_f_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const non_central_f_distribution<RealType, Policy>& /* dist */)
       { // Range of permissible values for random variable k.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
       }
 
       template <class RealType, class Policy>
-      inline const std::pair<RealType, RealType> support(const non_central_f_distribution<RealType, Policy>& /* dist */)
+      BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const non_central_f_distribution<RealType, Policy>& /* dist */)
       { // Range of supported values for random variable k.
          // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
          using boost::math::tools::max_value;
-         return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
+         return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>());
       }
 
       template <class RealType, class Policy>
-      inline RealType mean(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mean(const non_central_f_distribution<RealType, Policy>& dist)
       {
-         const char* function = "mean(non_central_f_distribution<%1%> const&)";
+         constexpr auto function = "mean(non_central_f_distribution<%1%> const&)";
          RealType v1 = dist.degrees_of_freedom1();
          RealType v2 = dist.degrees_of_freedom2();
          RealType l = dist.non_centrality();
@@ -116,9 +120,9 @@ namespace boost
       } // mean
 
       template <class RealType, class Policy>
-      inline RealType mode(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType mode(const non_central_f_distribution<RealType, Policy>& dist)
       { // mode.
-         static const char* function = "mode(non_central_chi_squared_distribution<%1%> const&)";
+         constexpr auto function = "mode(non_central_chi_squared_distribution<%1%> const&)";
 
          RealType n = dist.degrees_of_freedom1();
          RealType m = dist.degrees_of_freedom2();
@@ -146,9 +150,9 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType variance(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType variance(const non_central_f_distribution<RealType, Policy>& dist)
       { // variance.
-         const char* function = "variance(non_central_f_distribution<%1%> const&)";
+         constexpr auto function = "variance(non_central_f_distribution<%1%> const&)";
          RealType n = dist.degrees_of_freedom1();
          RealType m = dist.degrees_of_freedom2();
          RealType l = dist.non_centrality();
@@ -182,9 +186,9 @@ namespace boost
       // standard_deviation provided by derived accessors.
 
       template <class RealType, class Policy>
-      inline RealType skewness(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType skewness(const non_central_f_distribution<RealType, Policy>& dist)
       { // skewness = sqrt(l).
-         const char* function = "skewness(non_central_f_distribution<%1%> const&)";
+         constexpr auto function = "skewness(non_central_f_distribution<%1%> const&)";
          BOOST_MATH_STD_USING
          RealType n = dist.degrees_of_freedom1();
          RealType m = dist.degrees_of_freedom2();
@@ -219,9 +223,9 @@ namespace boost
       }
 
       template <class RealType, class Policy>
-      inline RealType kurtosis_excess(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const non_central_f_distribution<RealType, Policy>& dist)
       {
-         const char* function = "kurtosis_excess(non_central_f_distribution<%1%> const&)";
+         constexpr auto function = "kurtosis_excess(non_central_f_distribution<%1%> const&)";
          BOOST_MATH_STD_USING
          RealType n = dist.degrees_of_freedom1();
          RealType m = dist.degrees_of_freedom2();
@@ -266,13 +270,13 @@ namespace boost
       } // kurtosis_excess
 
       template <class RealType, class Policy>
-      inline RealType kurtosis(const non_central_f_distribution<RealType, Policy>& dist)
+      BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const non_central_f_distribution<RealType, Policy>& dist)
       {
          return kurtosis_excess(dist) + 3;
       }
 
       template <class RealType, class Policy>
-      inline RealType pdf(const non_central_f_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED inline RealType pdf(const non_central_f_distribution<RealType, Policy>& dist, const RealType& x)
       { // Probability Density/Mass Function.
          typedef typename policies::evaluation<RealType, Policy>::type value_type;
          typedef typename policies::normalise<
@@ -292,9 +296,9 @@ namespace boost
       } // pdf
 
       template <class RealType, class Policy>
-      RealType cdf(const non_central_f_distribution<RealType, Policy>& dist, const RealType& x)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const non_central_f_distribution<RealType, Policy>& dist, const RealType& x)
       {
-         const char* function = "cdf(const non_central_f_distribution<%1%>&, %1%)";
+         constexpr auto function = "cdf(const non_central_f_distribution<%1%>&, %1%)";
          RealType r;
          if(!detail::check_df(
             function,
@@ -333,9 +337,9 @@ namespace boost
       } // cdf
 
       template <class RealType, class Policy>
-      RealType cdf(const complemented2_type<non_central_f_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED RealType cdf(const complemented2_type<non_central_f_distribution<RealType, Policy>, RealType>& c)
       { // Complemented Cumulative Distribution Function
-         const char* function = "cdf(complement(const non_central_f_distribution<%1%>&, %1%))";
+         constexpr auto function = "cdf(complement(const non_central_f_distribution<%1%>&, %1%))";
          RealType r;
          if(!detail::check_df(
             function,
@@ -374,7 +378,7 @@ namespace boost
       } // ccdf
 
       template <class RealType, class Policy>
-      inline RealType quantile(const non_central_f_distribution<RealType, Policy>& dist, const RealType& p)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const non_central_f_distribution<RealType, Policy>& dist, const RealType& p)
       { // Quantile (or Percent Point) function.
          RealType alpha = dist.degrees_of_freedom1() / 2;
          RealType beta = dist.degrees_of_freedom2() / 2;
@@ -388,7 +392,7 @@ namespace boost
       } // quantile
 
       template <class RealType, class Policy>
-      inline RealType quantile(const complemented2_type<non_central_f_distribution<RealType, Policy>, RealType>& c)
+      BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<non_central_f_distribution<RealType, Policy>, RealType>& c)
       { // Quantile (or Percent Point) function.
          RealType alpha = c.dist.degrees_of_freedom1() / 2;
          RealType beta = c.dist.degrees_of_freedom2() / 2;
diff --git a/include/boost/math/distributions/normal.hpp b/include/boost/math/distributions/normal.hpp
index 70259e62b1..9d973fb539 100644
--- a/include/boost/math/distributions/normal.hpp
+++ b/include/boost/math/distributions/normal.hpp
@@ -1,6 +1,6 @@
 //  Copyright John Maddock 2006, 2007.
 //  Copyright Paul A. Bristow 2006, 2007.
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -15,13 +15,15 @@
 // From MathWorld--A Wolfram Web Resource.
 // http://mathworld.wolfram.com/NormalDistribution.html
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/erf.hpp> // for erf/erfc.
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
-
-#include <utility>
-#include <type_traits>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/policies/policy.hpp>
 
 namespace boost{ namespace math{
 
@@ -32,32 +34,32 @@ class normal_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit normal_distribution(RealType l_mean = 0, RealType sd = 1)
+   BOOST_MATH_GPU_ENABLED explicit normal_distribution(RealType l_mean = 0, RealType sd = 1)
       : m_mean(l_mean), m_sd(sd)
    { // Default is a 'standard' normal distribution N01.
-     static const char* function = "boost::math::normal_distribution<%1%>::normal_distribution";
+     constexpr auto function = "boost::math::normal_distribution<%1%>::normal_distribution";
 
      RealType result;
      detail::check_scale(function, sd, &result, Policy());
      detail::check_location(function, l_mean, &result, Policy());
    }
 
-   RealType mean()const
+   BOOST_MATH_GPU_ENABLED RealType mean()const
    { // alias for location.
       return m_mean;
    }
 
-   RealType standard_deviation()const
+   BOOST_MATH_GPU_ENABLED RealType standard_deviation()const
    { // alias for scale.
       return m_sd;
    }
 
    // Synonyms, provided to allow generic use of find_location and find_scale.
-   RealType location()const
+   BOOST_MATH_GPU_ENABLED RealType location()const
    { // location.
       return m_mean;
    }
-   RealType scale()const
+   BOOST_MATH_GPU_ENABLED RealType scale()const
    { // scale.
       return m_sd;
    }
@@ -92,30 +94,30 @@ normal_distribution(RealType)->normal_distribution<typename boost::math::tools::
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const normal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const normal_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   { // Can only use max_value.
     using boost::math::tools::max_value;
-    return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
+    return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + max value.
   }
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const normal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const normal_distribution<RealType, Policy>& /*dist*/)
 { // This is range values for random variable x where cdf rises from 0 to 1, and outside it, the pdf is zero.
-  if (std::numeric_limits<RealType>::has_infinity)
+  BOOST_MATH_IF_CONSTEXPR (boost::math::numeric_limits<RealType>::has_infinity)
   { 
-     return std::pair<RealType, RealType>(-std::numeric_limits<RealType>::infinity(), std::numeric_limits<RealType>::infinity()); // - to + infinity.
+     return boost::math::pair<RealType, RealType>(-boost::math::numeric_limits<RealType>::infinity(), boost::math::numeric_limits<RealType>::infinity()); // - to + infinity.
   }
   else
   { // Can only use max_value.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(-max_value<RealType>(),  max_value<RealType>()); // - to + max value.
+   return boost::math::pair<RealType, RealType>(-max_value<RealType>(),  max_value<RealType>()); // - to + max value.
   }
 }
 
@@ -124,14 +126,14 @@ inline std::pair<RealType, RealType> support(const normal_distribution<RealType,
 #endif
 
 template <class RealType, class Policy>
-inline RealType pdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType sd = dist.standard_deviation();
    RealType mean = dist.mean();
 
-   static const char* function = "boost::math::pdf(const normal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const normal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(false == detail::check_scale(function, sd, &result, Policy()))
@@ -162,16 +164,16 @@ inline RealType pdf(const normal_distribution<RealType, Policy>& dist, const Rea
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    const RealType sd = dist.standard_deviation();
    const RealType mean = dist.mean();
 
-   static const char* function = "boost::math::logpdf(const normal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logpdf(const normal_distribution<%1%>&, %1%)";
 
-   RealType result = -std::numeric_limits<RealType>::infinity();
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
    if(false == detail::check_scale(function, sd, &result, Policy()))
    {
       return result;
@@ -198,13 +200,13 @@ inline RealType logpdf(const normal_distribution<RealType, Policy>& dist, const
 }
 
 template <class RealType, class Policy>
-inline RealType cdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const normal_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType sd = dist.standard_deviation();
    RealType mean = dist.mean();
-   static const char* function = "boost::math::cdf(const normal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const normal_distribution<%1%>&, %1%)";
    RealType result = 0;
    if(false == detail::check_scale(function, sd, &result, Policy()))
    {
@@ -229,13 +231,13 @@ inline RealType cdf(const normal_distribution<RealType, Policy>& dist, const Rea
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const normal_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const normal_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType sd = dist.standard_deviation();
    RealType mean = dist.mean();
-   static const char* function = "boost::math::quantile(const normal_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const normal_distribution<%1%>&, %1%)";
 
    RealType result = 0;
    if(false == detail::check_scale(function, sd, &result, Policy()))
@@ -253,14 +255,14 @@ inline RealType quantile(const normal_distribution<RealType, Policy>& dist, cons
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<normal_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<normal_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType sd = c.dist.standard_deviation();
    RealType mean = c.dist.mean();
    RealType x = c.param;
-   static const char* function = "boost::math::cdf(const complement(normal_distribution<%1%>&), %1%)";
+   constexpr auto function = "boost::math::cdf(const complement(normal_distribution<%1%>&), %1%)";
 
    RealType result = 0;
    if(false == detail::check_scale(function, sd, &result, Policy()))
@@ -281,13 +283,13 @@ inline RealType cdf(const complemented2_type<normal_distribution<RealType, Polic
 } // cdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<normal_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<normal_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING  // for ADL of std functions
 
    RealType sd = c.dist.standard_deviation();
    RealType mean = c.dist.mean();
-   static const char* function = "boost::math::quantile(const complement(normal_distribution<%1%>&), %1%)";
+   constexpr auto function = "boost::math::quantile(const complement(normal_distribution<%1%>&), %1%)";
    RealType result = 0;
    if(false == detail::check_scale(function, sd, &result, Policy()))
       return result;
@@ -303,51 +305,51 @@ inline RealType quantile(const complemented2_type<normal_distribution<RealType,
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType mean(const normal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const normal_distribution<RealType, Policy>& dist)
 {
    return dist.mean();
 }
 
 template <class RealType, class Policy>
-inline RealType standard_deviation(const normal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType standard_deviation(const normal_distribution<RealType, Policy>& dist)
 {
    return dist.standard_deviation();
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const normal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const normal_distribution<RealType, Policy>& dist)
 {
    return dist.mean();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const normal_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const normal_distribution<RealType, Policy>& dist)
 {
    return dist.mean();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const normal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const normal_distribution<RealType, Policy>& /*dist*/)
 {
    return 0;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const normal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const normal_distribution<RealType, Policy>& /*dist*/)
 {
    return 3;
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const normal_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const normal_distribution<RealType, Policy>& /*dist*/)
 {
    return 0;
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const normal_distribution<RealType, Policy> & dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const normal_distribution<RealType, Policy> & dist)
 {
-   using std::log;
+   BOOST_MATH_STD_USING
    RealType arg = constants::two_pi<RealType>()*constants::e<RealType>()*dist.standard_deviation()*dist.standard_deviation();
    return log(arg)/2;
 }
diff --git a/include/boost/math/distributions/pareto.hpp b/include/boost/math/distributions/pareto.hpp
index 778310d10e..97cf8024a0 100644
--- a/include/boost/math/distributions/pareto.hpp
+++ b/include/boost/math/distributions/pareto.hpp
@@ -17,16 +17,15 @@
 // Handbook of Statistical Distributions with Applications, K Krishnamoorthy, ISBN 1-58488-635-8, Chapter 23, pp 257 - 267.
 // Caution KK's a and b are the reverse of Mathworld!
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/special_functions/powm1.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 
-#include <utility> // for BOOST_CURRENT_VALUE?
-#include <limits>
-#include <cmath>
-
 namespace boost
 {
   namespace math
@@ -34,7 +33,7 @@ namespace boost
     namespace detail
     { // Parameter checking.
       template <class RealType, class Policy>
-      inline bool check_pareto_scale(
+      BOOST_MATH_GPU_ENABLED inline bool check_pareto_scale(
         const char* function,
         RealType scale,
         RealType* result, const Policy& pol)
@@ -63,7 +62,7 @@ namespace boost
       } // bool check_pareto_scale
 
       template <class RealType, class Policy>
-      inline bool check_pareto_shape(
+      BOOST_MATH_GPU_ENABLED inline bool check_pareto_shape(
         const char* function,
         RealType shape,
         RealType* result, const Policy& pol)
@@ -92,7 +91,7 @@ namespace boost
       } // bool check_pareto_shape(
 
       template <class RealType, class Policy>
-      inline bool check_pareto_x(
+      BOOST_MATH_GPU_ENABLED inline bool check_pareto_x(
         const char* function,
         RealType const& x,
         RealType* result, const Policy& pol)
@@ -121,7 +120,7 @@ namespace boost
       } // bool check_pareto_x
 
       template <class RealType, class Policy>
-      inline bool check_pareto( // distribution parameters.
+      BOOST_MATH_GPU_ENABLED inline bool check_pareto( // distribution parameters.
         const char* function,
         RealType scale,
         RealType shape,
@@ -140,19 +139,19 @@ namespace boost
       typedef RealType value_type;
       typedef Policy policy_type;
 
-      pareto_distribution(RealType l_scale = 1, RealType l_shape = 1)
+      BOOST_MATH_GPU_ENABLED pareto_distribution(RealType l_scale = 1, RealType l_shape = 1)
         : m_scale(l_scale), m_shape(l_shape)
       { // Constructor.
         RealType result = 0;
         detail::check_pareto("boost::math::pareto_distribution<%1%>::pareto_distribution", l_scale, l_shape, &result, Policy());
       }
 
-      RealType scale()const
+      BOOST_MATH_GPU_ENABLED RealType scale()const
       { // AKA Xm and Wolfram b and beta
         return m_scale;
       }
 
-      RealType shape()const
+      BOOST_MATH_GPU_ENABLED RealType shape()const
       { // AKA k and Wolfram a and alpha
         return m_shape;
       }
@@ -173,25 +172,25 @@ namespace boost
 
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> range(const pareto_distribution<RealType, Policy>& /*dist*/)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const pareto_distribution<RealType, Policy>& /*dist*/)
     { // Range of permissible values for random variable x.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // scale zero to + infinity.
+      return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // scale zero to + infinity.
     } // range
 
     template <class RealType, class Policy>
-    inline const std::pair<RealType, RealType> support(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const pareto_distribution<RealType, Policy>& dist)
     { // Range of supported values for random variable x.
       // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
       using boost::math::tools::max_value;
-      return std::pair<RealType, RealType>(dist.scale(), max_value<RealType>() ); // scale to + infinity.
+      return boost::math::pair<RealType, RealType>(dist.scale(), max_value<RealType>() ); // scale to + infinity.
     } // support
 
     template <class RealType, class Policy>
-    inline RealType pdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType pdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
     {
       BOOST_MATH_STD_USING  // for ADL of std function pow.
-      static const char* function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
       RealType scale = dist.scale();
       RealType shape = dist.shape();
       RealType result = 0;
@@ -207,10 +206,10 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    inline RealType cdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
     {
       BOOST_MATH_STD_USING  // for ADL of std function pow.
-      static const char* function = "boost::math::cdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::cdf(const pareto_distribution<%1%>&, %1%)";
       RealType scale = dist.scale();
       RealType shape = dist.shape();
       RealType result = 0;
@@ -230,10 +229,10 @@ namespace boost
     } // cdf
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const pareto_distribution<RealType, Policy>& dist, const RealType& x)
     {
       BOOST_MATH_STD_USING  // for ADL of std function pow.
-      static const char* function = "boost::math::logcdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::logcdf(const pareto_distribution<%1%>&, %1%)";
       RealType scale = dist.scale();
       RealType shape = dist.shape();
       RealType result = 0;
@@ -244,7 +243,7 @@ namespace boost
 
       if (x <= scale)
       { // regardless of shape, cdf is zero.
-        return -std::numeric_limits<RealType>::infinity();
+        return -boost::math::numeric_limits<RealType>::infinity();
       }
 
       result = log1p(-pow(scale/x, shape), Policy());
@@ -252,10 +251,10 @@ namespace boost
     } // logcdf
 
     template <class RealType, class Policy>
-    inline RealType quantile(const pareto_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const pareto_distribution<RealType, Policy>& dist, const RealType& p)
     {
       BOOST_MATH_STD_USING  // for ADL of std function pow.
-      static const char* function = "boost::math::quantile(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::quantile(const pareto_distribution<%1%>&, %1%)";
       RealType result = 0;
       RealType scale = dist.scale();
       RealType shape = dist.shape();
@@ -279,10 +278,10 @@ namespace boost
     } // quantile
 
     template <class RealType, class Policy>
-    inline RealType cdf(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
     {
        BOOST_MATH_STD_USING  // for ADL of std function pow.
-       static const char* function = "boost::math::cdf(const pareto_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::cdf(const pareto_distribution<%1%>&, %1%)";
        RealType result = 0;
        RealType x = c.param;
        RealType scale = c.dist.scale();
@@ -301,10 +300,10 @@ namespace boost
     } // cdf complement
 
     template <class RealType, class Policy>
-    inline RealType logcdf(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
     {
        BOOST_MATH_STD_USING  // for ADL of std function pow.
-       static const char* function = "boost::math::logcdf(const pareto_distribution<%1%>&, %1%)";
+       constexpr auto function = "boost::math::logcdf(const pareto_distribution<%1%>&, %1%)";
        RealType result = 0;
        RealType x = c.param;
        RealType scale = c.dist.scale();
@@ -323,10 +322,10 @@ namespace boost
     } // logcdf complement
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<pareto_distribution<RealType, Policy>, RealType>& c)
     {
       BOOST_MATH_STD_USING  // for ADL of std function pow.
-      static const char* function = "boost::math::quantile(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::quantile(const pareto_distribution<%1%>&, %1%)";
       RealType result = 0;
       RealType q = c.param;
       RealType scale = c.dist.scale();
@@ -350,10 +349,10 @@ namespace boost
     } // quantile complement
 
     template <class RealType, class Policy>
-    inline RealType mean(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const pareto_distribution<RealType, Policy>& dist)
     {
       RealType result = 0;
-      static const char* function = "boost::math::mean(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::mean(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, dist.scale(), dist.shape(), &result, Policy()))
       {
         return result;
@@ -370,16 +369,16 @@ namespace boost
     } // mean
 
     template <class RealType, class Policy>
-    inline RealType mode(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const pareto_distribution<RealType, Policy>& dist)
     {
       return dist.scale();
     } // mode
 
     template <class RealType, class Policy>
-    inline RealType median(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType median(const pareto_distribution<RealType, Policy>& dist)
     {
       RealType result = 0;
-      static const char* function = "boost::math::median(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::median(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, dist.scale(), dist.shape(), &result, Policy()))
       {
         return result;
@@ -389,12 +388,12 @@ namespace boost
     } // median
 
     template <class RealType, class Policy>
-    inline RealType variance(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const pareto_distribution<RealType, Policy>& dist)
     {
       RealType result = 0;
       RealType scale = dist.scale();
       RealType shape = dist.shape();
-      static const char* function = "boost::math::variance(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::variance(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, scale, shape, &result, Policy()))
       {
         return result;
@@ -414,12 +413,12 @@ namespace boost
     } // variance
 
     template <class RealType, class Policy>
-    inline RealType skewness(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const pareto_distribution<RealType, Policy>& dist)
     {
       BOOST_MATH_STD_USING
       RealType result = 0;
       RealType shape = dist.shape();
-      static const char* function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, dist.scale(), shape, &result, Policy()))
       {
         return result;
@@ -440,11 +439,11 @@ namespace boost
     } // skewness
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const pareto_distribution<RealType, Policy>& dist)
     {
       RealType result = 0;
       RealType shape = dist.shape();
-      static const char* function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, dist.scale(), shape, &result, Policy()))
       {
         return result;
@@ -464,11 +463,11 @@ namespace boost
     } // kurtosis
 
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const pareto_distribution<RealType, Policy>& dist)
     {
       RealType result = 0;
       RealType shape = dist.shape();
-      static const char* function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::pdf(const pareto_distribution<%1%>&, %1%)";
       if(false == detail::check_pareto(function, dist.scale(), shape, &result, Policy()))
       {
         return result;
@@ -488,9 +487,9 @@ namespace boost
     } // kurtosis_excess
 
     template <class RealType, class Policy>
-    inline RealType entropy(const pareto_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType entropy(const pareto_distribution<RealType, Policy>& dist)
     {
-      using std::log;
+      BOOST_MATH_STD_USING
       RealType xm = dist.scale();
       RealType alpha = dist.shape();
       return log(xm/alpha) + 1 + 1/alpha;
diff --git a/include/boost/math/distributions/poisson.hpp b/include/boost/math/distributions/poisson.hpp
index 570a590259..c2fad66be0 100644
--- a/include/boost/math/distributions/poisson.hpp
+++ b/include/boost/math/distributions/poisson.hpp
@@ -2,6 +2,7 @@
 
 // Copyright John Maddock 2006.
 // Copyright Paul A. Bristow 2007.
+// Copyright Matt Borland 2024.
 
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
@@ -36,6 +37,10 @@
 #ifndef BOOST_MATH_SPECIAL_POISSON_HPP
 #define BOOST_MATH_SPECIAL_POISSON_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/gamma.hpp> // for incomplete gamma. gamma_q
 #include <boost/math/special_functions/trunc.hpp> // for incomplete gamma. gamma_q
@@ -46,9 +51,6 @@
 #include <boost/math/tools/roots.hpp> // for root finding.
 #include <boost/math/distributions/detail/inv_discrete_quantile.hpp>
 
-#include <utility>
-#include <limits>
-
 namespace boost
 {
   namespace math
@@ -60,7 +62,7 @@ namespace boost
       // checks are always performed, even if exceptions are not enabled.
 
       template <class RealType, class Policy>
-      inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_mean(const char* function, const RealType& mean, RealType* result, const Policy& pol)
       {
         if(!(boost::math::isfinite)(mean) || (mean < 0))
         {
@@ -73,7 +75,7 @@ namespace boost
       } // bool check_mean
 
       template <class RealType, class Policy>
-      inline bool check_mean_NZ(const char* function, const RealType& mean, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_mean_NZ(const char* function, const RealType& mean, RealType* result, const Policy& pol)
       { // mean == 0 is considered an error.
         if( !(boost::math::isfinite)(mean) || (mean <= 0))
         {
@@ -86,13 +88,13 @@ namespace boost
       } // bool check_mean_NZ
 
       template <class RealType, class Policy>
-      inline bool check_dist(const char* function, const RealType& mean, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist(const char* function, const RealType& mean, RealType* result, const Policy& pol)
       { // Only one check, so this is redundant really but should be optimized away.
         return check_mean_NZ(function, mean, result, pol);
       } // bool check_dist
 
       template <class RealType, class Policy>
-      inline bool check_k(const char* function, const RealType& k, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_k(const char* function, const RealType& k, RealType* result, const Policy& pol)
       {
         if((k < 0) || !(boost::math::isfinite)(k))
         {
@@ -105,7 +107,7 @@ namespace boost
       } // bool check_k
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_k(const char* function, RealType mean, RealType k, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_k(const char* function, RealType mean, RealType k, RealType* result, const Policy& pol)
       {
         if((check_dist(function, mean, result, pol) == false) ||
           (check_k(function, k, result, pol) == false))
@@ -116,7 +118,7 @@ namespace boost
       } // bool check_dist_and_k
 
       template <class RealType, class Policy>
-      inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_prob(const char* function, const RealType& p, RealType* result, const Policy& pol)
       { // Check 0 <= p <= 1
         if(!(boost::math::isfinite)(p) || (p < 0) || (p > 1))
         {
@@ -129,7 +131,7 @@ namespace boost
       } // bool check_prob
 
       template <class RealType, class Policy>
-      inline bool check_dist_and_prob(const char* function, RealType mean,  RealType p, RealType* result, const Policy& pol)
+      BOOST_MATH_GPU_ENABLED inline bool check_dist_and_prob(const char* function, RealType mean,  RealType p, RealType* result, const Policy& pol)
       {
         if((check_dist(function, mean, result, pol) == false) ||
           (check_prob(function, p, result, pol) == false))
@@ -148,7 +150,7 @@ namespace boost
       using value_type = RealType;
       using policy_type = Policy;
 
-      explicit poisson_distribution(RealType l_mean = 1) : m_l(l_mean) // mean (lambda).
+      BOOST_MATH_GPU_ENABLED explicit poisson_distribution(RealType l_mean = 1) : m_l(l_mean) // mean (lambda).
       { // Expected mean number of events that occur during the given interval.
         RealType r;
         poisson_detail::check_dist(
@@ -157,7 +159,7 @@ namespace boost
           &r, Policy());
       } // poisson_distribution constructor.
 
-      RealType mean() const
+      BOOST_MATH_GPU_ENABLED RealType mean() const
       { // Private data getter function.
         return m_l;
       }
@@ -176,28 +178,28 @@ namespace boost
     // Non-member functions to give properties of the distribution.
 
     template <class RealType, class Policy>
-    inline std::pair<RealType, RealType> range(const poisson_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const poisson_distribution<RealType, Policy>& /* dist */)
     { // Range of permissible values for random variable k.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // Max integer?
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), max_value<RealType>()); // Max integer?
     }
 
     template <class RealType, class Policy>
-    inline std::pair<RealType, RealType> support(const poisson_distribution<RealType, Policy>& /* dist */)
+    BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const poisson_distribution<RealType, Policy>& /* dist */)
     { // Range of supported values for random variable k.
        // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
        using boost::math::tools::max_value;
-       return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+       return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
     }
 
     template <class RealType, class Policy>
-    inline RealType mean(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mean(const poisson_distribution<RealType, Policy>& dist)
     { // Mean of poisson distribution = lambda.
       return dist.mean();
     } // mean
 
     template <class RealType, class Policy>
-    inline RealType mode(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType mode(const poisson_distribution<RealType, Policy>& dist)
     { // mode.
       BOOST_MATH_STD_USING // ADL of std functions.
       return floor(dist.mean());
@@ -206,7 +208,7 @@ namespace boost
     // Median now implemented via quantile(half) in derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType variance(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType variance(const poisson_distribution<RealType, Policy>& dist)
     { // variance.
       return dist.mean();
     }
@@ -214,14 +216,14 @@ namespace boost
     // standard_deviation provided by derived accessors.
 
     template <class RealType, class Policy>
-    inline RealType skewness(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType skewness(const poisson_distribution<RealType, Policy>& dist)
     { // skewness = sqrt(l).
       BOOST_MATH_STD_USING // ADL of std functions.
       return 1 / sqrt(dist.mean());
     }
 
     template <class RealType, class Policy>
-    inline RealType kurtosis_excess(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const poisson_distribution<RealType, Policy>& dist)
     { // skewness = sqrt(l).
       return 1 / dist.mean(); // kurtosis_excess 1/mean from Wiki & MathWorld eq 31.
       // http://mathworld.wolfram.com/Kurtosis.html explains that the kurtosis excess
@@ -230,7 +232,7 @@ namespace boost
     } // RealType kurtosis_excess
 
     template <class RealType, class Policy>
-    inline RealType kurtosis(const poisson_distribution<RealType, Policy>& dist)
+    BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const poisson_distribution<RealType, Policy>& dist)
     { // kurtosis is 4th moment about the mean = u4 / sd ^ 4
       // http://en.wikipedia.org/wiki/Kurtosis
       // kurtosis can range from -2 (flat top) to +infinity (sharp peak & heavy tails).
@@ -242,7 +244,7 @@ namespace boost
     } // RealType kurtosis
 
     template <class RealType, class Policy>
-    RealType pdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED RealType pdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
     { // Probability Density/Mass Function.
       // Probability that there are EXACTLY k occurrences (or arrivals).
       BOOST_FPU_EXCEPTION_GUARD
@@ -274,7 +276,7 @@ namespace boost
     } // pdf
 
     template <class RealType, class Policy>
-    RealType logpdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED RealType logpdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
     {
       BOOST_FPU_EXCEPTION_GUARD
 
@@ -283,7 +285,7 @@ namespace boost
 
       RealType mean = dist.mean();
       // Error check:
-      RealType result = -std::numeric_limits<RealType>::infinity();
+      RealType result = -boost::math::numeric_limits<RealType>::infinity();
       if(false == poisson_detail::check_dist_and_k(
         "boost::math::pdf(const poisson_distribution<%1%>&, %1%)",
         mean,
@@ -296,7 +298,7 @@ namespace boost
       // Special case of mean zero, regardless of the number of events k.
       if (mean == 0)
       { // Probability for any k is zero.
-        return std::numeric_limits<RealType>::quiet_NaN();
+        return boost::math::numeric_limits<RealType>::quiet_NaN();
       }
       
       // Special case where k and lambda are both positive
@@ -310,7 +312,7 @@ namespace boost
     }
 
     template <class RealType, class Policy>
-    RealType cdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
+    BOOST_MATH_GPU_ENABLED RealType cdf(const poisson_distribution<RealType, Policy>& dist, const RealType& k)
     { // Cumulative Distribution Function Poisson.
       // The random variate k is the number of occurrences(or arrivals)
       // k argument may be integral, signed, or unsigned, or floating point.
@@ -361,7 +363,7 @@ namespace boost
     } // binomial cdf
 
     template <class RealType, class Policy>
-    RealType cdf(const complemented2_type<poisson_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED RealType cdf(const complemented2_type<poisson_distribution<RealType, Policy>, RealType>& c)
     { // Complemented Cumulative Distribution Function Poisson
       // The random variate k is the number of events, occurrences or arrivals.
       // k argument may be integral, signed, or unsigned, or floating point.
@@ -411,10 +413,10 @@ namespace boost
     } // poisson ccdf
 
     template <class RealType, class Policy>
-    inline RealType quantile(const poisson_distribution<RealType, Policy>& dist, const RealType& p)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const poisson_distribution<RealType, Policy>& dist, const RealType& p)
     { // Quantile (or Percent Point) Poisson function.
       // Return the number of expected events k for a given probability p.
-      static const char* function = "boost::math::quantile(const poisson_distribution<%1%>&, %1%)";
+      constexpr auto function = "boost::math::quantile(const poisson_distribution<%1%>&, %1%)";
       RealType result = 0; // of Argument checks:
       if(false == poisson_detail::check_prob(
         function,
@@ -443,7 +445,7 @@ namespace boost
          return policies::raise_overflow_error<RealType>(function, 0, Policy());
       }
       using discrete_type = typename Policy::discrete_quantile_type;
-      std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+      boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
       RealType guess;
       RealType factor = 8;
       RealType z = dist.mean();
@@ -477,13 +479,13 @@ namespace boost
    } // quantile
 
     template <class RealType, class Policy>
-    inline RealType quantile(const complemented2_type<poisson_distribution<RealType, Policy>, RealType>& c)
+    BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<poisson_distribution<RealType, Policy>, RealType>& c)
     { // Quantile (or Percent Point) of Poisson function.
       // Return the number of expected events k for a given
       // complement of the probability q.
       //
       // Error checks:
-      static const char* function = "boost::math::quantile(complement(const poisson_distribution<%1%>&, %1%))";
+      constexpr auto function = "boost::math::quantile(complement(const poisson_distribution<%1%>&, %1%))";
       RealType q = c.param;
       const poisson_distribution<RealType, Policy>& dist = c.dist;
       RealType result = 0;  // of argument checks.
@@ -514,7 +516,7 @@ namespace boost
          return 0;  // Exact result regardless of discrete-quantile Policy
       }
       using discrete_type = typename Policy::discrete_quantile_type;
-      std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+      boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
       RealType guess;
       RealType factor = 8;
       RealType z = dist.mean();
diff --git a/include/boost/math/distributions/rayleigh.hpp b/include/boost/math/distributions/rayleigh.hpp
index 4e741313c8..155525b539 100644
--- a/include/boost/math/distributions/rayleigh.hpp
+++ b/include/boost/math/distributions/rayleigh.hpp
@@ -7,6 +7,10 @@
 #ifndef BOOST_STATS_rayleigh_HPP
 #define BOOST_STATS_rayleigh_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/special_functions/log1p.hpp>
@@ -19,16 +23,12 @@
 # pragma warning(disable: 4702) // unreachable code (return after domain_error throw).
 #endif
 
-#include <utility>
-#include <limits>
-#include <cmath>
-
 namespace boost{ namespace math{
 
 namespace detail
 { // Error checks:
   template <class RealType, class Policy>
-  inline bool verify_sigma(const char* function, RealType sigma, RealType* presult, const Policy& pol)
+  BOOST_MATH_GPU_ENABLED inline bool verify_sigma(const char* function, RealType sigma, RealType* presult, const Policy& pol)
   {
      if((sigma <= 0) || (!(boost::math::isfinite)(sigma)))
      {
@@ -41,7 +41,7 @@ namespace detail
   } // bool verify_sigma
 
   template <class RealType, class Policy>
-  inline bool verify_rayleigh_x(const char* function, RealType x, RealType* presult, const Policy& pol)
+  BOOST_MATH_GPU_ENABLED inline bool verify_rayleigh_x(const char* function, RealType x, RealType* presult, const Policy& pol)
   {
      if((x < 0) || (boost::math::isnan)(x))
      {
@@ -61,14 +61,14 @@ class rayleigh_distribution
    using value_type = RealType;
    using policy_type = Policy;
 
-   explicit rayleigh_distribution(RealType l_sigma = 1)
+   BOOST_MATH_GPU_ENABLED explicit rayleigh_distribution(RealType l_sigma = 1)
       : m_sigma(l_sigma)
    {
       RealType err;
       detail::verify_sigma("boost::math::rayleigh_distribution<%1%>::rayleigh_distribution", l_sigma, &err, Policy());
    } // rayleigh_distribution
 
-   RealType sigma()const
+   BOOST_MATH_GPU_ENABLED RealType sigma()const
    { // Accessor.
      return m_sigma;
    }
@@ -85,28 +85,28 @@ rayleigh_distribution(RealType)->rayleigh_distribution<typename boost::math::too
 #endif
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> range(const rayleigh_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> range(const rayleigh_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0), std::numeric_limits<RealType>::has_infinity ? std::numeric_limits<RealType>::infinity() : max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0), boost::math::numeric_limits<RealType>::has_infinity ? boost::math::numeric_limits<RealType>::infinity() : max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline std::pair<RealType, RealType> support(const rayleigh_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<RealType, RealType> support(const rayleigh_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   return std::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(static_cast<RealType>(0),  max_value<RealType>());
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std function exp.
 
    RealType sigma = dist.sigma();
    RealType result = 0;
-   static const char* function = "boost::math::pdf(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::pdf(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -125,13 +125,13 @@ inline RealType pdf(const rayleigh_distribution<RealType, Policy>& dist, const R
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType logpdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logpdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std function exp.
 
    const RealType sigma = dist.sigma();
-   RealType result = -std::numeric_limits<RealType>::infinity();
-   static const char* function = "boost::math::logpdf(const rayleigh_distribution<%1%>&, %1%)";
+   RealType result = -boost::math::numeric_limits<RealType>::infinity();
+   constexpr auto function = "boost::math::logpdf(const rayleigh_distribution<%1%>&, %1%)";
 
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
@@ -151,13 +151,13 @@ inline RealType logpdf(const rayleigh_distribution<RealType, Policy>& dist, cons
 } // logpdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
    RealType sigma = dist.sigma();
-   static const char* function = "boost::math::cdf(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -171,33 +171,33 @@ inline RealType cdf(const rayleigh_distribution<RealType, Policy>& dist, const R
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType logcdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const rayleigh_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
    RealType sigma = dist.sigma();
-   static const char* function = "boost::math::logcdf(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
-      return -std::numeric_limits<RealType>::infinity();
+      return -boost::math::numeric_limits<RealType>::infinity();
    }
    if(false == detail::verify_rayleigh_x(function, x, &result, Policy()))
    {
-      return -std::numeric_limits<RealType>::infinity();
+      return -boost::math::numeric_limits<RealType>::infinity();
    }
    result = log1p(-exp(-x * x / ( 2 * sigma * sigma)), Policy());   
    return result;
 } // logcdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const rayleigh_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const rayleigh_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
    RealType sigma = dist.sigma();
-   static const char* function = "boost::math::quantile(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
       return result;
    if(false == detail::check_probability(function, p, &result, Policy()))
@@ -216,13 +216,13 @@ inline RealType quantile(const rayleigh_distribution<RealType, Policy>& dist, co
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
    RealType sigma = c.dist.sigma();
-   static const char* function = "boost::math::cdf(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::cdf(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -241,21 +241,21 @@ inline RealType cdf(const complemented2_type<rayleigh_distribution<RealType, Pol
 } // cdf complement
 
 template <class RealType, class Policy>
-inline RealType logcdf(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType logcdf(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
 
    RealType result = 0;
    RealType sigma = c.dist.sigma();
-   static const char* function = "boost::math::logcdf(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::logcdf(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
-      return -std::numeric_limits<RealType>::infinity();
+      return -boost::math::numeric_limits<RealType>::infinity();
    }
    RealType x = c.param;
    if(false == detail::verify_rayleigh_x(function, x, &result, Policy()))
    {
-      return -std::numeric_limits<RealType>::infinity();
+      return -boost::math::numeric_limits<RealType>::infinity();
    }
    RealType ea = x * x / (2 * sigma * sigma);
    // Fix for VC11/12 x64 bug in exp(float):
@@ -266,13 +266,13 @@ inline RealType logcdf(const complemented2_type<rayleigh_distribution<RealType,
 } // logcdf complement
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<rayleigh_distribution<RealType, Policy>, RealType>& c)
 {
    BOOST_MATH_STD_USING // for ADL of std functions, log & sqrt.
 
    RealType result = 0;
    RealType sigma = c.dist.sigma();
-   static const char* function = "boost::math::quantile(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -295,11 +295,11 @@ inline RealType quantile(const complemented2_type<rayleigh_distribution<RealType
 } // quantile complement
 
 template <class RealType, class Policy>
-inline RealType mean(const rayleigh_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const rayleigh_distribution<RealType, Policy>& dist)
 {
    RealType result = 0;
    RealType sigma = dist.sigma();
-   static const char* function = "boost::math::mean(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::mean(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -309,11 +309,11 @@ inline RealType mean(const rayleigh_distribution<RealType, Policy>& dist)
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const rayleigh_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const rayleigh_distribution<RealType, Policy>& dist)
 {
    RealType result = 0;
    RealType sigma = dist.sigma();
-   static const char* function = "boost::math::variance(const rayleigh_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::variance(const rayleigh_distribution<%1%>&, %1%)";
    if(false == detail::verify_sigma(function, sigma, &result, Policy()))
    {
       return result;
@@ -323,20 +323,20 @@ inline RealType variance(const rayleigh_distribution<RealType, Policy>& dist)
 } // variance
 
 template <class RealType, class Policy>
-inline RealType mode(const rayleigh_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const rayleigh_distribution<RealType, Policy>& dist)
 {
    return dist.sigma();
 }
 
 template <class RealType, class Policy>
-inline RealType median(const rayleigh_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType median(const rayleigh_distribution<RealType, Policy>& dist)
 {
    using boost::math::constants::root_ln_four;
    return root_ln_four<RealType>() * dist.sigma();
 }
 
 template <class RealType, class Policy>
-inline RealType skewness(const rayleigh_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const rayleigh_distribution<RealType, Policy>& /*dist*/)
 {
   return static_cast<RealType>(0.63111065781893713819189935154422777984404221106391L);
   // Computed using NTL at 150 bit, about 50 decimal digits.
@@ -344,7 +344,7 @@ inline RealType skewness(const rayleigh_distribution<RealType, Policy>& /*dist*/
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const rayleigh_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const rayleigh_distribution<RealType, Policy>& /*dist*/)
 {
   return static_cast<RealType>(3.2450893006876380628486604106197544154170667057995L);
   // Computed using NTL at 150 bit, about 50 decimal digits.
@@ -352,7 +352,7 @@ inline RealType kurtosis(const rayleigh_distribution<RealType, Policy>& /*dist*/
 }
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const rayleigh_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const rayleigh_distribution<RealType, Policy>& /*dist*/)
 {
   return static_cast<RealType>(0.2450893006876380628486604106197544154170667057995L);
   // Computed using NTL at 150 bit, about 50 decimal digits.
@@ -360,9 +360,9 @@ inline RealType kurtosis_excess(const rayleigh_distribution<RealType, Policy>& /
 } // kurtosis_excess
 
 template <class RealType, class Policy>
-inline RealType entropy(const rayleigh_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const rayleigh_distribution<RealType, Policy>& dist)
 {
-   using std::log;
+   BOOST_MATH_STD_USING
    return 1 + log(dist.sigma()*constants::one_div_root_two<RealType>()) + constants::euler<RealType>()/2;
 }
 
diff --git a/include/boost/math/distributions/students_t.hpp b/include/boost/math/distributions/students_t.hpp
index b01b8aa0fc..39f20d6e41 100644
--- a/include/boost/math/distributions/students_t.hpp
+++ b/include/boost/math/distributions/students_t.hpp
@@ -1,7 +1,7 @@
 //  Copyright John Maddock 2006.
 //  Copyright Paul A. Bristow 2006, 2012, 2017.
 //  Copyright Thomas Mang 2012.
-
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,14 +12,17 @@
 // http://en.wikipedia.org/wiki/Student%27s_t_distribution
 // http://www.itl.nist.gov/div898/handbook/eda/section3/eda3664.htm
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/beta.hpp> // for ibeta(a, b, x).
 #include <boost/math/special_functions/digamma.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/normal.hpp> 
-
-#include <utility>
+#include <boost/math/policies/policy.hpp>
 
 #ifdef _MSC_VER
 # pragma warning(push)
@@ -35,20 +38,20 @@ class students_t_distribution
    typedef RealType value_type;
    typedef Policy policy_type;
 
-   students_t_distribution(RealType df) : df_(df)
+   BOOST_MATH_GPU_ENABLED students_t_distribution(RealType df) : df_(df)
    { // Constructor.
       RealType result;
       detail::check_df_gt0_to_inf( // Checks that df > 0 or df == inf.
          "boost::math::students_t_distribution<%1%>::students_t_distribution", df_, &result, Policy());
    } // students_t_distribution
 
-   RealType degrees_of_freedom()const
+   BOOST_MATH_GPU_ENABLED RealType degrees_of_freedom()const
    {
       return df_;
    }
 
    // Parameter estimation:
-   static RealType find_degrees_of_freedom(
+   BOOST_MATH_GPU_ENABLED static RealType find_degrees_of_freedom(
       RealType difference_from_mean,
       RealType alpha,
       RealType beta,
@@ -68,26 +71,26 @@ students_t_distribution(RealType)->students_t_distribution<typename boost::math:
 #endif
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> range(const students_t_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const students_t_distribution<RealType, Policy>& /*dist*/)
 { // Range of permissible values for random variable x.
   // Now including infinity.
    using boost::math::tools::max_value;
-   //return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
-   return std::pair<RealType, RealType>(((::std::numeric_limits<RealType>::is_specialized & ::std::numeric_limits<RealType>::has_infinity) ? -std::numeric_limits<RealType>::infinity() : -max_value<RealType>()), ((::std::numeric_limits<RealType>::is_specialized & ::std::numeric_limits<RealType>::has_infinity) ? +std::numeric_limits<RealType>::infinity() : +max_value<RealType>()));
+   //return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(((::boost::math::numeric_limits<RealType>::is_specialized & ::boost::math::numeric_limits<RealType>::has_infinity) ? -boost::math::numeric_limits<RealType>::infinity() : -max_value<RealType>()), ((::boost::math::numeric_limits<RealType>::is_specialized & ::boost::math::numeric_limits<RealType>::has_infinity) ? +boost::math::numeric_limits<RealType>::infinity() : +max_value<RealType>()));
 }
 
 template <class RealType, class Policy>
-inline const std::pair<RealType, RealType> support(const students_t_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const students_t_distribution<RealType, Policy>& /*dist*/)
 { // Range of supported values for random variable x.
   // Now including infinity.
    // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
    using boost::math::tools::max_value;
-   //return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
-   return std::pair<RealType, RealType>(((::std::numeric_limits<RealType>::is_specialized & ::std::numeric_limits<RealType>::has_infinity) ? -std::numeric_limits<RealType>::infinity() : -max_value<RealType>()), ((::std::numeric_limits<RealType>::is_specialized & ::std::numeric_limits<RealType>::has_infinity) ? +std::numeric_limits<RealType>::infinity() : +max_value<RealType>()));
+   //return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
+   return boost::math::pair<RealType, RealType>(((::boost::math::numeric_limits<RealType>::is_specialized & ::boost::math::numeric_limits<RealType>::has_infinity) ? -boost::math::numeric_limits<RealType>::infinity() : -max_value<RealType>()), ((::boost::math::numeric_limits<RealType>::is_specialized & ::boost::math::numeric_limits<RealType>::has_infinity) ? +boost::math::numeric_limits<RealType>::infinity() : +max_value<RealType>()));
 }
 
 template <class RealType, class Policy>
-inline RealType pdf(const students_t_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType pdf(const students_t_distribution<RealType, Policy>& dist, const RealType& x)
 {
    BOOST_FPU_EXCEPTION_GUARD
    BOOST_MATH_STD_USING  // for ADL of std functions.
@@ -135,7 +138,7 @@ inline RealType pdf(const students_t_distribution<RealType, Policy>& dist, const
 } // pdf
 
 template <class RealType, class Policy>
-inline RealType cdf(const students_t_distribution<RealType, Policy>& dist, const RealType& x)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const students_t_distribution<RealType, Policy>& dist, const RealType& x)
 {
    RealType error_result;
    // degrees_of_freedom > 0 or infinity check:
@@ -209,7 +212,7 @@ inline RealType cdf(const students_t_distribution<RealType, Policy>& dist, const
 } // cdf
 
 template <class RealType, class Policy>
-inline RealType quantile(const students_t_distribution<RealType, Policy>& dist, const RealType& p)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const students_t_distribution<RealType, Policy>& dist, const RealType& p)
 {
    BOOST_MATH_STD_USING // for ADL of std functions
    //
@@ -218,7 +221,7 @@ inline RealType quantile(const students_t_distribution<RealType, Policy>& dist,
  
    // Check for domain errors:
    RealType df = dist.degrees_of_freedom();
-   static const char* function = "boost::math::quantile(const students_t_distribution<%1%>&, %1%)";
+   constexpr auto function = "boost::math::quantile(const students_t_distribution<%1%>&, %1%)";
    RealType error_result;
    if(false == (detail::check_df_gt0_to_inf( // Check that df > 0 or == +infinity.
       function, df, &error_result, Policy())
@@ -263,13 +266,13 @@ inline RealType quantile(const students_t_distribution<RealType, Policy>& dist,
 } // quantile
 
 template <class RealType, class Policy>
-inline RealType cdf(const complemented2_type<students_t_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<students_t_distribution<RealType, Policy>, RealType>& c)
 {
    return cdf(c.dist, -c.param);
 }
 
 template <class RealType, class Policy>
-inline RealType quantile(const complemented2_type<students_t_distribution<RealType, Policy>, RealType>& c)
+BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<students_t_distribution<RealType, Policy>, RealType>& c)
 {
    return -quantile(c.dist, c.param);
 }
@@ -284,10 +287,10 @@ namespace detail{
 template <class RealType, class Policy>
 struct sample_size_func
 {
-   sample_size_func(RealType a, RealType b, RealType s, RealType d)
+   BOOST_MATH_GPU_ENABLED sample_size_func(RealType a, RealType b, RealType s, RealType d)
       : alpha(a), beta(b), ratio(s*s/(d*d)) {}
 
-   RealType operator()(const RealType& df)
+   BOOST_MATH_GPU_ENABLED RealType operator()(const RealType& df)
    {
       if(df <= tools::min_value<RealType>())
       { // 
@@ -308,14 +311,14 @@ struct sample_size_func
 }  // namespace detail
 
 template <class RealType, class Policy>
-RealType students_t_distribution<RealType, Policy>::find_degrees_of_freedom(
+BOOST_MATH_GPU_ENABLED RealType students_t_distribution<RealType, Policy>::find_degrees_of_freedom(
       RealType difference_from_mean,
       RealType alpha,
       RealType beta,
       RealType sd,
       RealType hint)
 {
-   static const char* function = "boost::math::students_t_distribution<%1%>::find_degrees_of_freedom";
+   constexpr auto function = "boost::math::students_t_distribution<%1%>::find_degrees_of_freedom";
    //
    // Check for domain errors:
    //
@@ -330,8 +333,8 @@ RealType students_t_distribution<RealType, Policy>::find_degrees_of_freedom(
 
    detail::sample_size_func<RealType, Policy> f(alpha, beta, sd, difference_from_mean);
    tools::eps_tolerance<RealType> tol(policies::digits<RealType, Policy>());
-   std::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
-   std::pair<RealType, RealType> r = tools::bracket_and_solve_root(f, hint, RealType(2), false, tol, max_iter, Policy());
+   boost::math::uintmax_t max_iter = policies::get_max_root_iterations<Policy>();
+   boost::math::pair<RealType, RealType> r = tools::bracket_and_solve_root(f, hint, RealType(2), false, tol, max_iter, Policy());
    RealType result = r.first + (r.second - r.first) / 2;
    if(max_iter >= policies::get_max_root_iterations<Policy>())
    {
@@ -342,14 +345,14 @@ RealType students_t_distribution<RealType, Policy>::find_degrees_of_freedom(
 }
 
 template <class RealType, class Policy>
-inline RealType mode(const students_t_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType mode(const students_t_distribution<RealType, Policy>& /*dist*/)
 {
   // Assume no checks on degrees of freedom are useful (unlike mean).
    return 0; // Always zero by definition.
 }
 
 template <class RealType, class Policy>
-inline RealType median(const students_t_distribution<RealType, Policy>& /*dist*/)
+BOOST_MATH_GPU_ENABLED inline RealType median(const students_t_distribution<RealType, Policy>& /*dist*/)
 {
    // Assume no checks on degrees of freedom are useful (unlike mean).
    return 0; // Always zero by definition.
@@ -358,7 +361,7 @@ inline RealType median(const students_t_distribution<RealType, Policy>& /*dist*/
 // See section 5.1 on moments at  http://en.wikipedia.org/wiki/Student%27s_t-distribution
 
 template <class RealType, class Policy>
-inline RealType mean(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType mean(const students_t_distribution<RealType, Policy>& dist)
 {  // Revised for https://svn.boost.org/trac/boost/ticket/7177
    RealType df = dist.degrees_of_freedom();
    if(((boost::math::isnan)(df)) || (df <= 1) ) 
@@ -366,13 +369,13 @@ inline RealType mean(const students_t_distribution<RealType, Policy>& dist)
       return policies::raise_domain_error<RealType>(
       "boost::math::mean(students_t_distribution<%1%> const&, %1%)",
       "Mean is undefined for degrees of freedom < 1 but got %1%.", df, Policy());
-      return std::numeric_limits<RealType>::quiet_NaN();
+      return boost::math::numeric_limits<RealType>::quiet_NaN();
    }
    return 0;
 } // mean
 
 template <class RealType, class Policy>
-inline RealType variance(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType variance(const students_t_distribution<RealType, Policy>& dist)
 { // http://en.wikipedia.org/wiki/Student%27s_t-distribution
   // Revised for https://svn.boost.org/trac/boost/ticket/7177
   RealType df = dist.degrees_of_freedom();
@@ -382,7 +385,7 @@ inline RealType variance(const students_t_distribution<RealType, Policy>& dist)
       "boost::math::variance(students_t_distribution<%1%> const&, %1%)",
       "variance is undefined for degrees of freedom <= 2, but got %1%.",
       df, Policy());
-    return std::numeric_limits<RealType>::quiet_NaN(); // Undefined.
+    return boost::math::numeric_limits<RealType>::quiet_NaN(); // Undefined.
   }
   if ((boost::math::isinf)(df))
   { // +infinity.
@@ -404,7 +407,7 @@ inline RealType variance(const students_t_distribution<RealType, Policy>& dist)
 } // variance
 
 template <class RealType, class Policy>
-inline RealType skewness(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType skewness(const students_t_distribution<RealType, Policy>& dist)
 {
     RealType df = dist.degrees_of_freedom();
    if( ((boost::math::isnan)(df)) || (dist.degrees_of_freedom() <= 3))
@@ -413,13 +416,13 @@ inline RealType skewness(const students_t_distribution<RealType, Policy>& dist)
          "boost::math::skewness(students_t_distribution<%1%> const&, %1%)",
          "Skewness is undefined for degrees of freedom <= 3, but got %1%.",
          dist.degrees_of_freedom(), Policy());
-      return std::numeric_limits<RealType>::quiet_NaN();
+      return boost::math::numeric_limits<RealType>::quiet_NaN();
    }
    return 0; // For all valid df, including infinity.
 } // skewness
 
 template <class RealType, class Policy>
-inline RealType kurtosis(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const students_t_distribution<RealType, Policy>& dist)
 {
    RealType df = dist.degrees_of_freedom();
    if(((boost::math::isnan)(df)) || (df <= 4))
@@ -428,7 +431,7 @@ inline RealType kurtosis(const students_t_distribution<RealType, Policy>& dist)
        "boost::math::kurtosis(students_t_distribution<%1%> const&, %1%)",
        "Kurtosis is undefined for degrees of freedom <= 4, but got %1%.",
         df, Policy());
-        return std::numeric_limits<RealType>::quiet_NaN(); // Undefined.
+        return boost::math::numeric_limits<RealType>::quiet_NaN(); // Undefined.
    }
    if ((boost::math::isinf)(df))
    { // +infinity.
@@ -451,7 +454,7 @@ inline RealType kurtosis(const students_t_distribution<RealType, Policy>& dist)
 } // kurtosis
 
 template <class RealType, class Policy>
-inline RealType kurtosis_excess(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const students_t_distribution<RealType, Policy>& dist)
 {
    // see http://mathworld.wolfram.com/Kurtosis.html
 
@@ -462,7 +465,7 @@ inline RealType kurtosis_excess(const students_t_distribution<RealType, Policy>&
        "boost::math::kurtosis_excess(students_t_distribution<%1%> const&, %1%)",
        "Kurtosis_excess is undefined for degrees of freedom <= 4, but got %1%.",
       df, Policy());
-     return std::numeric_limits<RealType>::quiet_NaN(); // Undefined.
+     return boost::math::numeric_limits<RealType>::quiet_NaN(); // Undefined.
    }
    if ((boost::math::isinf)(df))
    { // +infinity.
@@ -484,10 +487,9 @@ inline RealType kurtosis_excess(const students_t_distribution<RealType, Policy>&
 }
 
 template <class RealType, class Policy>
-inline RealType entropy(const students_t_distribution<RealType, Policy>& dist)
+BOOST_MATH_GPU_ENABLED inline RealType entropy(const students_t_distribution<RealType, Policy>& dist)
 {
-   using std::log;
-   using std::sqrt;
+   BOOST_MATH_STD_USING
    RealType v = dist.degrees_of_freedom();
    RealType vp1 = (v+1)/2;
    RealType vd2 = v/2;
diff --git a/include/boost/math/distributions/triangular.hpp b/include/boost/math/distributions/triangular.hpp
index 950d78147f..b333ddbc31 100644
--- a/include/boost/math/distributions/triangular.hpp
+++ b/include/boost/math/distributions/triangular.hpp
@@ -16,20 +16,20 @@
 
 // http://en.wikipedia.org/wiki/Triangular_distribution
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/special_functions/expm1.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 #include <boost/math/constants/constants.hpp>
 
-#include <utility>
-
 namespace boost{ namespace math
 {
   namespace detail
   {
     template <class RealType, class Policy>
-    inline bool check_triangular_lower(
+    BOOST_MATH_GPU_ENABLED inline bool check_triangular_lower(
       const char* function,
       RealType lower,
       RealType* result, const Policy& pol)
@@ -48,7 +48,7 @@ namespace boost{ namespace math
     } // bool check_triangular_lower(
 
     template <class RealType, class Policy>
-    inline bool check_triangular_mode(
+    BOOST_MATH_GPU_ENABLED inline bool check_triangular_mode(
       const char* function,
       RealType mode,
       RealType* result, const Policy& pol)
@@ -67,7 +67,7 @@ namespace boost{ namespace math
     } // bool check_triangular_mode(
 
     template <class RealType, class Policy>
-    inline bool check_triangular_upper(
+    BOOST_MATH_GPU_ENABLED inline bool check_triangular_upper(
       const char* function,
       RealType upper,
       RealType* result, const Policy& pol)
@@ -86,7 +86,7 @@ namespace boost{ namespace math
     } // bool check_triangular_upper(
 
     template <class RealType, class Policy>
-    inline bool check_triangular_x(
+    BOOST_MATH_GPU_ENABLED inline bool check_triangular_x(
       const char* function,
       RealType const& x,
       RealType* result, const Policy& pol)
@@ -105,7 +105,7 @@ namespace boost{ namespace math
     } // bool check_triangular_x
 
     template <class RealType, class Policy>
-    inline bool check_triangular(
+    BOOST_MATH_GPU_ENABLED inline bool check_triangular(
       const char* function,
       RealType lower,
       RealType mode,
@@ -153,7 +153,7 @@ namespace boost{ namespace math
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    triangular_distribution(RealType l_lower = -1, RealType l_mode = 0, RealType l_upper = 1)
+    BOOST_MATH_GPU_ENABLED triangular_distribution(RealType l_lower = -1, RealType l_mode = 0, RealType l_upper = 1)
       : m_lower(l_lower), m_mode(l_mode), m_upper(l_upper) // Constructor.
     { // Evans says 'standard triangular' is lower 0, mode 1/2, upper 1,
       // has median sqrt(c/2) for c <=1/2 and 1 - sqrt(1-c)/2 for c >= 1/2
@@ -163,15 +163,15 @@ namespace boost{ namespace math
       detail::check_triangular("boost::math::triangular_distribution<%1%>::triangular_distribution",l_lower, l_mode, l_upper, &result, Policy());
     }
     // Accessor functions.
-    RealType lower()const
+    BOOST_MATH_GPU_ENABLED RealType lower()const
     {
       return m_lower;
     }
-    RealType mode()const
+    BOOST_MATH_GPU_ENABLED RealType mode()const
     {
       return m_mode;
     }
-    RealType upper()const
+    BOOST_MATH_GPU_ENABLED RealType upper()const
     {
       return m_upper;
     }
@@ -194,23 +194,23 @@ namespace boost{ namespace math
   #endif
 
   template <class RealType, class Policy>
-  inline const std::pair<RealType, RealType> range(const triangular_distribution<RealType, Policy>& /* dist */)
+  BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const triangular_distribution<RealType, Policy>& /* dist */)
   { // Range of permissible values for random variable x.
     using boost::math::tools::max_value;
-    return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
+    return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>());
   }
 
   template <class RealType, class Policy>
-  inline const std::pair<RealType, RealType> support(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const triangular_distribution<RealType, Policy>& dist)
   { // Range of supported values for random variable x.
     // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
-    return std::pair<RealType, RealType>(dist.lower(), dist.upper());
+    return boost::math::pair<RealType, RealType>(dist.lower(), dist.upper());
   }
 
   template <class RealType, class Policy>
-  RealType pdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
+  BOOST_MATH_GPU_ENABLED RealType pdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
   {
-    static const char* function = "boost::math::pdf(const triangular_distribution<%1%>&, %1%)";
+    constexpr auto function = "boost::math::pdf(const triangular_distribution<%1%>&, %1%)";
     RealType lower = dist.lower();
     RealType mode = dist.mode();
     RealType upper = dist.upper();
@@ -246,9 +246,9 @@ namespace boost{ namespace math
   } // RealType pdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
 
   template <class RealType, class Policy>
-  inline RealType cdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
+  BOOST_MATH_GPU_ENABLED inline RealType cdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
   {
-    static const char* function = "boost::math::cdf(const triangular_distribution<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(const triangular_distribution<%1%>&, %1%)";
     RealType lower = dist.lower();
     RealType mode = dist.mode();
     RealType upper = dist.upper();
@@ -281,10 +281,10 @@ namespace boost{ namespace math
   } // RealType cdf(const triangular_distribution<RealType, Policy>& dist, const RealType& x)
 
   template <class RealType, class Policy>
-  RealType quantile(const triangular_distribution<RealType, Policy>& dist, const RealType& p)
+  BOOST_MATH_GPU_ENABLED RealType quantile(const triangular_distribution<RealType, Policy>& dist, const RealType& p)
   {
     BOOST_MATH_STD_USING  // for ADL of std functions (sqrt).
-    static const char* function = "boost::math::quantile(const triangular_distribution<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(const triangular_distribution<%1%>&, %1%)";
     RealType lower = dist.lower();
     RealType mode = dist.mode();
     RealType upper = dist.upper();
@@ -324,9 +324,9 @@ namespace boost{ namespace math
   } // RealType quantile(const triangular_distribution<RealType, Policy>& dist, const RealType& q)
 
   template <class RealType, class Policy>
-  RealType cdf(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
+  BOOST_MATH_GPU_ENABLED RealType cdf(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
   {
-    static const char* function = "boost::math::cdf(const triangular_distribution<%1%>&, %1%)";
+    constexpr auto function = "boost::math::cdf(const triangular_distribution<%1%>&, %1%)";
     RealType lower = c.dist.lower();
     RealType mode = c.dist.mode();
     RealType upper = c.dist.upper();
@@ -359,10 +359,10 @@ namespace boost{ namespace math
   } // RealType cdf(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
 
   template <class RealType, class Policy>
-  RealType quantile(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
+  BOOST_MATH_GPU_ENABLED RealType quantile(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
   {
     BOOST_MATH_STD_USING  // Aid ADL for sqrt.
-    static const char* function = "boost::math::quantile(const triangular_distribution<%1%>&, %1%)";
+    constexpr auto function = "boost::math::quantile(const triangular_distribution<%1%>&, %1%)";
     RealType l = c.dist.lower();
     RealType m = c.dist.mode();
     RealType u = c.dist.upper();
@@ -408,9 +408,9 @@ namespace boost{ namespace math
   } // RealType quantile(const complemented2_type<triangular_distribution<RealType, Policy>, RealType>& c)
 
   template <class RealType, class Policy>
-  inline RealType mean(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType mean(const triangular_distribution<RealType, Policy>& dist)
   {
-    static const char* function = "boost::math::mean(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::mean(const triangular_distribution<%1%>&)";
     RealType lower = dist.lower();
     RealType mode = dist.mode();
     RealType upper = dist.upper();
@@ -424,9 +424,9 @@ namespace boost{ namespace math
 
 
   template <class RealType, class Policy>
-  inline RealType variance(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType variance(const triangular_distribution<RealType, Policy>& dist)
   {
-    static const char* function = "boost::math::mean(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::mean(const triangular_distribution<%1%>&)";
     RealType lower = dist.lower();
     RealType mode = dist.mode();
     RealType upper = dist.upper();
@@ -439,9 +439,9 @@ namespace boost{ namespace math
   } // RealType variance(const triangular_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType mode(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType mode(const triangular_distribution<RealType, Policy>& dist)
   {
-    static const char* function = "boost::math::mode(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::mode(const triangular_distribution<%1%>&)";
     RealType mode = dist.mode();
     RealType result = 0; // of checks.
     if(false == detail::check_triangular_mode(function, mode, &result, Policy()))
@@ -452,10 +452,10 @@ namespace boost{ namespace math
   } // RealType mode
 
   template <class RealType, class Policy>
-  inline RealType median(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType median(const triangular_distribution<RealType, Policy>& dist)
   {
     BOOST_MATH_STD_USING // ADL of std functions.
-    static const char* function = "boost::math::median(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::median(const triangular_distribution<%1%>&)";
     RealType mode = dist.mode();
     RealType result = 0; // of checks.
     if(false == detail::check_triangular_mode(function, mode, &result, Policy()))
@@ -475,11 +475,11 @@ namespace boost{ namespace math
   } // RealType mode
 
   template <class RealType, class Policy>
-  inline RealType skewness(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType skewness(const triangular_distribution<RealType, Policy>& dist)
   {
     BOOST_MATH_STD_USING  // for ADL of std functions
     using namespace boost::math::constants; // for root_two
-    static const char* function = "boost::math::skewness(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::skewness(const triangular_distribution<%1%>&)";
 
     RealType lower = dist.lower();
     RealType mode = dist.mode();
@@ -496,9 +496,9 @@ namespace boost{ namespace math
   } // RealType skewness(const triangular_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType kurtosis(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const triangular_distribution<RealType, Policy>& dist)
   { // These checks may be belt and braces as should have been checked on construction?
-    static const char* function = "boost::math::kurtosis(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::kurtosis(const triangular_distribution<%1%>&)";
     RealType lower = dist.lower();
     RealType upper = dist.upper();
     RealType mode = dist.mode();
@@ -511,9 +511,9 @@ namespace boost{ namespace math
   } // RealType kurtosis_excess(const triangular_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType kurtosis_excess(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const triangular_distribution<RealType, Policy>& dist)
   { // These checks may be belt and braces as should have been checked on construction?
-    static const char* function = "boost::math::kurtosis_excess(const triangular_distribution<%1%>&)";
+    constexpr auto function = "boost::math::kurtosis_excess(const triangular_distribution<%1%>&)";
     RealType lower = dist.lower();
     RealType upper = dist.upper();
     RealType mode = dist.mode();
@@ -527,9 +527,9 @@ namespace boost{ namespace math
   }
 
   template <class RealType, class Policy>
-  inline RealType entropy(const triangular_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType entropy(const triangular_distribution<RealType, Policy>& dist)
   {
-    using std::log;
+    BOOST_MATH_STD_USING
     return constants::half<RealType>() + log((dist.upper() - dist.lower())/2);
   }
 
diff --git a/include/boost/math/distributions/uniform.hpp b/include/boost/math/distributions/uniform.hpp
index f57f8cc9f1..328fc61330 100644
--- a/include/boost/math/distributions/uniform.hpp
+++ b/include/boost/math/distributions/uniform.hpp
@@ -1,5 +1,6 @@
 //  Copyright John Maddock 2006.
 //  Copyright Paul A. Bristow 2006.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -15,18 +16,18 @@
 // http://documents.wolfram.com/calculationcenter/v2/Functions/ListsMatrices/Statistics/UniformDistribution.html
 // http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/distributions/fwd.hpp>
 #include <boost/math/distributions/detail/common_error_handling.hpp>
 #include <boost/math/distributions/complement.hpp>
 
-#include <utility>
-
 namespace boost{ namespace math
 {
   namespace detail
   {
     template <class RealType, class Policy>
-    inline bool check_uniform_lower(
+    BOOST_MATH_GPU_ENABLED inline bool check_uniform_lower(
       const char* function,
       RealType lower,
       RealType* result, const Policy& pol)
@@ -45,7 +46,7 @@ namespace boost{ namespace math
     } // bool check_uniform_lower(
 
     template <class RealType, class Policy>
-    inline bool check_uniform_upper(
+    BOOST_MATH_GPU_ENABLED inline bool check_uniform_upper(
       const char* function,
       RealType upper,
       RealType* result, const Policy& pol)
@@ -64,7 +65,7 @@ namespace boost{ namespace math
     } // bool check_uniform_upper(
 
     template <class RealType, class Policy>
-    inline bool check_uniform_x(
+    BOOST_MATH_GPU_ENABLED inline bool check_uniform_x(
       const char* function,
       RealType const& x,
       RealType* result, const Policy& pol)
@@ -83,7 +84,7 @@ namespace boost{ namespace math
     } // bool check_uniform_x
 
     template <class RealType, class Policy>
-    inline bool check_uniform(
+    BOOST_MATH_GPU_ENABLED inline bool check_uniform(
       const char* function,
       RealType lower,
       RealType upper,
@@ -116,19 +117,19 @@ namespace boost{ namespace math
     typedef RealType value_type;
     typedef Policy policy_type;
 
-    uniform_distribution(RealType l_lower = 0, RealType l_upper = 1) // Constructor.
+    BOOST_MATH_GPU_ENABLED uniform_distribution(RealType l_lower = 0, RealType l_upper = 1) // Constructor.
       : m_lower(l_lower), m_upper(l_upper) // Default is standard uniform distribution.
     {
       RealType result;
       detail::check_uniform("boost::math::uniform_distribution<%1%>::uniform_distribution", l_lower, l_upper, &result, Policy());
     }
     // Accessor functions.
-    RealType lower()const
+    BOOST_MATH_GPU_ENABLED RealType lower()const
     {
       return m_lower;
     }
 
-    RealType upper()const
+    BOOST_MATH_GPU_ENABLED RealType upper()const
     {
       return m_upper;
     }
@@ -148,23 +149,23 @@ namespace boost{ namespace math
   #endif
 
   template <class RealType, class Policy>
-  inline const std::pair<RealType, RealType> range(const uniform_distribution<RealType, Policy>& /* dist */)
+  BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> range(const uniform_distribution<RealType, Policy>& /* dist */)
   { // Range of permissible values for random variable x.
      using boost::math::tools::max_value;
-     return std::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + 'infinity'.
+     return boost::math::pair<RealType, RealType>(-max_value<RealType>(), max_value<RealType>()); // - to + 'infinity'.
      // Note RealType infinity is NOT permitted, only max_value.
   }
 
   template <class RealType, class Policy>
-  inline const std::pair<RealType, RealType> support(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline const boost::math::pair<RealType, RealType> support(const uniform_distribution<RealType, Policy>& dist)
   { // Range of supported values for random variable x.
      // This is range where cdf rises from 0 to 1, and outside it, the pdf is zero.
      using boost::math::tools::max_value;
-     return std::pair<RealType, RealType>(dist.lower(),  dist.upper());
+     return boost::math::pair<RealType, RealType>(dist.lower(),  dist.upper());
   }
 
   template <class RealType, class Policy>
-  inline RealType pdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
+  BOOST_MATH_GPU_ENABLED inline RealType pdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -189,7 +190,7 @@ namespace boost{ namespace math
   } // RealType pdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
 
   template <class RealType, class Policy>
-  inline RealType cdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
+  BOOST_MATH_GPU_ENABLED inline RealType cdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -214,7 +215,7 @@ namespace boost{ namespace math
   } // RealType cdf(const uniform_distribution<RealType, Policy>& dist, const RealType& x)
 
   template <class RealType, class Policy>
-  inline RealType quantile(const uniform_distribution<RealType, Policy>& dist, const RealType& p)
+  BOOST_MATH_GPU_ENABLED inline RealType quantile(const uniform_distribution<RealType, Policy>& dist, const RealType& p)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -239,7 +240,7 @@ namespace boost{ namespace math
   } // RealType quantile(const uniform_distribution<RealType, Policy>& dist, const RealType& p)
 
   template <class RealType, class Policy>
-  inline RealType cdf(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
+  BOOST_MATH_GPU_ENABLED inline RealType cdf(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
   {
     RealType lower = c.dist.lower();
     RealType upper = c.dist.upper();
@@ -265,7 +266,7 @@ namespace boost{ namespace math
   } // RealType cdf(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
 
   template <class RealType, class Policy>
-  inline RealType quantile(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
+  BOOST_MATH_GPU_ENABLED inline RealType quantile(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
   {
     RealType lower = c.dist.lower();
     RealType upper = c.dist.upper();
@@ -291,7 +292,7 @@ namespace boost{ namespace math
   } // RealType quantile(const complemented2_type<uniform_distribution<RealType, Policy>, RealType>& c)
 
   template <class RealType, class Policy>
-  inline RealType mean(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType mean(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -304,7 +305,7 @@ namespace boost{ namespace math
   } // RealType mean(const uniform_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType variance(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType variance(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -318,7 +319,7 @@ namespace boost{ namespace math
   } // RealType variance(const uniform_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType mode(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType mode(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -332,7 +333,7 @@ namespace boost{ namespace math
   }
 
   template <class RealType, class Policy>
-  inline RealType median(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType median(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -344,7 +345,7 @@ namespace boost{ namespace math
     return (lower + upper) / 2; //
   }
   template <class RealType, class Policy>
-  inline RealType skewness(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType skewness(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -357,7 +358,7 @@ namespace boost{ namespace math
   } // RealType skewness(const uniform_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType kurtosis_excess(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType kurtosis_excess(const uniform_distribution<RealType, Policy>& dist)
   {
     RealType lower = dist.lower();
     RealType upper = dist.upper();
@@ -370,15 +371,15 @@ namespace boost{ namespace math
   } // RealType kurtosis_excess(const uniform_distribution<RealType, Policy>& dist)
 
   template <class RealType, class Policy>
-  inline RealType kurtosis(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType kurtosis(const uniform_distribution<RealType, Policy>& dist)
   {
     return kurtosis_excess(dist) + 3;
   }
 
   template <class RealType, class Policy>
-  inline RealType entropy(const uniform_distribution<RealType, Policy>& dist)
+  BOOST_MATH_GPU_ENABLED inline RealType entropy(const uniform_distribution<RealType, Policy>& dist)
   {
-    using std::log;
+    BOOST_MATH_STD_USING
     return log(dist.upper() - dist.lower());
   }
 
diff --git a/include/boost/math/policies/error_handling.hpp b/include/boost/math/policies/error_handling.hpp
index 559e70a2f4..0a22dffa7f 100644
--- a/include/boost/math/policies/error_handling.hpp
+++ b/include/boost/math/policies/error_handling.hpp
@@ -13,6 +13,8 @@
 #include <boost/math/tools/type_traits.hpp>
 #include <boost/math/tools/cstdint.hpp>
 #include <boost/math/tools/tuple.hpp>
+#include <boost/math/policies/policy.hpp>
+#include <boost/math/tools/precision.hpp>
 
 #ifndef BOOST_MATH_HAS_NVRTC
 
@@ -26,8 +28,6 @@
 #include <complex>
 #include <cmath>
 #include <cstdint>
-#include <boost/math/policies/policy.hpp>
-#include <boost/math/tools/precision.hpp>
 #ifndef BOOST_MATH_NO_EXCEPTIONS
 #include <stdexcept>
 #include <boost/math/tools/throw_exception.hpp>
diff --git a/include/boost/math/special_functions/detail/gamma_inva.hpp b/include/boost/math/special_functions/detail/gamma_inva.hpp
index 61c64a6486..8c3be8ef1a 100644
--- a/include/boost/math/special_functions/detail/gamma_inva.hpp
+++ b/include/boost/math/special_functions/detail/gamma_inva.hpp
@@ -21,7 +21,14 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/toms748_solve.hpp>
 
-namespace boost{ namespace math{ namespace detail{
+namespace boost{ namespace math{ 
+
+#ifdef BOOST_MATH_HAS_NVRTC
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED auto erfc_inv(T x, const Policy&);
+#endif
+   
+namespace detail{
 
 template <class T, class Policy>
 struct gamma_inva_t
diff --git a/include/boost/math/special_functions/detail/t_distribution_inv.hpp b/include/boost/math/special_functions/detail/t_distribution_inv.hpp
index 22e1d11f02..79a29a0274 100644
--- a/include/boost/math/special_functions/detail/t_distribution_inv.hpp
+++ b/include/boost/math/special_functions/detail/t_distribution_inv.hpp
@@ -429,6 +429,19 @@ BOOST_MATH_GPU_ENABLED inline T find_ibeta_inv_from_t_dist(T a, T p, T /*q*/, T*
    return df / (df + t * t);
 }
 
+// NVRTC requires this forward decl because there is a header cycle between here and ibeta_inverse.hpp
+#ifdef BOOST_MATH_HAS_NVRTC
+
+} // Namespace detail
+
+template <class T1, class T2, class T3, class T4, class Policy>
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type
+   ibeta_inv(T1 a, T2 b, T3 p, T4* py, const Policy& pol);
+
+namespace detail {
+
+#endif
+
 template <class T, class Policy>
 BOOST_MATH_GPU_ENABLED inline T fast_students_t_quantile_imp(T df, T p, const Policy& pol, const boost::math::false_type*)
 {
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index e3a2722c3d..22c3889499 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -25,6 +25,7 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/promotion.hpp> // for argument promotion.
 
 #ifdef BOOST_MATH_HAS_NVRTC
 
@@ -44,7 +45,6 @@ beta(RT1 a, RT2 b, A arg);
 #include <complex>
 #include <type_traits>
 #include <boost/math/special_functions/detail/round_fwd.hpp>
-#include <boost/math/tools/promotion.hpp> // for argument promotion.
 #include <boost/math/tools/type_traits.hpp>
 #include <boost/math/policies/policy.hpp>
 
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index fac8f84db0..6d7af4d2be 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -804,6 +804,7 @@ BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_max(const T& a, const T& b) { return
 #define BOOST_MATH_IS_FLOAT(T) (boost::math::is_floating_point<T>::value)
 #define BOOST_MATH_CONSTEXPR_TABLE_FUNCTION constexpr
 #define BOOST_MATH_NO_EXCEPTIONS
+#define BOOST_MATH_PREVENT_MACRO_SUBSTITUTION 
 
 // This should be defined to nothing but since it is not specifically a math macro
 // we need to undef before proceeding
diff --git a/include/boost/math/tools/minima.hpp b/include/boost/math/tools/minima.hpp
index 6070fc5307..a6be94cb2b 100644
--- a/include/boost/math/tools/minima.hpp
+++ b/include/boost/math/tools/minima.hpp
@@ -11,20 +11,26 @@
 #pragma once
 #endif
 
-#include <cstdint>
-#include <cmath>
-#include <utility>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/tuple.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
 #include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/utility.hpp>
 #include <boost/math/policies/policy.hpp>
 
 namespace boost{ namespace math{ namespace tools{
 
 template <class F, class T>
-std::pair<T, T> brent_find_minima(F f, T min, T max, int bits, std::uintmax_t& max_iter)
-   noexcept(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED boost::math::pair<T, T> brent_find_minima(F f, T min, T max, int bits, boost::math::uintmax_t& max_iter)
+   noexcept(BOOST_MATH_IS_FLOAT(T) 
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
+   && noexcept(std::declval<F>()(std::declval<T>()))
+   #endif
+   )
 {
    BOOST_MATH_STD_USING
-   bits = (std::min)(policies::digits<T, policies::policy<> >() / 2, bits);
+   bits = (boost::math::min)(policies::digits<T, policies::policy<> >() / 2, bits);
    T tolerance = static_cast<T>(ldexp(1.0, 1-bits));
    T x;  // minima so far
    T w;  // second best point
@@ -42,7 +48,7 @@ std::pair<T, T> brent_find_minima(F f, T min, T max, int bits, std::uintmax_t& m
    fw = fv = fx = f(x);
    delta2 = delta = 0;
 
-   uintmax_t count = max_iter;
+   boost::math::uintmax_t count = max_iter;
 
    do{
       // get midpoint
@@ -134,14 +140,18 @@ std::pair<T, T> brent_find_minima(F f, T min, T max, int bits, std::uintmax_t& m
 
    max_iter -= count;
 
-   return std::make_pair(x, fx);
+   return boost::math::make_pair(x, fx);
 }
 
 template <class F, class T>
-inline std::pair<T, T> brent_find_minima(F f, T min, T max, int digits)
-   noexcept(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval<F>()(std::declval<T>())))
+BOOST_MATH_GPU_ENABLED inline boost::math::pair<T, T> brent_find_minima(F f, T min, T max, int digits)
+   noexcept(BOOST_MATH_IS_FLOAT(T)
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
+   && noexcept(std::declval<F>()(std::declval<T>()))
+   #endif
+   )
 {
-   std::uintmax_t m = (std::numeric_limits<std::uintmax_t>::max)();
+   boost::math::uintmax_t m = (boost::math::numeric_limits<boost::math::uintmax_t>::max)();
    return brent_find_minima(f, min, max, digits, m);
 }
 
diff --git a/include/boost/math/tools/utility.hpp b/include/boost/math/tools/utility.hpp
new file mode 100644
index 0000000000..3e22865780
--- /dev/null
+++ b/include/boost/math/tools/utility.hpp
@@ -0,0 +1,69 @@
+//  Copyright (c) 2024 Matt Borland
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#ifndef BOOST_MATH_TOOLS_UTILITY
+#define BOOST_MATH_TOOLS_UTILITY
+
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_GPU_SUPPORT
+
+#include <utility>
+
+namespace boost {
+namespace math {
+
+template <typename T>
+constexpr T min BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (const T& a, const T& b)
+{
+    return (std::min)(a, b);
+}
+
+template <typename T>
+constexpr T max BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (const T& a, const T& b)
+{
+    return (std::max)(a, b);
+}
+
+template <typename T>
+void swap BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (T& a, T& b)
+{
+    return (std::swap)(a, b);
+}
+
+} // namespace math
+} // namespace boost
+
+#else
+
+namespace boost {
+namespace math {
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED constexpr T min BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (const T& a, const T& b)
+{ 
+    return a < b ? a : b; 
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED constexpr T max BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (const T& a, const T& b)
+{ 
+    return a > b ? a : b;
+}
+
+template <typename T>
+BOOST_MATH_GPU_ENABLED constexpr void swap BOOST_MATH_PREVENT_MACRO_SUBSTITUTION (T& a, T& b)
+{ 
+    T t(a); 
+    a = b; 
+    b = t;
+}
+
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_HAS_GPU_SUPPORT
+
+#endif // BOOST_MATH_TOOLS_UTILITY
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index bae42a8d99..2eb7810081 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -104,6 +104,13 @@ run test_inverse_gamma_pdf_float.cu ;
 run test_inverse_gamma_quan_double.cu ;
 run test_inverse_gamma_quan_float.cu ;
 
+run test_inverse_gaussian_cdf_double.cu ;
+run test_inverse_gaussian_cdf_float.cu ;
+run test_inverse_gaussian_pdf_double.cu ;
+run test_inverse_gaussian_pdf_float.cu ;
+run test_inverse_gaussian_quan_double.cu ;
+run test_inverse_gaussian_quan_float.cu ;
+
 run test_landau_cdf_double.cu ;
 run test_landau_cdf_float.cu ;
 run test_landau_pdf_double.cu ;
@@ -125,6 +132,13 @@ run test_logistic_pdf_float.cu ;
 run test_logistic_quan_double.cu ;
 run test_logistic_quan_float.cu ;
 
+run test_lognormal_cdf_double.cu ;
+run test_lognormal_cdf_float.cu ;
+run test_lognormal_pdf_double.cu ;
+run test_lognormal_pdf_float.cu ;
+run test_lognormal_quan_double.cu ;
+run test_lognormal_quan_float.cu ;
+
 run test_mapairy_cdf_double.cu ;
 run test_mapairy_cdf_float.cu ;
 run test_mapairy_pdf_double.cu ;
@@ -132,6 +146,62 @@ run test_mapairy_pdf_float.cu ;
 run test_mapairy_quan_double.cu ;
 run test_mapairy_quan_float.cu ;
 
+run test_nc_beta_cdf_double.cu ;
+run test_nc_beta_cdf_float.cu ;
+run test_nc_beta_pdf_double.cu ;
+run test_nc_beta_pdf_float.cu ;
+run test_nc_beta_quan_double.cu ;
+run test_nc_beta_quan_float.cu ;
+
+run test_nc_f_cdf_double.cu ;
+run test_nc_f_cdf_float.cu ;
+run test_nc_f_pdf_double.cu ;
+run test_nc_f_pdf_float.cu ;
+run test_nc_f_quan_double.cu ;
+run test_nc_f_quan_float.cu ;
+
+run test_nc_chi_squared_cdf_double.cu ;
+run test_nc_chi_squared_cdf_float.cu ;
+run test_nc_chi_squared_pdf_double.cu ;
+run test_nc_chi_squared_pdf_float.cu ;
+run test_nc_chi_squared_quan_double.cu ;
+run test_nc_chi_squared_quan_float.cu ;
+
+run test_negative_binomial_cdf_double.cu ;
+run test_negative_binomial_cdf_float.cu ;
+run test_negative_binomial_pdf_double.cu ;
+run test_negative_binomial_pdf_float.cu ;
+run test_negative_binomial_quan_double.cu ;
+run test_negative_binomial_quan_float.cu ;
+
+run test_normal_cdf_double.cu ;
+run test_normal_cdf_float.cu ;
+run test_normal_pdf_double.cu ;
+run test_normal_pdf_float.cu ;
+run test_normal_quan_double.cu ;
+run test_normal_quan_float.cu ;
+
+run test_pareto_cdf_double.cu ;
+run test_pareto_cdf_float.cu ;
+run test_pareto_pdf_double.cu ;
+run test_pareto_pdf_float.cu ;
+run test_pareto_quan_double.cu ;
+run test_pareto_quan_float.cu ;
+
+run test_poisson_cdf_double.cu ;
+run test_poisson_cdf_float.cu ;
+run test_poisson_pdf_double.cu ;
+run test_poisson_pdf_float.cu ;
+run test_poisson_quan_double.cu ;
+run test_poisson_quan_float.cu ;
+
+run test_rayleigh_cdf_double.cu ;
+run test_rayleigh_cdf_float.cu ;
+run test_rayleigh_pdf_double.cu ;
+run test_rayleigh_pdf_float.cu ;
+run test_rayleigh_quan_double.cu ;
+run test_rayleigh_quan_float.cu ;
+
 run test_saspoint5_cdf_double.cu ;
 run test_saspoint5_cdf_float.cu ;
 run test_saspoint5_pdf_double.cu ;
@@ -139,6 +209,27 @@ run test_saspoint5_pdf_float.cu ;
 run test_saspoint5_quan_double.cu ;
 run test_saspoint5_quan_float.cu ;
 
+run test_students_t_cdf_double.cu ;
+run test_students_t_cdf_float.cu ;
+run test_students_t_pdf_double.cu ;
+run test_students_t_pdf_float.cu ;
+run test_students_t_quan_double.cu ;
+run test_students_t_quan_float.cu ;
+
+run test_triangular_cdf_double.cu ;
+run test_triangular_cdf_float.cu ;
+run test_triangular_pdf_double.cu ;
+run test_triangular_pdf_float.cu ;
+run test_triangular_quan_double.cu ;
+run test_triangular_quan_float.cu ;
+
+run test_uniform_cdf_double.cu ;
+run test_uniform_cdf_float.cu ;
+run test_uniform_pdf_double.cu ;
+run test_uniform_pdf_float.cu ;
+run test_uniform_quan_double.cu ;
+run test_uniform_quan_float.cu ;
+
 run test_weibull_cdf_double.cu ;
 run test_weibull_cdf_float.cu ;
 run test_weibull_pdf_double.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 1b001eb2f1..0786564d7c 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -101,6 +101,13 @@ run test_inverse_gamma_pdf_nvrtc_float.cpp ;
 run test_inverse_gamma_quan_nvrtc_double.cpp ;
 run test_inverse_gamma_quan_nvrtc_float.cpp ;
 
+run test_inverse_gaussian_cdf_nvrtc_double.cpp ;
+run test_inverse_gaussian_cdf_nvrtc_float.cpp ;
+run test_inverse_gaussian_pdf_nvrtc_double.cpp ;
+run test_inverse_gaussian_pdf_nvrtc_float.cpp ;
+run test_inverse_gaussian_quan_nvrtc_double.cpp ;
+run test_inverse_gaussian_quan_nvrtc_float.cpp ;
+
 run test_landau_cdf_nvrtc_double.cpp ;
 run test_landau_cdf_nvrtc_float.cpp ;
 run test_landau_pdf_nvrtc_double.cpp ;
@@ -122,6 +129,13 @@ run test_logistic_pdf_nvrtc_float.cpp ;
 run test_logistic_quan_nvrtc_double.cpp ;
 run test_logistic_quan_nvrtc_float.cpp ;
 
+run test_lognormal_cdf_nvrtc_double.cpp ;
+run test_lognormal_cdf_nvrtc_float.cpp ;
+run test_lognormal_pdf_nvrtc_double.cpp ;
+run test_lognormal_pdf_nvrtc_float.cpp ;
+run test_lognormal_quan_nvrtc_double.cpp ;
+run test_lognormal_quan_nvrtc_float.cpp ;
+
 run test_mapairy_cdf_nvrtc_double.cpp ;
 run test_mapairy_cdf_nvrtc_float.cpp ;
 run test_mapairy_pdf_nvrtc_double.cpp ;
@@ -129,6 +143,62 @@ run test_mapairy_pdf_nvrtc_float.cpp ;
 run test_mapairy_quan_nvrtc_double.cpp ;
 run test_mapairy_quan_nvrtc_float.cpp ;
 
+run test_nc_beta_cdf_nvrtc_double.cpp ;
+run test_nc_beta_cdf_nvrtc_float.cpp ;
+run test_nc_beta_pdf_nvrtc_double.cpp ;
+run test_nc_beta_pdf_nvrtc_float.cpp ;
+run test_nc_beta_quan_nvrtc_double.cpp ;
+run test_nc_beta_quan_nvrtc_float.cpp ;
+
+run test_nc_chi_squared_cdf_nvrtc_double.cpp ;
+run test_nc_chi_squared_cdf_nvrtc_float.cpp ;
+run test_nc_chi_squared_pdf_nvrtc_double.cpp ;
+run test_nc_chi_squared_pdf_nvrtc_float.cpp ;
+run test_nc_chi_squared_quan_nvrtc_double.cpp ;
+run test_nc_chi_squared_quan_nvrtc_float.cpp ;
+
+run test_nc_f_cdf_nvrtc_double.cpp ; 
+run test_nc_f_cdf_nvrtc_float.cpp ;
+run test_nc_f_pdf_nvrtc_double.cpp ;
+run test_nc_f_pdf_nvrtc_float.cpp ;
+run test_nc_f_quan_nvrtc_double.cpp ;
+run test_nc_f_quan_nvrtc_float.cpp ;
+
+run test_negative_binomial_cdf_nvrtc_double.cpp ;
+run test_negative_binomial_cdf_nvrtc_float.cpp ;
+run test_negative_binomial_pdf_nvrtc_double.cpp ;
+run test_negative_binomial_pdf_nvrtc_float.cpp ;
+run test_negative_binomial_quan_nvrtc_double.cpp ;
+run test_negative_binomial_quan_nvrtc_float.cpp ;
+
+run test_normal_cdf_nvrtc_double.cpp ;
+run test_normal_cdf_nvrtc_float.cpp ;
+run test_normal_pdf_nvrtc_double.cpp ;
+run test_normal_pdf_nvrtc_float.cpp ;
+run test_normal_quan_nvrtc_double.cpp ;
+run test_normal_quan_nvrtc_float.cpp ;
+
+run test_pareto_cdf_nvrtc_double.cpp ;
+run test_pareto_cdf_nvrtc_float.cpp ;
+run test_pareto_pdf_nvrtc_double.cpp ;
+run test_pareto_pdf_nvrtc_float.cpp ;
+run test_pareto_quan_nvrtc_double.cpp ;
+run test_pareto_quan_nvrtc_float.cpp ;
+
+run test_poisson_cdf_nvrtc_double.cpp ;
+run test_poisson_cdf_nvrtc_float.cpp ;
+run test_poisson_pdf_nvrtc_double.cpp ;
+run test_poisson_pdf_nvrtc_float.cpp ;
+run test_poisson_quan_nvrtc_double.cpp ;
+run test_poisson_quan_nvrtc_float.cpp ;
+
+run test_rayleigh_cdf_nvrtc_double.cpp ;
+run test_rayleigh_cdf_nvrtc_float.cpp ;
+run test_rayleigh_pdf_nvrtc_double.cpp ;
+run test_rayleigh_pdf_nvrtc_float.cpp ;
+run test_rayleigh_quan_nvrtc_double.cpp ;
+run test_rayleigh_quan_nvrtc_float.cpp ;
+
 run test_saspoint5_cdf_nvrtc_double.cpp ;
 run test_saspoint5_cdf_nvrtc_float.cpp ;
 run test_saspoint5_pdf_nvrtc_double.cpp ;
@@ -136,6 +206,27 @@ run test_saspoint5_pdf_nvrtc_float.cpp ;
 run test_saspoint5_quan_nvrtc_double.cpp ;
 run test_saspoint5_quan_nvrtc_float.cpp ;
 
+run test_students_t_cdf_nvrtc_double.cpp ;
+run test_students_t_cdf_nvrtc_float.cpp ;
+run test_students_t_pdf_nvrtc_double.cpp ;
+run test_students_t_pdf_nvrtc_float.cpp ;
+run test_students_t_quan_nvrtc_double.cpp ;
+run test_students_t_quan_nvrtc_float.cpp ;
+
+run test_triangular_cdf_nvrtc_double.cpp ;
+run test_triangular_cdf_nvrtc_float.cpp ;
+run test_triangular_pdf_nvrtc_double.cpp ;
+run test_triangular_pdf_nvrtc_float.cpp ;
+run test_triangular_quan_nvrtc_double.cpp ;
+run test_triangular_quan_nvrtc_float.cpp ;
+
+run test_uniform_cdf_nvrtc_double.cpp ;
+run test_uniform_cdf_nvrtc_float.cpp ;
+run test_uniform_pdf_nvrtc_double.cpp ;
+run test_uniform_pdf_nvrtc_float.cpp ;
+run test_uniform_quan_nvrtc_double.cpp ;
+run test_uniform_quan_nvrtc_float.cpp ;
+
 run test_weibull_cdf_nvrtc_double.cpp ;
 run test_weibull_cdf_nvrtc_float.cpp ;
 run test_weibull_pdf_nvrtc_double.cpp ;
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index bcdfb7e5d2..1626031082 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -23,11 +23,24 @@ run test_geometric.cpp ;
 run test_holtsmark.cpp ;
 run test_inverse_chi_squared_distribution.cpp ;
 run test_inverse_gamma_distribution.cpp ;
+run test_inverse_gaussian.cpp ;
 run test_landau.cpp ;
 run test_laplace.cpp ;
 run test_logistic_dist.cpp ;
+run test_lognormal.cpp ;
 run test_mapairy.cpp ;
+run test_nc_beta.cpp ;
+run test_nc_chi_squared.cpp ;
+run test_nc_f.cpp ;
+run test_negative_binomial.cpp ;
+run test_normal.cpp ; 
+run test_pareto.cpp ;
+run test_poisson.cpp ;
+run test_rayleigh.cpp ;
 run test_saspoint5.cpp ;
+run test_students_t.cpp ;
+run test_triangular.cpp ;
+run test_uniform.cpp ;
 run test_weibull.cpp ;
 
 # Special Functions
diff --git a/test/test_inverse_gaussian.cpp b/test/test_inverse_gaussian.cpp
index 68012d48a2..3825da9397 100644
--- a/test/test_inverse_gaussian.cpp
+++ b/test/test_inverse_gaussian.cpp
@@ -16,8 +16,13 @@
 
 //#include <pch.hpp> // include directory libs/math/src/tr1/ is needed.
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
@@ -26,7 +31,6 @@
 using boost::math::inverse_gaussian_distribution;
 using boost::math::inverse_gaussian;
 
-#include <boost/math/tools/test.hpp>
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_inverse_gaussian_cdf_double.cu b/test/test_inverse_gaussian_cdf_double.cu
new file mode 100644
index 0000000000..3224ff527b
--- /dev/null
+++ b/test/test_inverse_gaussian_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_cdf_float.cu b/test/test_inverse_gaussian_cdf_float.cu
new file mode 100644
index 0000000000..e2abb72dd1
--- /dev/null
+++ b/test/test_inverse_gaussian_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_cdf_nvrtc_double.cpp b/test/test_inverse_gaussian_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1d677010fe
--- /dev/null
+++ b/test/test_inverse_gaussian_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gaussian_cdf_nvrtc_float.cpp b/test/test_inverse_gaussian_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..87e1537b89
--- /dev/null
+++ b/test/test_inverse_gaussian_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gaussian_pdf_double.cu b/test/test_inverse_gaussian_pdf_double.cu
new file mode 100644
index 0000000000..7f9128037b
--- /dev/null
+++ b/test/test_inverse_gaussian_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_pdf_float.cu b/test/test_inverse_gaussian_pdf_float.cu
new file mode 100644
index 0000000000..3795ff2dbb
--- /dev/null
+++ b/test/test_inverse_gaussian_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_pdf_nvrtc_double.cpp b/test/test_inverse_gaussian_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..e0f87de0ab
--- /dev/null
+++ b/test/test_inverse_gaussian_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gaussian_pdf_nvrtc_float.cpp b/test/test_inverse_gaussian_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..eb124deda9
--- /dev/null
+++ b/test/test_inverse_gaussian_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gaussian_quan_double.cu b/test/test_inverse_gaussian_quan_double.cu
new file mode 100644
index 0000000000..2727e53f49
--- /dev/null
+++ b/test/test_inverse_gaussian_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_quan_float.cu b/test/test_inverse_gaussian_quan_float.cu
new file mode 100644
index 0000000000..2727e53f49
--- /dev/null
+++ b/test/test_inverse_gaussian_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch inverse_gaussian distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::inverse_gaussian_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_inverse_gaussian_quan_nvrtc_double.cpp b/test/test_inverse_gaussian_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..a72aab4be4
--- /dev/null
+++ b/test/test_inverse_gaussian_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_inverse_gaussian_quan_nvrtc_float.cpp b/test/test_inverse_gaussian_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..550393f7e1
--- /dev/null
+++ b/test/test_inverse_gaussian_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/inverse_gaussian.hpp>
+extern "C" __global__ 
+void test_inverse_gaussian_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::inverse_gaussian_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_inverse_gaussian_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_inverse_gaussian_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_inverse_gaussian_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::inverse_gaussian_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal.cpp b/test/test_lognormal.cpp
index 759944b396..6fa4a6aa26 100644
--- a/test/test_lognormal.cpp
+++ b/test/test_lognormal.cpp
@@ -8,14 +8,19 @@
 
 // test_lognormal.cpp
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/lognormal.hpp>
     using boost::math::lognormal_distribution;
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_lognormal_cdf_double.cu b/test/test_lognormal_cdf_double.cu
new file mode 100644
index 0000000000..288240a43c
--- /dev/null
+++ b/test/test_lognormal_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_cdf_float.cu b/test/test_lognormal_cdf_float.cu
new file mode 100644
index 0000000000..d9411a1b4a
--- /dev/null
+++ b/test/test_lognormal_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_cdf_nvrtc_double.cpp b/test/test_lognormal_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..0ab15206c9
--- /dev/null
+++ b/test/test_lognormal_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal_cdf_nvrtc_float.cpp b/test/test_lognormal_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..308e8c85e3
--- /dev/null
+++ b/test/test_lognormal_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal_pdf_double.cu b/test/test_lognormal_pdf_double.cu
new file mode 100644
index 0000000000..67bb63a2cd
--- /dev/null
+++ b/test/test_lognormal_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_pdf_float.cu b/test/test_lognormal_pdf_float.cu
new file mode 100644
index 0000000000..ac8382dfd1
--- /dev/null
+++ b/test/test_lognormal_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_pdf_nvrtc_double.cpp b/test/test_lognormal_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1799559330
--- /dev/null
+++ b/test/test_lognormal_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal_pdf_nvrtc_float.cpp b/test/test_lognormal_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..f66c8bf4bb
--- /dev/null
+++ b/test/test_lognormal_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal_quan_double.cu b/test/test_lognormal_quan_double.cu
new file mode 100644
index 0000000000..056177e006
--- /dev/null
+++ b/test/test_lognormal_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_quan_float.cu b/test/test_lognormal_quan_float.cu
new file mode 100644
index 0000000000..65a9188d77
--- /dev/null
+++ b/test/test_lognormal_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch lognormal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::lognormal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_lognormal_quan_nvrtc_double.cpp b/test/test_lognormal_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..ddde58fc0b
--- /dev/null
+++ b/test/test_lognormal_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_lognormal_quan_nvrtc_float.cpp b/test/test_lognormal_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..e121f3b380
--- /dev/null
+++ b/test/test_lognormal_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/lognormal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/lognormal.hpp>
+extern "C" __global__ 
+void test_lognormal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::lognormal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_lognormal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_lognormal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_lognormal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::lognormal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta.cpp b/test/test_nc_beta.cpp
index 3e7c08d0f3..105db62a3e 100644
--- a/test/test_nc_beta.cpp
+++ b/test/test_nc_beta.cpp
@@ -11,6 +11,9 @@
 // This must appear *before* any #includes, and precludes pch usage:
 //
 #define BOOST_MATH_ASSERT_UNDEFINED_POLICY false
+#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#endif
 
 #ifdef _MSC_VER
 #pragma warning (disable:4127 4512)
@@ -27,7 +30,12 @@
 #  define TEST_REAL_CONCEPT
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #include <boost/math/distributions/non_central_beta.hpp> // for chi_squared_distribution
 #include <boost/math/distributions/poisson.hpp> // for poisson_distribution
 #define BOOST_TEST_MAIN
@@ -41,6 +49,7 @@
 #include "test_ncbeta_hooks.hpp"
 #include "table_type.hpp"
 #include "test_nc_beta.hpp"
+#include "../include_private/boost/math/tools/test.hpp"
 
 #include <iostream>
 using std::cout;
diff --git a/test/test_nc_beta.hpp b/test/test_nc_beta.hpp
index 3ba983adca..39b4ede9eb 100644
--- a/test/test_nc_beta.hpp
+++ b/test/test_nc_beta.hpp
@@ -6,7 +6,9 @@
 #ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #endif
-#include <boost/math/concepts/real_concept.hpp>
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
+#include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
diff --git a/test/test_nc_beta_cdf_double.cu b/test/test_nc_beta_cdf_double.cu
new file mode 100644
index 0000000000..75073ac8d7
--- /dev/null
+++ b/test/test_nc_beta_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_cdf_float.cu b/test/test_nc_beta_cdf_float.cu
new file mode 100644
index 0000000000..1088678c29
--- /dev/null
+++ b/test/test_nc_beta_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_cdf_nvrtc_double.cpp b/test/test_nc_beta_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4b9523fb22
--- /dev/null
+++ b/test/test_nc_beta_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta_cdf_nvrtc_float.cpp b/test/test_nc_beta_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..ec63159b41
--- /dev/null
+++ b/test/test_nc_beta_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta_pdf_double.cu b/test/test_nc_beta_pdf_double.cu
new file mode 100644
index 0000000000..485cf1d77c
--- /dev/null
+++ b/test/test_nc_beta_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_pdf_float.cu b/test/test_nc_beta_pdf_float.cu
new file mode 100644
index 0000000000..bd989a330a
--- /dev/null
+++ b/test/test_nc_beta_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_pdf_nvrtc_double.cpp b/test/test_nc_beta_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..64387cebc6
--- /dev/null
+++ b/test/test_nc_beta_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta_pdf_nvrtc_float.cpp b/test/test_nc_beta_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..de85a7ebc6
--- /dev/null
+++ b/test/test_nc_beta_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta_quan_double.cu b/test/test_nc_beta_quan_double.cu
new file mode 100644
index 0000000000..eb1a872774
--- /dev/null
+++ b/test/test_nc_beta_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_quan_float.cu b/test/test_nc_beta_quan_float.cu
new file mode 100644
index 0000000000..f205e810c7
--- /dev/null
+++ b/test/test_nc_beta_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_beta distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_beta_quan_nvrtc_double.cpp b/test/test_nc_beta_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..61651d85e3
--- /dev/null
+++ b/test/test_nc_beta_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_beta_quan_nvrtc_float.cpp b/test/test_nc_beta_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..3c9a0ce231
--- /dev/null
+++ b/test/test_nc_beta_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_beta.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_beta.hpp>
+extern "C" __global__ 
+void test_non_central_beta_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_beta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_beta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_beta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_beta_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared.cpp b/test/test_nc_chi_squared.cpp
index 14bec61259..0d6f261fa3 100644
--- a/test/test_nc_chi_squared.cpp
+++ b/test/test_nc_chi_squared.cpp
@@ -7,7 +7,9 @@
 // (See accompanying file LICENSE_1_0.txt
 // or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp>
+#endif
 
 #ifdef _MSC_VER
 #pragma warning (disable:4127 4512)
@@ -24,8 +26,18 @@
 #  define TEST_REAL_CONCEPT
 #endif
 
-#include <boost/math/tools/test.hpp>
+#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#endif
+
+#include <boost/math/tools/config.hpp>
+
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #include <boost/math/distributions/non_central_chi_squared.hpp> // for chi_squared_distribution
 #include <boost/math/special_functions/cbrt.hpp> // for chi_squared_distribution
 #define BOOST_TEST_MAIN
diff --git a/test/test_nc_chi_squared.hpp b/test/test_nc_chi_squared.hpp
index b2fa6d75be..3ab276a5a0 100644
--- a/test/test_nc_chi_squared.hpp
+++ b/test/test_nc_chi_squared.hpp
@@ -80,7 +80,7 @@ void test_spot(
    boost::math::non_central_chi_squared_distribution<RealType> dist(df, ncp);
    BOOST_CHECK_CLOSE(
       cdf(dist, cs), P, tol);
-#ifndef BOOST_NO_EXCEPTIONS
+#if !defined(BOOST_NO_EXCEPTIONS) && !defined(BOOST_MATH_NO_EXCEPTIONS)
    try{
       BOOST_CHECK_CLOSE(
          pdf(dist, cs), naive_pdf(dist.degrees_of_freedom(), ncp, cs), tol * 150);
@@ -402,7 +402,7 @@ void quantile_sanity_check(T& data, const char* type_name, const char* test)
          // Sanity check mode, the accuracy of
          // the mode is at *best* the square root of the accuracy of the PDF:
          //
-#ifndef BOOST_NO_EXCEPTIONS
+#if !defined(BOOST_NO_EXCEPTIONS) && !defined(BOOST_MATH_NO_EXCEPTIONS)
          try{
             value_type m = mode(boost::math::non_central_chi_squared_distribution<value_type>(data[i][0], data[i][1]));
             value_type p = pdf(boost::math::non_central_chi_squared_distribution<value_type>(data[i][0], data[i][1]), m);
@@ -417,7 +417,7 @@ void quantile_sanity_check(T& data, const char* type_name, const char* test)
          // values to get back to the correct degrees of freedom or
          // non-centrality parameter:
          //
-#ifndef BOOST_NO_EXCEPTIONS
+#if !defined(BOOST_NO_EXCEPTIONS) && !defined(BOOST_MATH_NO_EXCEPTIONS)
          try{
 #endif
             if((data[i][3] < 0.99) && (data[i][3] != 0))
@@ -438,7 +438,7 @@ void quantile_sanity_check(T& data, const char* type_name, const char* test)
                   boost::math::non_central_chi_squared_distribution<value_type>::find_non_centrality(boost::math::complement(data[i][0], data[i][2], data[i][4])),
                   data[i][1], precision, i);
             }
-#ifndef BOOST_NO_EXCEPTIONS
+#if !defined(BOOST_NO_EXCEPTIONS) && !defined(BOOST_MATH_NO_EXCEPTIONS)
          }
          catch(const std::exception& e)
          {
diff --git a/test/test_nc_chi_squared_cdf_double.cu b/test/test_nc_chi_squared_cdf_double.cu
new file mode 100644
index 0000000000..64a442f6f8
--- /dev/null
+++ b/test/test_nc_chi_squared_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_cdf_float.cu b/test/test_nc_chi_squared_cdf_float.cu
new file mode 100644
index 0000000000..8ac518adc8
--- /dev/null
+++ b/test/test_nc_chi_squared_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_cdf_nvrtc_double.cpp b/test/test_nc_chi_squared_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..05569b02eb
--- /dev/null
+++ b/test/test_nc_chi_squared_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared_cdf_nvrtc_float.cpp b/test/test_nc_chi_squared_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..57964384bd
--- /dev/null
+++ b/test/test_nc_chi_squared_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared_pdf_double.cu b/test/test_nc_chi_squared_pdf_double.cu
new file mode 100644
index 0000000000..19a96944bd
--- /dev/null
+++ b/test/test_nc_chi_squared_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_pdf_float.cu b/test/test_nc_chi_squared_pdf_float.cu
new file mode 100644
index 0000000000..9433005b26
--- /dev/null
+++ b/test/test_nc_chi_squared_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_pdf_nvrtc_double.cpp b/test/test_nc_chi_squared_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4ddede8281
--- /dev/null
+++ b/test/test_nc_chi_squared_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared_pdf_nvrtc_float.cpp b/test/test_nc_chi_squared_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..ec749b2a4b
--- /dev/null
+++ b/test/test_nc_chi_squared_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared_quan_double.cu b/test/test_nc_chi_squared_quan_double.cu
new file mode 100644
index 0000000000..a54a2e015c
--- /dev/null
+++ b/test/test_nc_chi_squared_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_quan_float.cu b/test/test_nc_chi_squared_quan_float.cu
new file mode 100644
index 0000000000..7f83eb5c0b
--- /dev/null
+++ b/test/test_nc_chi_squared_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_chi_squared distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_chi_squared_quan_nvrtc_double.cpp b/test/test_nc_chi_squared_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..f2ca532622
--- /dev/null
+++ b/test/test_nc_chi_squared_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_chi_squared_quan_nvrtc_float.cpp b/test/test_nc_chi_squared_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..931a1aa60e
--- /dev/null
+++ b/test/test_nc_chi_squared_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_chi_squared.hpp>
+extern "C" __global__ 
+void test_non_central_chi_squared_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_chi_squared_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_chi_squared_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_chi_squared_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_chi_squared_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f.cpp b/test/test_nc_f.cpp
index 1cf411516d..7de8b254d5 100644
--- a/test/test_nc_f.cpp
+++ b/test/test_nc_f.cpp
@@ -7,7 +7,9 @@
 // (See accompanying file LICENSE_1_0.txt
 // or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp>
+#endif
 
 #ifdef _MSC_VER
 #pragma warning (disable:4127 4512)
@@ -20,8 +22,12 @@
 #  define TEST_REAL_CONCEPT
 #endif
 
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #include <boost/math/distributions/non_central_f.hpp> // for chi_squared_distribution
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // for test_main
diff --git a/test/test_nc_f_cdf_double.cu b/test/test_nc_f_cdf_double.cu
new file mode 100644
index 0000000000..a4e4c442ff
--- /dev/null
+++ b/test/test_nc_f_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_cdf_float.cu b/test/test_nc_f_cdf_float.cu
new file mode 100644
index 0000000000..79a7d84144
--- /dev/null
+++ b/test/test_nc_f_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_cdf_nvrtc_double.cpp b/test/test_nc_f_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1f35ba2ec4
--- /dev/null
+++ b/test/test_nc_f_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f_cdf_nvrtc_float.cpp b/test/test_nc_f_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..4aaa8b3910
--- /dev/null
+++ b/test/test_nc_f_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f_pdf_double.cu b/test/test_nc_f_pdf_double.cu
new file mode 100644
index 0000000000..3a156ffb71
--- /dev/null
+++ b/test/test_nc_f_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_pdf_float.cu b/test/test_nc_f_pdf_float.cu
new file mode 100644
index 0000000000..8a792b2f7e
--- /dev/null
+++ b/test/test_nc_f_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_pdf_nvrtc_double.cpp b/test/test_nc_f_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..bb5da728e9
--- /dev/null
+++ b/test/test_nc_f_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f_pdf_nvrtc_float.cpp b/test/test_nc_f_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..db46004729
--- /dev/null
+++ b/test/test_nc_f_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f_quan_double.cu b/test/test_nc_f_quan_double.cu
new file mode 100644
index 0000000000..687f789616
--- /dev/null
+++ b/test/test_nc_f_quan_double.cu
@@ -0,0 +1,117 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    bool failed = false;
+    for(int i = 0; i < numElements; ++i)
+    {
+        // Nearly all values are within 150 eps but their out outliers that hit ~100'000 eps
+        // Typically this occurs around 0 on device with doubles.
+        // Floats do not have this issue
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100000.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            failed = true;
+        }
+    }
+
+    if (failed)
+      return EXIT_FAILURE;
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_quan_float.cu b/test/test_nc_f_quan_float.cu
new file mode 100644
index 0000000000..e2cd182aed
--- /dev/null
+++ b/test/test_nc_f_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch non_central_f distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_nc_f_quan_nvrtc_double.cpp b/test/test_nc_f_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..c2a6acd553
--- /dev/null
+++ b/test/test_nc_f_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_nc_f_quan_nvrtc_float.cpp b/test/test_nc_f_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..2e2aefc5e5
--- /dev/null
+++ b/test/test_nc_f_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/non_central_f.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/non_central_f.hpp>
+extern "C" __global__ 
+void test_non_central_f_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_non_central_f_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_non_central_f_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_non_central_f_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::non_central_f_distribution<float_type>(0.5, 0.5, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial.cpp b/test/test_negative_binomial.cpp
index 069ebf8798..69f42b4a4b 100644
--- a/test/test_negative_binomial.cpp
+++ b/test/test_negative_binomial.cpp
@@ -26,9 +26,13 @@
 #  define TEST_REAL_CONCEPT
 #endif
 
-#include <boost/math/tools/test.hpp> // for real_concept
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
 using ::boost::math::concepts::real_concept;
+#endif
 
 #include <boost/math/distributions/negative_binomial.hpp> // for negative_binomial_distribution
 using boost::math::negative_binomial_distribution;
diff --git a/test/test_negative_binomial_cdf_double.cu b/test/test_negative_binomial_cdf_double.cu
new file mode 100644
index 0000000000..6c4ae4e07d
--- /dev/null
+++ b/test/test_negative_binomial_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_cdf_float.cu b/test/test_negative_binomial_cdf_float.cu
new file mode 100644
index 0000000000..0f5849474b
--- /dev/null
+++ b/test/test_negative_binomial_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_cdf_nvrtc_double.cpp b/test/test_negative_binomial_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1cb7af6663
--- /dev/null
+++ b/test/test_negative_binomial_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial_cdf_nvrtc_float.cpp b/test/test_negative_binomial_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..f0d1b16476
--- /dev/null
+++ b/test/test_negative_binomial_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial_pdf_double.cu b/test/test_negative_binomial_pdf_double.cu
new file mode 100644
index 0000000000..16bd2ee487
--- /dev/null
+++ b/test/test_negative_binomial_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_pdf_float.cu b/test/test_negative_binomial_pdf_float.cu
new file mode 100644
index 0000000000..d9965c3050
--- /dev/null
+++ b/test/test_negative_binomial_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_pdf_nvrtc_double.cpp b/test/test_negative_binomial_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..395f9a30e5
--- /dev/null
+++ b/test/test_negative_binomial_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial_pdf_nvrtc_float.cpp b/test/test_negative_binomial_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..ad20351fcd
--- /dev/null
+++ b/test/test_negative_binomial_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial_quan_double.cu b/test/test_negative_binomial_quan_double.cu
new file mode 100644
index 0000000000..2ecabc86c7
--- /dev/null
+++ b/test/test_negative_binomial_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_quan_float.cu b/test/test_negative_binomial_quan_float.cu
new file mode 100644
index 0000000000..e9a3aece3a
--- /dev/null
+++ b/test/test_negative_binomial_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch negative_binomial distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_negative_binomial_quan_nvrtc_double.cpp b/test/test_negative_binomial_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..c63342ba66
--- /dev/null
+++ b/test/test_negative_binomial_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_negative_binomial_quan_nvrtc_float.cpp b/test/test_negative_binomial_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..6d7e98839f
--- /dev/null
+++ b/test/test_negative_binomial_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/negative_binomial.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/negative_binomial.hpp>
+extern "C" __global__ 
+void test_negative_binomial_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_negative_binomial_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_negative_binomial_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_negative_binomial_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::negative_binomial_distribution<float_type>(1, 0.5), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal.cpp b/test/test_normal.cpp
index ef984d5e63..e68a1f82e3 100644
--- a/test/test_normal.cpp
+++ b/test/test_normal.cpp
@@ -15,7 +15,9 @@
 // From MathWorld--A Wolfram Web Resource.
 // http://mathworld.wolfram.com/NormalDistribution.html
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp> // include directory /libs/math/src/tr1/ is needed.
+#endif
 
 #ifdef _MSC_VER
 #  pragma warning (disable: 4127) // conditional expression is constant
@@ -23,15 +25,20 @@
 // and   if (std::numeric_limits<RealType>::has_quiet_NaN)
 #endif
 
-#include <boost/math/tools/test.hpp>
+#include <boost/math/tools/config.hpp>
+
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/normal.hpp>
     using boost::math::normal_distribution;
-#include <boost/math/tools/test.hpp>
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_normal_cdf_double.cu b/test/test_normal_cdf_double.cu
new file mode 100644
index 0000000000..cd99d49253
--- /dev/null
+++ b/test/test_normal_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_cdf_float.cu b/test/test_normal_cdf_float.cu
new file mode 100644
index 0000000000..c8e422f6e3
--- /dev/null
+++ b/test/test_normal_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_cdf_nvrtc_double.cpp b/test/test_normal_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..934e18d434
--- /dev/null
+++ b/test/test_normal_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal_cdf_nvrtc_float.cpp b/test/test_normal_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..06a2351d2e
--- /dev/null
+++ b/test/test_normal_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal_pdf_double.cu b/test/test_normal_pdf_double.cu
new file mode 100644
index 0000000000..b318023318
--- /dev/null
+++ b/test/test_normal_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_pdf_float.cu b/test/test_normal_pdf_float.cu
new file mode 100644
index 0000000000..155278fede
--- /dev/null
+++ b/test/test_normal_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_pdf_nvrtc_double.cpp b/test/test_normal_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..216e264dd1
--- /dev/null
+++ b/test/test_normal_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal_pdf_nvrtc_float.cpp b/test/test_normal_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..669a1aad26
--- /dev/null
+++ b/test/test_normal_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal_quan_double.cu b/test/test_normal_quan_double.cu
new file mode 100644
index 0000000000..ca7fea427f
--- /dev/null
+++ b/test/test_normal_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_quan_float.cu b/test/test_normal_quan_float.cu
new file mode 100644
index 0000000000..ca7fea427f
--- /dev/null
+++ b/test/test_normal_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch normal distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::normal_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_normal_quan_nvrtc_double.cpp b/test/test_normal_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..f47650f708
--- /dev/null
+++ b/test/test_normal_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_normal_quan_nvrtc_float.cpp b/test/test_normal_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..d988472778
--- /dev/null
+++ b/test/test_normal_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/normal.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/normal.hpp>
+extern "C" __global__ 
+void test_normal_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::normal_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_normal_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_normal_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_normal_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::normal_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto.cpp b/test/test_pareto.cpp
index 35a5bb0098..b59b93f189 100644
--- a/test/test_pareto.cpp
+++ b/test/test_pareto.cpp
@@ -24,15 +24,19 @@
 #  pragma warning(disable: 4100) // unreferenced formal parameter.
 #endif
 
-#include <boost/math/tools/test.hpp> // for real_concept
+#include <boost/math/tools/config.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/pareto.hpp>
     using boost::math::pareto_distribution;
-#include <boost/math/tools/test.hpp>
 #include "test_out_of_range.hpp"
 
 #include <iostream>
@@ -47,11 +51,13 @@
   void check_pareto(RealType scale, RealType shape, RealType x, RealType p, RealType q, RealType tol)
   {
     RealType logtol = tol * 10;
+    #ifndef BOOST_MATH_HAS_GPU_SUPPORT
     BOOST_IF_CONSTEXPR (std::is_same<RealType, long double>::value || 
                         std::is_same<RealType, boost::math::concepts::real_concept>::value)
     {
       logtol *= 100;
     }
+    #endif
     
     BOOST_CHECK_CLOSE_FRACTION(
       ::boost::math::cdf(
diff --git a/test/test_pareto_cdf_double.cu b/test/test_pareto_cdf_double.cu
new file mode 100644
index 0000000000..94ca6618a2
--- /dev/null
+++ b/test/test_pareto_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_cdf_float.cu b/test/test_pareto_cdf_float.cu
new file mode 100644
index 0000000000..7778900a47
--- /dev/null
+++ b/test/test_pareto_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_cdf_nvrtc_double.cpp b/test/test_pareto_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..55e7ecbb0a
--- /dev/null
+++ b/test/test_pareto_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto_cdf_nvrtc_float.cpp b/test/test_pareto_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..a9d4f62500
--- /dev/null
+++ b/test/test_pareto_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto_pdf_double.cu b/test/test_pareto_pdf_double.cu
new file mode 100644
index 0000000000..0eae49b445
--- /dev/null
+++ b/test/test_pareto_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_pdf_float.cu b/test/test_pareto_pdf_float.cu
new file mode 100644
index 0000000000..8dbd97311a
--- /dev/null
+++ b/test/test_pareto_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_pdf_nvrtc_double.cpp b/test/test_pareto_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..6533303cd6
--- /dev/null
+++ b/test/test_pareto_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto_pdf_nvrtc_float.cpp b/test/test_pareto_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..a5d415ae4f
--- /dev/null
+++ b/test/test_pareto_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto_quan_double.cu b/test/test_pareto_quan_double.cu
new file mode 100644
index 0000000000..1d2c47ef93
--- /dev/null
+++ b/test/test_pareto_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_quan_float.cu b/test/test_pareto_quan_float.cu
new file mode 100644
index 0000000000..410067ea5c
--- /dev/null
+++ b/test/test_pareto_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch pareto distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::pareto_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_pareto_quan_nvrtc_double.cpp b/test/test_pareto_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..59444ee351
--- /dev/null
+++ b/test/test_pareto_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_pareto_quan_nvrtc_float.cpp b/test/test_pareto_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..75eda6bee4
--- /dev/null
+++ b/test/test_pareto_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/pareto.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/pareto.hpp>
+extern "C" __global__ 
+void test_pareto_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::pareto_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_pareto_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_pareto_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_pareto_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::pareto_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson.cpp b/test/test_poisson.cpp
index 73de4751e3..2a0bc4c499 100644
--- a/test/test_poisson.cpp
+++ b/test/test_poisson.cpp
@@ -23,19 +23,24 @@
 #  pragma warning(disable: 4127) // conditional expression is constant.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #include <boost/math/distributions/poisson.hpp>
     using boost::math::poisson_distribution;
-#include <boost/math/tools/test.hpp> // for real_concept
 
 #include <boost/math/special_functions/gamma.hpp> // for (incomplete) gamma.
 //   using boost::math::qamma_Q;
 #include "table_type.hpp"
 #include "test_out_of_range.hpp"
+#include "../include_private/boost/math/tools/test.hpp"
 
 #include <iostream>
    using std::cout;
@@ -106,6 +111,7 @@ void test_spots(RealType)
   using  ::boost::math::pdf;
 
    // Check that bad arguments throw.
+   #ifndef BOOST_MATH_NO_EXCEPTIONS
    BOOST_MATH_CHECK_THROW(
    cdf(poisson_distribution<RealType>(static_cast<RealType>(0)), // mean zero is bad.
       static_cast<RealType>(0)),  // even for a good k.
@@ -155,6 +161,7 @@ void test_spots(RealType)
      quantile(complement(poisson_distribution<RealType>(static_cast<RealType>(1)), 
       static_cast<RealType>(0))),  // bad probability. 
       std::overflow_error);
+   #endif
 
   BOOST_CHECK_EQUAL(
      quantile(poisson_distribution<RealType>(static_cast<RealType>(1)), 
@@ -559,6 +566,7 @@ BOOST_AUTO_TEST_CASE( test_main )
   // poisson mydudpoisson(0.);
   // throws (if BOOST_MATH_DOMAIN_ERROR_POLICY == throw_on_error).
 
+#ifndef BOOST_MATH_NO_EXCEPTIONS
 #ifndef BOOST_NO_EXCEPTIONS
   BOOST_MATH_CHECK_THROW(poisson mydudpoisson(-1), std::domain_error);// Mean must be > 0.
   BOOST_MATH_CHECK_THROW(poisson mydudpoisson(-1), std::logic_error);// Mean must be > 0.
@@ -570,7 +578,7 @@ BOOST_AUTO_TEST_CASE( test_main )
   // BOOST_MATH_CHECK_THROW(poisson mydudpoisson(-1), std::overflow_error); // fails the check
   // because overflow_error is unrelated - except from std::exception
   BOOST_MATH_CHECK_THROW(cdf(mypoisson, -1), std::domain_error); // k must be >= 0
-
+#endif
   BOOST_CHECK_EQUAL(mean(mypoisson), 4.);
   BOOST_CHECK_CLOSE(
   pdf(mypoisson, 2.),  // k events = 2. 
diff --git a/test/test_poisson_cdf_double.cu b/test/test_poisson_cdf_double.cu
new file mode 100644
index 0000000000..34ca74a622
--- /dev/null
+++ b/test/test_poisson_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_cdf_float.cu b/test/test_poisson_cdf_float.cu
new file mode 100644
index 0000000000..0c024f6692
--- /dev/null
+++ b/test/test_poisson_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_cdf_nvrtc_double.cpp b/test/test_poisson_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..81ef15adc6
--- /dev/null
+++ b/test/test_poisson_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson_cdf_nvrtc_float.cpp b/test/test_poisson_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..8e53303873
--- /dev/null
+++ b/test/test_poisson_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson_pdf_double.cu b/test/test_poisson_pdf_double.cu
new file mode 100644
index 0000000000..616fe0ba4f
--- /dev/null
+++ b/test/test_poisson_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_pdf_float.cu b/test/test_poisson_pdf_float.cu
new file mode 100644
index 0000000000..81ac558999
--- /dev/null
+++ b/test/test_poisson_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_pdf_nvrtc_double.cpp b/test/test_poisson_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..514963d638
--- /dev/null
+++ b/test/test_poisson_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson_pdf_nvrtc_float.cpp b/test/test_poisson_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..9b79360094
--- /dev/null
+++ b/test/test_poisson_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson_quan_double.cu b/test/test_poisson_quan_double.cu
new file mode 100644
index 0000000000..b1ef1a17c5
--- /dev/null
+++ b/test/test_poisson_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_quan_float.cu b/test/test_poisson_quan_float.cu
new file mode 100644
index 0000000000..82a28bd882
--- /dev/null
+++ b/test/test_poisson_quan_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch poisson distribution kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::poisson_distribution<float_type>(), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_poisson_quan_nvrtc_double.cpp b/test/test_poisson_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..572d57a257
--- /dev/null
+++ b/test/test_poisson_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_poisson_quan_nvrtc_float.cpp b/test/test_poisson_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..34bd1ea53c
--- /dev/null
+++ b/test/test_poisson_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/poisson.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/poisson.hpp>
+extern "C" __global__ 
+void test_poisson_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::poisson_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_poisson_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_poisson_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_poisson_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::poisson_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh.cpp b/test/test_rayleigh.cpp
index de92dfa848..0d4ebf2a80 100644
--- a/test/test_rayleigh.cpp
+++ b/test/test_rayleigh.cpp
@@ -13,10 +13,15 @@
 #  pragma warning(disable: 4100) // unreferenced formal parameter.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #include <boost/math/distributions/rayleigh.hpp>
     using boost::math::rayleigh_distribution;
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
@@ -36,11 +41,13 @@ void test_spot(RealType s, RealType x, RealType p, RealType q, RealType toleranc
 {
    RealType logtolerance = tolerance;
 
+   #ifndef BOOST_MATH_HAS_GPU_SUPPORT
    BOOST_IF_CONSTEXPR (std::is_same<RealType, long double>::value || 
                        std::is_same<RealType, boost::math::concepts::real_concept>::value)
    {
       logtolerance *= 100;
    }
+   #endif
    
    BOOST_CHECK_CLOSE(
       ::boost::math::cdf(
diff --git a/test/test_rayleigh_cdf_double.cu b/test/test_rayleigh_cdf_double.cu
new file mode 100644
index 0000000000..d6056dcaf1
--- /dev/null
+++ b/test/test_rayleigh_cdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_cdf_float.cu b/test/test_rayleigh_cdf_float.cu
new file mode 100644
index 0000000000..2c86ec1ba3
--- /dev/null
+++ b/test/test_rayleigh_cdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_cdf_nvrtc_double.cpp b/test/test_rayleigh_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f57595d195
--- /dev/null
+++ b/test/test_rayleigh_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh_cdf_nvrtc_float.cpp b/test/test_rayleigh_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..aeeaacadfb
--- /dev/null
+++ b/test/test_rayleigh_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh_pdf_double.cu b/test/test_rayleigh_pdf_double.cu
new file mode 100644
index 0000000000..b83ae3cbf0
--- /dev/null
+++ b/test/test_rayleigh_pdf_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_pdf_float.cu b/test/test_rayleigh_pdf_float.cu
new file mode 100644
index 0000000000..a5bfee42da
--- /dev/null
+++ b/test/test_rayleigh_pdf_float.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_pdf_nvrtc_double.cpp b/test/test_rayleigh_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..17662bba07
--- /dev/null
+++ b/test/test_rayleigh_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh_pdf_nvrtc_float.cpp b/test/test_rayleigh_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..82cc534e8b
--- /dev/null
+++ b/test/test_rayleigh_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh_quan_double.cu b/test/test_rayleigh_quan_double.cu
new file mode 100644
index 0000000000..65084e57cf
--- /dev/null
+++ b/test/test_rayleigh_quan_double.cu
@@ -0,0 +1,110 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_quan_float.cu b/test/test_rayleigh_quan_float.cu
new file mode 100644
index 0000000000..7a03396646
--- /dev/null
+++ b/test/test_rayleigh_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::rayleigh_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::rayleigh_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_rayleigh_quan_nvrtc_double.cpp b/test/test_rayleigh_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..c105b50470
--- /dev/null
+++ b/test/test_rayleigh_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_rayleigh_quan_nvrtc_float.cpp b/test/test_rayleigh_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..88c9418a32
--- /dev/null
+++ b/test/test_rayleigh_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/rayleigh.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/rayleigh.hpp>
+extern "C" __global__ 
+void test_rayleigh_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::rayleigh_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_rayleigh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_rayleigh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_rayleigh_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::rayleigh_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t.cpp b/test/test_students_t.cpp
index ad4dc4187b..b6aec11f44 100644
--- a/test/test_students_t.cpp
+++ b/test/test_students_t.cpp
@@ -18,13 +18,19 @@
 #  pragma warning (disable :4127) // conditional expression is constant.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/next.hpp>  // for has_denorm_now
 
+#include "../include_private/boost/math/tools/test.hpp"
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
-#include <boost/math/tools/test.hpp> // for real_concept
+#endif
+
 #include "test_out_of_range.hpp"
 #include <boost/math/distributions/students_t.hpp>
     using boost::math::students_t_distribution;
@@ -35,6 +41,7 @@
    using std::setprecision;
 #include <limits>
   using std::numeric_limits;
+#include <type_traits>
 
 template <class RealType>
 RealType naive_pdf(RealType v, RealType t)
@@ -528,7 +535,10 @@ void test_spots(RealType)
 
     std::string type = typeid(RealType).name();
 //    if (type != "class boost::math::concepts::real_concept") fails for gcc
-    if (typeid(RealType) != typeid(boost::math::concepts::real_concept))
+
+    #ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
+    BOOST_MATH_IF_CONSTEXPR(!std::is_same<RealType, boost::math::concepts::real_concept>::value)
+    #endif
     { // Ordinary floats only.
       RealType limit = 1/ boost::math::tools::epsilon<RealType>();
       // Default policy to get full accuracy.
diff --git a/test/test_students_t_cdf_double.cu b/test/test_students_t_cdf_double.cu
new file mode 100644
index 0000000000..e8f47faa25
--- /dev/null
+++ b/test/test_students_t_cdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_cdf_float.cu b/test/test_students_t_cdf_float.cu
new file mode 100644
index 0000000000..22fd5d7c01
--- /dev/null
+++ b/test/test_students_t_cdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_cdf_nvrtc_double.cpp b/test/test_students_t_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..c88bdd18d5
--- /dev/null
+++ b/test/test_students_t_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t_cdf_nvrtc_float.cpp b/test/test_students_t_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..b5c1b37229
--- /dev/null
+++ b/test/test_students_t_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t_pdf_double.cu b/test/test_students_t_pdf_double.cu
new file mode 100644
index 0000000000..187f63ff52
--- /dev/null
+++ b/test/test_students_t_pdf_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_pdf_float.cu b/test/test_students_t_pdf_float.cu
new file mode 100644
index 0000000000..ba0469b0e3
--- /dev/null
+++ b/test/test_students_t_pdf_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_pdf_nvrtc_double.cpp b/test/test_students_t_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..e67eb382a0
--- /dev/null
+++ b/test/test_students_t_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t_pdf_nvrtc_float.cpp b/test/test_students_t_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..e0c9556840
--- /dev/null
+++ b/test/test_students_t_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t_quan_double.cu b/test/test_students_t_quan_double.cu
new file mode 100644
index 0000000000..fe6d999528
--- /dev/null
+++ b/test/test_students_t_quan_double.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_quan_float.cu b/test/test_students_t_quan_float.cu
new file mode 100644
index 0000000000..6293ec3f83
--- /dev/null
+++ b/test/test_students_t_quan_float.cu
@@ -0,0 +1,109 @@
+//  Copyright John Maddock 2016.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::students_t_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
\ No newline at end of file
diff --git a/test/test_students_t_quan_nvrtc_double.cpp b/test/test_students_t_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..e5b5f60f38
--- /dev/null
+++ b/test/test_students_t_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_students_t_quan_nvrtc_float.cpp b/test/test_students_t_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..db41964a93
--- /dev/null
+++ b/test/test_students_t_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/students_t.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/students_t.hpp>
+extern "C" __global__ 
+void test_students_t_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::students_t_distribution<float_type>(1), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_students_t_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_students_t_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_students_t_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::students_t_distribution<float_type>(1), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular.cpp b/test/test_triangular.cpp
index 8efb17d85c..d8f37b8520 100644
--- a/test/test_triangular.cpp
+++ b/test/test_triangular.cpp
@@ -8,21 +8,28 @@
 
 // test_triangular.cpp
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp>
+#endif
 
 #ifdef _MSC_VER
 #  pragma warning(disable: 4127) // conditional expression is constant.
 #  pragma warning(disable: 4305) // truncation from 'long double' to 'float'
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/triangular.hpp>
 using boost::math::triangular_distribution;
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/special_functions/fpclassify.hpp>
 #include "test_out_of_range.hpp"
 
@@ -463,8 +470,11 @@ void test_spots(RealType)
     BOOST_CHECK_CLOSE_FRACTION(
       mode(tridef), static_cast<RealType>(0), tolerance);
     // skewness:
+    // On device the result does not get flushed exactly to zero so the eps difference is by default huge
+    #ifndef BOOST_MATH_HAS_GPU_SUPPORT
     BOOST_CHECK_CLOSE_FRACTION(
       median(tridef), static_cast<RealType>(0), tolerance);
+    #endif
     // https://reference.wolfram.com/language/ref/Skewness.html  skewness{-1, 0, +1} = 0
     // skewness[triangulardistribution{-1, 0, +1}] does not compute a result.
     // skewness[triangulardistribution{0, +1}] result == 0
diff --git a/test/test_triangular_cdf_double.cu b/test/test_triangular_cdf_double.cu
new file mode 100644
index 0000000000..38affb91bd
--- /dev/null
+++ b/test/test_triangular_cdf_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_cdf_float.cu b/test/test_triangular_cdf_float.cu
new file mode 100644
index 0000000000..c1bb22bd3f
--- /dev/null
+++ b/test/test_triangular_cdf_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_cdf_nvrtc_double.cpp b/test/test_triangular_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f23009d92d
--- /dev/null
+++ b/test/test_triangular_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular_cdf_nvrtc_float.cpp b/test/test_triangular_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..e17f5c8146
--- /dev/null
+++ b/test/test_triangular_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular_pdf_double.cu b/test/test_triangular_pdf_double.cu
new file mode 100644
index 0000000000..38050faff8
--- /dev/null
+++ b/test/test_triangular_pdf_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_pdf_float.cu b/test/test_triangular_pdf_float.cu
new file mode 100644
index 0000000000..82e1be5fcc
--- /dev/null
+++ b/test/test_triangular_pdf_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_pdf_nvrtc_double.cpp b/test/test_triangular_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..4fd23a51dc
--- /dev/null
+++ b/test/test_triangular_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular_pdf_nvrtc_float.cpp b/test/test_triangular_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..17128139cc
--- /dev/null
+++ b/test/test_triangular_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular_quan_double.cu b/test/test_triangular_quan_double.cu
new file mode 100644
index 0000000000..5751ead020
--- /dev/null
+++ b/test/test_triangular_quan_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_quan_float.cu b/test/test_triangular_quan_float.cu
new file mode 100644
index 0000000000..579e10fd54
--- /dev/null
+++ b/test/test_triangular_quan_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::triangular_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::triangular_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_triangular_quan_nvrtc_double.cpp b/test/test_triangular_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..c41b3a11bc
--- /dev/null
+++ b/test/test_triangular_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_triangular_quan_nvrtc_float.cpp b/test/test_triangular_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..256a7f2d28
--- /dev/null
+++ b/test/test_triangular_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/triangular.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/triangular.hpp>
+extern "C" __global__ 
+void test_triangular_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::triangular_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_triangular_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_triangular_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_triangular_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::triangular_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform.cpp b/test/test_uniform.cpp
index 65d192a4d6..4e034cab74 100644
--- a/test/test_uniform.cpp
+++ b/test/test_uniform.cpp
@@ -8,21 +8,28 @@
 
 // test_uniform.cpp
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch.hpp>
+#endif
 
 #ifdef _MSC_VER
 #  pragma warning(disable: 4127) // conditional expression is constant.
 #  pragma warning(disable: 4100) // unreferenced formal parameter.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp> // for real_concept
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp> // Boost.Test
 #include <boost/test/tools/floating_point_comparison.hpp>
 
 #include <boost/math/distributions/uniform.hpp>
     using boost::math::uniform_distribution;
-#include <boost/math/tools/test.hpp> 
+#include "../include_private/boost/math/tools/test.hpp"
 #include "test_out_of_range.hpp"
 
 #include <iostream>
diff --git a/test/test_uniform_cdf_double.cu b/test/test_uniform_cdf_double.cu
new file mode 100644
index 0000000000..beb98c34dd
--- /dev/null
+++ b/test/test_uniform_cdf_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_cdf_float.cu b/test/test_uniform_cdf_float.cu
new file mode 100644
index 0000000000..7aef4a6be1
--- /dev/null
+++ b/test/test_uniform_cdf_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(cdf(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_cdf_nvrtc_double.cpp b/test/test_uniform_cdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..1b6b563a05
--- /dev/null
+++ b/test/test_uniform_cdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform_cdf_nvrtc_float.cpp b/test/test_uniform_cdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..6ba98900f9
--- /dev/null
+++ b/test/test_uniform_cdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = cdf(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = cdf(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform_pdf_double.cu b/test/test_uniform_pdf_double.cu
new file mode 100644
index 0000000000..6b1cf83e0d
--- /dev/null
+++ b/test/test_uniform_pdf_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_pdf_float.cu b/test/test_uniform_pdf_float.cu
new file mode 100644
index 0000000000..4b003d22a1
--- /dev/null
+++ b/test/test_uniform_pdf_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(pdf(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_pdf_nvrtc_double.cpp b/test/test_uniform_pdf_nvrtc_double.cpp
new file mode 100644
index 0000000000..f638c43961
--- /dev/null
+++ b/test/test_uniform_pdf_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform_pdf_nvrtc_float.cpp b/test/test_uniform_pdf_nvrtc_float.cpp
new file mode 100644
index 0000000000..81da44417a
--- /dev/null
+++ b/test/test_uniform_pdf_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = pdf(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = pdf(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform_quan_double.cu b/test/test_uniform_quan_double.cu
new file mode 100644
index 0000000000..ab11374754
--- /dev/null
+++ b/test/test_uniform_quan_double.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_quan_float.cu b/test/test_uniform_quan_float.cu
new file mode 100644
index 0000000000..7a7e4ccf50
--- /dev/null
+++ b/test/test_uniform_quan_float.cu
@@ -0,0 +1,113 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <boost/random/mersenne_twister.hpp>
+#include <boost/random/uniform_real_distribution.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::uniform_distribution<float_type>(1), in1[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+  try{
+
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    boost::random::mt19937 gen;
+    boost::random::uniform_real_distribution<float_type> dist;
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = dist(gen);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+    std::cout << "CUDA kernal done in " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(quantile(boost::math::uniform_distribution<float_type>(1), input_vector1[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+          if (boost::math::epsilon_difference(output_vector[i], results[i]) > 100.0)
+          {
+              std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+              std::cerr << "Error rate was: " << boost::math::epsilon_difference(output_vector[i], results[i]) << "eps" << std::endl;
+              return EXIT_FAILURE;
+          }
+        }
+    }
+
+    std::cout << "Test PASSED with calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+  }
+  catch(const std::exception& e)
+  {
+    std::cerr << "Stopped with exception: " << e.what() << std::endl;
+  }
+  return 0;
+}
diff --git a/test/test_uniform_quan_nvrtc_double.cpp b/test/test_uniform_quan_nvrtc_double.cpp
new file mode 100644
index 0000000000..13b8c6d230
--- /dev/null
+++ b/test/test_uniform_quan_nvrtc_double.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_uniform_quan_nvrtc_float.cpp b/test/test_uniform_quan_nvrtc_float.cpp
new file mode 100644
index 0000000000..57372dee3f
--- /dev/null
+++ b/test/test_uniform_quan_nvrtc_float.cpp
@@ -0,0 +1,191 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/distributions/uniform.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/distributions/uniform.hpp>
+extern "C" __global__ 
+void test_uniform_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = quantile(boost::math::uniform_distribution<float_type>(), in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_uniform_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_uniform_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_uniform_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = quantile(boost::math::uniform_distribution<float_type>(), h_in1[i]);
+            
+            if (boost::math::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From cb068993561cb143da401d5cf4ad52efc4b6ea57 Mon Sep 17 00:00:00 2001
From: jzmaddock <john@johnmaddock.co.uk>
Date: Sat, 7 Sep 2024 17:36:39 +0100
Subject: [PATCH 376/399] Catch evaluation_error's in
 temme_method_2_ibeta_inverse (#1175)

Catch evaluation_error's in temme_method_2_ibeta_inverse
fixes https://github.com/boostorg/math/issues/1169.
Add test case.
---
 .../detail/ibeta_inverse.hpp                  | 21 +++++++++++++---
 test/Jamfile.v2                               |  1 +
 test/git_issue_1175.cpp                       | 25 +++++++++++++++++++
 3 files changed, 44 insertions(+), 3 deletions(-)
 create mode 100644 test/git_issue_1175.cpp

diff --git a/include/boost/math/special_functions/detail/ibeta_inverse.hpp b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
index 90f6e90705..6f222cf77d 100644
--- a/include/boost/math/special_functions/detail/ibeta_inverse.hpp
+++ b/include/boost/math/special_functions/detail/ibeta_inverse.hpp
@@ -304,9 +304,23 @@ BOOST_MATH_GPU_ENABLED T temme_method_2_ibeta_inverse(T /*a*/, T /*b*/, T z, T r
    //
    // And iterate:
    //
-   x = tools::newton_raphson_iterate(
-      temme_root_finder<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 2);
-
+#ifndef BOOST_MATH_NO_EXCEPTIONS
+   try {
+#endif
+      x = tools::newton_raphson_iterate(
+         temme_root_finder<T>(-lu, alpha), x, lower, upper, policies::digits<T, Policy>() / 2);
+#ifndef BOOST_MATH_NO_EXCEPTIONS
+   }
+   catch (const boost::math::evaluation_error&)
+   {
+      // Due to numerical instability we may have cases where no root is found when
+      // in fact we should just touch the origin.  We simply ignore the error here
+      // and return our best guess for x so far...
+      // Maybe we should special case the symmetrical parameter case, but it's not clear 
+      // whether that is the only situation when problems can occur.
+      // See https://github.com/boostorg/math/issues/1169
+   }
+#endif
    return x;
 }
 //
@@ -321,6 +335,7 @@ BOOST_MATH_GPU_ENABLED T temme_method_3_ibeta_inverse(T a, T b, T p, T q, const
 {
    BOOST_MATH_STD_USING // ADL of std names
 
+
    //
    // Begin by getting an initial approximation for the quantity
    // eta from the dominant part of the incomplete beta:
diff --git a/test/Jamfile.v2 b/test/Jamfile.v2
index e6814fd867..e19957777e 100644
--- a/test/Jamfile.v2
+++ b/test/Jamfile.v2
@@ -192,6 +192,7 @@ test-suite special_fun :
    [ run git_issue_184.cpp ]
    [ run git_issue_1137.cpp ]
    [ run git_issue_1139.cpp ]
+   [ run git_issue_1175.cpp ]
    [ run special_functions_test.cpp /boost/test//boost_unit_test_framework  ]
    [ run test_airy.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
    [ run test_bessel_j.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
diff --git a/test/git_issue_1175.cpp b/test/git_issue_1175.cpp
new file mode 100644
index 0000000000..9770acf537
--- /dev/null
+++ b/test/git_issue_1175.cpp
@@ -0,0 +1,25 @@
+//  (C) Copyright Matt Borland 2023.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include "math_unit_test.hpp"
+#include <iostream>
+#include <boost/math/distributions/beta.hpp>
+
+using namespace std;
+using boost::math::beta_distribution;
+
+int main(int argc, char* argv[])
+{
+   double a = 5.0;
+   double b = 5.0;
+   double p = 0.5;
+
+   beta_distribution<> dist(a, b);
+   double x = quantile(dist, p);
+
+   CHECK_ULP_CLOSE(x, 0.5, 2);
+
+   return boost::math::test::report_errors();
+}

From d2fe8e388d6332cc8b59dfa93f15664420c2aa04 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 9 Sep 2024 10:03:03 -0400
Subject: [PATCH 377/399] Add test set

---
 test/Jamfile.v2         |  1 +
 test/git_issue_1194.cpp | 41 +++++++++++++++++++++++++++++++++++++++++
 2 files changed, 42 insertions(+)
 create mode 100644 test/git_issue_1194.cpp

diff --git a/test/Jamfile.v2 b/test/Jamfile.v2
index e19957777e..4adb29d160 100644
--- a/test/Jamfile.v2
+++ b/test/Jamfile.v2
@@ -193,6 +193,7 @@ test-suite special_fun :
    [ run git_issue_1137.cpp ]
    [ run git_issue_1139.cpp ]
    [ run git_issue_1175.cpp ]
+   [ run git_issue_1194.cpp ]
    [ run special_functions_test.cpp /boost/test//boost_unit_test_framework  ]
    [ run test_airy.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
    [ run test_bessel_j.cpp test_instances//test_instances pch_light /boost/test//boost_unit_test_framework  ]
diff --git a/test/git_issue_1194.cpp b/test/git_issue_1194.cpp
new file mode 100644
index 0000000000..1c364a0c4d
--- /dev/null
+++ b/test/git_issue_1194.cpp
@@ -0,0 +1,41 @@
+//  (C) Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include "math_unit_test.hpp"
+#include <boost/math/special_functions/gamma.hpp>
+#include <cerrno>
+
+int main()
+{
+    using c99_error_policy = ::boost::math::policies::policy<
+            ::boost::math::policies::domain_error< ::boost::math::policies::errno_on_error>,
+            ::boost::math::policies::pole_error< ::boost::math::policies::errno_on_error>,
+            ::boost::math::policies::overflow_error< ::boost::math::policies::errno_on_error>,
+            ::boost::math::policies::evaluation_error< ::boost::math::policies::errno_on_error>,
+            ::boost::math::policies::rounding_error< ::boost::math::policies::errno_on_error> >;
+
+    double val = -std::numeric_limits<double>::infinity();
+
+    val = boost::math::tgamma(val, c99_error_policy());
+    CHECK_EQUAL(errno, EDOM);
+
+    val = std::numeric_limits<double>::quiet_NaN();
+    val = boost::math::tgamma(val, c99_error_policy());
+    CHECK_EQUAL(errno, EDOM);
+
+    val = std::numeric_limits<double>::infinity();
+    val = boost::math::tgamma(val, c99_error_policy());
+    CHECK_EQUAL(errno, ERANGE);
+
+    val = 0;
+    val = boost::math::tgamma(val, c99_error_policy());
+    CHECK_EQUAL(errno, EDOM); // OK
+
+    val = -2;
+    val = boost::math::tgamma(val, c99_error_policy());
+    CHECK_EQUAL(errno, EDOM); // OK
+
+    return boost::math::test::report_errors();
+}

From 9d133071d064857bd50bf85391c9218dab0ed16b Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 9 Sep 2024 10:28:00 -0400
Subject: [PATCH 378/399] Fix removed error check

---
 .../boost/math/special_functions/gamma.hpp    | 39 +++++++++++--------
 1 file changed, 22 insertions(+), 17 deletions(-)

diff --git a/include/boost/math/special_functions/gamma.hpp b/include/boost/math/special_functions/gamma.hpp
index 41c85936dd..4a15782c01 100644
--- a/include/boost/math/special_functions/gamma.hpp
+++ b/include/boost/math/special_functions/gamma.hpp
@@ -197,25 +197,30 @@ BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T gamma_imp(T z, const Policy& pol
 {
    BOOST_MATH_STD_USING
 
-   if(z <= -20)
-   {
-      constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
-      T result = gamma_imp_final(T(-z), pol, l) * sinpx(z);
-      BOOST_MATH_INSTRUMENT_VARIABLE(result);
-      if((fabs(result) < 1) && (tools::max_value<T>() * fabs(result) < boost::math::constants::pi<T>()))
-         return -boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
-      result = -boost::math::constants::pi<T>() / result;
-      if(result == 0)
-         return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
-      if((boost::math::fpclassify)(result) == (int)BOOST_MATH_FP_SUBNORMAL)
-         return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
-      BOOST_MATH_INSTRUMENT_VARIABLE(result);
-      return result;
-   }
-   else
+   T result = 1;
+   constexpr auto function = "boost::math::tgamma<%1%>(%1%)";
+
+   if(z <= 0)
    {
-      return gamma_imp_final(T(z), pol, l);
+      if(floor(z) == z)
+         return policies::raise_pole_error<T>(function, "Evaluation of tgamma at a negative integer %1%.", z, pol);
+      if(z <= -20)
+      {
+         result = gamma_imp_final(T(-z), pol, l) * sinpx(z);
+         BOOST_MATH_INSTRUMENT_VARIABLE(result);
+         if((fabs(result) < 1) && (tools::max_value<T>() * fabs(result) < boost::math::constants::pi<T>()))
+            return -boost::math::sign(result) * policies::raise_overflow_error<T>(function, "Result of tgamma is too large to represent.", pol);
+         result = -boost::math::constants::pi<T>() / result;
+         if(result == 0)
+            return policies::raise_underflow_error<T>(function, "Result of tgamma is too small to represent.", pol);
+         if((boost::math::fpclassify)(result) == BOOST_MATH_FP_SUBNORMAL)
+            return policies::raise_denorm_error<T>(function, "Result of tgamma is denormalized.", result, pol);
+         BOOST_MATH_INSTRUMENT_VARIABLE(result);
+         return result;
+      }
    }
+
+   return gamma_imp_final(T(z), pol, l);
 }
 
 #ifdef BOOST_MATH_ENABLE_CUDA

From b5214b5935bea24021c719eea3451d1eec3024fb Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 12 Sep 2024 10:25:17 -0400
Subject: [PATCH 379/399] Add device only impl

Add function for device only impl

Fix function signatures

Fix arrays

Add basic test for compilation

Allow serial implementation to be run on host under NVCC

Add verification steps

Add arrays of levels coefficient sizes

Cleanup test set

Add double test set

Add structure for the doubles support

Save space by using pointer to different size arrays rather than 2d

Separate the double precision weights into their own arrays

Remove stray call to std::abs

Add NVRTC testing

Add documentation section

Add device function signature for sinh_sinh_integrate

Add float coefficients

Add double coeffs

Add device specific impl

Add sinh_sinh CUDA testing

Add sinh_sinh NVRTC testing
---
 doc/quadrature/double_exponential.qbk         |   25 +
 .../quadrature/detail/exp_sinh_detail.hpp     | 1460 ++++++++++++++++-
 .../quadrature/detail/sinh_sinh_detail.hpp    |  869 +++++++++-
 include/boost/math/quadrature/exp_sinh.hpp    |   83 +-
 include/boost/math/quadrature/sinh_sinh.hpp   |   33 +-
 test/cuda_jamfile                             |    6 +
 test/nvrtc_jamfile                            |    6 +
 test/test_exp_sinh_quad_double.cu             |  133 ++
 test/test_exp_sinh_quad_float.cu              |  133 ++
 test/test_exp_sinh_quad_nvrtc_double.cpp      |  206 +++
 test/test_exp_sinh_quad_nvrtc_float.cpp       |  206 +++
 test/test_sinh_sinh_quad_double.cu            |  133 ++
 test/test_sinh_sinh_quad_float.cu             |  133 ++
 test/test_sinh_sinh_quad_nvrtc_double.cpp     |  206 +++
 test/test_sinh_sinh_quad_nvrtc_float.cpp      |  206 +++
 15 files changed, 3831 insertions(+), 7 deletions(-)
 create mode 100644 test/test_exp_sinh_quad_double.cu
 create mode 100644 test/test_exp_sinh_quad_float.cu
 create mode 100644 test/test_exp_sinh_quad_nvrtc_double.cpp
 create mode 100644 test/test_exp_sinh_quad_nvrtc_float.cpp
 create mode 100644 test/test_sinh_sinh_quad_double.cu
 create mode 100644 test/test_sinh_sinh_quad_float.cu
 create mode 100644 test/test_sinh_sinh_quad_nvrtc_double.cpp
 create mode 100644 test/test_sinh_sinh_quad_nvrtc_float.cpp

diff --git a/doc/quadrature/double_exponential.qbk b/doc/quadrature/double_exponential.qbk
index b4649adbc6..2959b94cd3 100644
--- a/doc/quadrature/double_exponential.qbk
+++ b/doc/quadrature/double_exponential.qbk
@@ -1,5 +1,6 @@
 [/
 Copyright (c) 2017 Nick Thompson
+Copyright (c) 2024 Matt Borland
 Use, modification and distribution are subject to the
 Boost Software License, Version 1.0. (See accompanying file
 LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -538,6 +539,30 @@ This form integrates just fine over (-log([pi]/2), +[infin]) using either the `t
 
 [endsect] [/section:de_caveats Caveats]
 
+[section:gpu_usage GPU Usage]
+
+``
+    #include <boost/math/quadrature/exp_sinh.hpp>
+
+    namespace boost{ namespace math{ namespace quadrature {
+
+    template <class F, class Real, class Policy = policies::policy<> >
+    __device__ auto exp_sinh_integrate(const F& f, Real a, Real b, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+
+    template <class F, class Real, class Policy = policies::policy<> >
+    __device__ auto exp_sinh_integrate(const F& f, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+
+}}}
+``
+
+Quadrature is additionally able to run on CUDA (NVCC and NVRTC) platforms.
+The major difference is outlined in the above function signatures.
+When used on device these are free standing functions instead of using OOP like on the host.
+The tables of abscissas and weights are stored in shared read only memory on the device instead of being initialized when the class is constructed.
+An example use case would be in the finite elements method computing a stiffness matrix since it would consist of many different functions.
+
+[endsect] [/section:gpu_usage Usage]
+
 [section:de_refes References]
 
 * Hidetosi Takahasi and Masatake Mori, ['Double Exponential Formulas for Numerical Integration] Publ. Res. Inst. Math. Sci., 9 (1974), pp. 721-741.
diff --git a/include/boost/math/quadrature/detail/exp_sinh_detail.hpp b/include/boost/math/quadrature/detail/exp_sinh_detail.hpp
index 2df07b6ecc..77f2fbf060 100644
--- a/include/boost/math/quadrature/detail/exp_sinh_detail.hpp
+++ b/include/boost/math/quadrature/detail/exp_sinh_detail.hpp
@@ -7,6 +7,10 @@
 #ifndef BOOST_MATH_QUADRATURE_DETAIL_EXP_SINH_DETAIL_HPP
 #define BOOST_MATH_QUADRATURE_DETAIL_EXP_SINH_DETAIL_HPP
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <vector>
 #include <typeinfo>
@@ -541,4 +545,1458 @@ void exp_sinh_detail<Real, Policy>::init(const std::integral_constant<int, 4>&)
 }
 }
 }
-#endif
+
+#endif // BOOST_MATH_HAS_NVRTC
+
+#ifdef BOOST_MATH_ENABLE_CUDA // BOOST_MATH_ENABLE_CUDA
+
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+namespace boost { 
+namespace math { 
+namespace quadrature {
+namespace detail {
+
+// In the CUDA case we break these down into a series of fixed size arrays and then make a pointer to the arrays
+// We can't use a 2D array because it takes up far too much memory that is primarily wasted space
+
+__constant__ float m_abscissas_float_1[9] =
+      { 3.47876573e-23f, 5.62503650e-09f, 9.95706124e-04f, 9.67438487e-02f, 7.43599217e-01f, 4.14293205e+00f, 
+        1.08086768e+02f, 4.56291316e+05f, 2.70123007e+15f, };
+
+__constant__ float m_abscissas_float_2[8] =
+      { 2.41870864e-14f, 1.02534662e-05f, 1.65637566e-02f, 3.11290799e-01f, 1.64691269e+00f, 1.49800773e+01f, 
+        2.57724301e+03f, 2.24833766e+09f, };
+
+__constant__ float m_abscissas_float_3[16] =
+      { 3.24983286e-18f, 2.51095186e-11f, 3.82035773e-07f, 1.33717837e-04f, 4.80260650e-03f, 4.41526928e-02f, 
+        1.83045938e-01f, 4.91960276e-01f, 1.10322609e+00f, 2.53681744e+00f, 7.39791792e+00f, 3.59560256e+01f, 
+        4.36061333e+02f, 2.49501460e+04f, 1.89216933e+07f, 1.03348694e+12f, };
+
+__constant__ float m_abscissas_float_4[33] =
+      { 1.51941172e-20f, 3.70201714e-16f, 9.67598102e-13f, 4.44773051e-10f, 5.28493928e-08f, 2.19158236e-06f, 
+        4.00799258e-05f, 3.88011529e-04f, 2.29325538e-03f, 9.25182629e-03f, 2.78117501e-02f, 6.67553298e-02f, 
+        1.35173168e-01f, 2.41374946e-01f, 3.94194704e-01f, 6.07196731e-01f, 9.06432514e-01f, 1.34481045e+00f, 
+        2.03268444e+00f, 3.21243032e+00f, 5.46310949e+00f, 1.03365745e+01f, 2.26486752e+01f, 6.03727778e+01f, 
+        2.08220266e+02f, 1.00431239e+03f, 7.47843388e+03f, 9.75279951e+04f, 2.61755592e+06f, 1.77776624e+08f, 
+        3.98255346e+10f, 4.13443763e+13f, 3.07708133e+17f, };
+
+__constant__ float m_abscissas_float_5[66] =
+      { 7.99409438e-22f, 2.41624595e-19f, 3.73461321e-17f, 3.19397902e-15f, 1.62042378e-13f, 5.18579386e-12f, 
+        1.10520072e-10f, 1.64548212e-09f, 1.78534009e-08f, 1.46529196e-07f, 9.40168786e-07f, 4.85507733e-06f, 
+        2.07038029e-05f, 7.45799409e-05f, 2.31536599e-04f, 6.30580368e-04f, 1.53035449e-03f, 3.35582040e-03f, 
+        6.73124842e-03f, 1.24856832e-02f, 2.16245309e-02f, 3.52720523e-02f, 5.45995171e-02f, 8.07587788e-02f, 
+        1.14840025e-01f, 1.57867103e-01f, 2.10837078e-01f, 2.74805391e-01f, 3.51015955e-01f, 4.41077540e-01f, 
+        5.47194016e-01f, 6.72466825e-01f, 8.21304567e-01f, 1.00000000e+00f, 1.21757511e+00f, 1.48706221e+00f, 
+        1.82750536e+00f, 2.26717507e+00f, 2.84887335e+00f, 3.63893880e+00f, 4.74299876e+00f, 6.33444194e+00f, 
+        8.70776542e+00f, 1.23825548e+01f, 1.83151803e+01f, 2.83510579e+01f, 4.62437776e+01f, 8.00917327e+01f, 
+        1.48560852e+02f, 2.97989725e+02f, 6.53443372e+02f, 1.58584068e+03f, 4.31897162e+03f, 1.34084311e+04f, 
+        4.83003053e+04f, 2.05969943e+05f, 1.06363880e+06f, 6.82457850e+06f, 5.60117371e+07f, 6.07724622e+08f, 
+        9.04813016e+09f, 1.92834507e+11f, 6.17122515e+12f, 3.13089095e+14f, 2.67765347e+16f, 4.13865153e+18f, };
+
+__constant__ float m_abscissas_float_6[132] =
+      { 1.70893932e-22f, 3.56621447e-21f, 6.19138882e-20f, 9.04299298e-19f, 1.12287188e-17f, 1.19706303e-16f, 
+        1.10583090e-15f, 8.92931857e-15f, 6.35404710e-14f, 4.01527389e-13f, 2.26955738e-12f, 1.15522811e-11f, 
+        5.32913181e-11f, 2.24130967e-10f, 8.64254491e-10f, 3.07161058e-09f, 1.01117742e-08f, 3.09775637e-08f, 
+        8.87004371e-08f, 2.38368096e-07f, 6.03520392e-07f, 1.44488635e-06f, 3.28212299e-06f, 7.09655821e-06f, 
+        1.46494407e-05f, 2.89537394e-05f, 5.49357161e-05f, 1.00313252e-04f, 1.76700203e-04f, 3.00920507e-04f, 
+        4.96484845e-04f, 7.95150594e-04f, 1.23845781e-03f, 1.87911525e-03f, 2.78210510e-03f, 4.02538552e-03f, 
+        5.70009588e-03f, 7.91020800e-03f, 1.07716137e-02f, 1.44106884e-02f, 1.89624177e-02f, 2.45682104e-02f, 
+        3.13735515e-02f, 3.95256605e-02f, 4.91713196e-02f, 6.04550279e-02f, 7.35176150e-02f, 8.84954195e-02f, 
+        1.05520113e-01f, 1.24719213e-01f, 1.46217318e-01f, 1.70138063e-01f, 1.96606781e-01f, 2.25753880e-01f,
+        2.57718900e-01f, 2.92655274e-01f, 3.30735809e-01f, 3.72158929e-01f, 4.17155794e-01f, 4.65998399e-01f,
+        5.19008863e-01f, 5.76570161e-01f, 6.39138643e-01f, 7.07258781e-01f, 7.81580731e-01f, 8.62881450e-01f, 
+        9.52090320e-01f, 1.05032052e+00f, 1.15890775e+00f, 1.27945836e+00f, 1.41390963e+00f, 1.56460576e+00f,
+        1.73439430e+00f, 1.92674937e+00f, 2.14593012e+00f, 2.39718593e+00f, 2.68702407e+00f, 3.02356133e+00f,
+        3.41698950e+00f, 3.88019661e+00f, 4.42960272e+00f, 5.08629455e+00f, 5.87757956e+00f, 6.83913514e+00f,
+        8.01801085e+00f, 9.47686632e+00f, 1.13000199e+01f, 1.36021823e+01f, 1.65412214e+01f, 2.03370584e+01f, 
+        2.53000199e+01f, 3.18739815e+01f, 4.07030054e+01f, 5.27358913e+01f, 6.93929374e+01f, 9.28366010e+01f,
+        1.26418926e+02f, 1.75435645e+02f, 2.48423411e+02f, 3.59440052e+02f, 5.32165336e+02f, 8.07455844e+02f,
+        1.25762341e+03f, 2.01416017e+03f, 3.32313676e+03f, 5.65930306e+03f, 9.96877263e+03f, 1.82030939e+04f,
+        3.45378531e+04f, 6.82619916e+04f, 1.40913380e+05f, 3.04680844e+05f, 6.92095957e+05f, 1.65694484e+06f,
+        4.19519229e+06f, 1.12739016e+07f, 3.22814282e+07f, 9.88946136e+07f, 3.25562103e+08f, 1.15706659e+09f,
+        4.46167708e+09f, 1.87647826e+10f, 8.65629909e+10f, 4.40614549e+11f, 2.49049013e+12f, 1.57380011e+13f,
+        1.11990629e+14f, 9.04297390e+14f, 8.35377903e+15f, 8.90573552e+16f, 1.10582857e+18f, 1.61514650e+19f, };
+
+__constant__ float m_abscissas_float_7[263] =
+      { 7.75845008e-23f, 3.71846701e-22f, 1.69833677e-21f, 7.40284853e-21f, 3.08399399e-20f, 1.22962599e-19f, 
+        4.69855182e-19f, 1.72288020e-18f, 6.07012059e-18f, 2.05742924e-17f, 6.71669437e-17f, 2.11441966e-16f, 
+        6.42566550e-16f, 1.88715605e-15f, 5.36188198e-15f, 1.47533056e-14f, 3.93507835e-14f, 1.01841667e-13f,
+        2.55981752e-13f, 6.25453236e-13f, 1.48683211e-12f, 3.44173601e-12f, 7.76421789e-12f, 1.70831312e-11f,
+        3.66877698e-11f, 7.69632540e-11f, 1.57822184e-10f, 3.16577320e-10f, 6.21604166e-10f, 1.19551931e-09f,
+        2.25364361e-09f, 4.16647469e-09f, 7.55905964e-09f, 1.34658870e-08f, 2.35675936e-08f, 4.05458117e-08f,
+        6.86052525e-08f, 1.14227960e-07f, 1.87243781e-07f, 3.02323521e-07f, 4.81026747e-07f, 7.54564302e-07f,
+        1.16746531e-06f, 1.78236867e-06f, 2.68618781e-06f, 3.99792342e-06f, 5.87841837e-06f, 8.54236163e-06f,
+        1.22728487e-05f, 1.74387947e-05f, 2.45154696e-05f, 3.41083807e-05f, 4.69806683e-05f, 6.40841007e-05f,
+        8.65936597e-05f, 1.15945600e-04f, 1.53878746e-04f, 2.02478652e-04f, 2.64224143e-04f, 3.42035594e-04f,
+        4.39324211e-04f, 5.60041454e-04f, 7.08727668e-04f, 8.90558896e-04f, 1.11139085e-03f, 1.37779898e-03f,
+        1.69711358e-03f, 2.07744903e-03f, 2.52772622e-03f, 3.05768742e-03f, 3.67790298e-03f, 4.39976940e-03f,
+        5.23549846e-03f, 6.19809738e-03f, 7.30134015e-03f, 8.55973022e-03f, 9.98845520e-03f, 1.16033342e-02f,
+        1.34207587e-02f, 1.54576276e-02f, 1.77312787e-02f, 2.02594158e-02f, 2.30600348e-02f, 2.61513493e-02f,
+        2.95517158e-02f, 3.32795626e-02f, 3.73533204e-02f, 4.17913590e-02f, 4.66119283e-02f, 5.18331072e-02f,
+        5.74727595e-02f, 6.35484986e-02f, 7.00776615e-02f, 7.70772927e-02f, 8.45641386e-02f, 9.25546518e-02f,
+        1.01065008e-01f, 1.10111132e-01f, 1.19708739e-01f, 1.29873379e-01f, 1.40620505e-01f, 1.51965539e-01f,
+        1.63923958e-01f, 1.76511391e-01f, 1.89743720e-01f, 2.03637197e-01f, 2.18208574e-01f, 2.33475238e-01f,
+        2.49455360e-01f, 2.66168055e-01f, 2.83633553e-01f, 3.01873381e-01f, 3.20910560e-01f, 3.40769809e-01f,
+        3.61477772e-01f, 3.83063247e-01f, 4.05557445e-01f, 4.28994258e-01f, 4.53410546e-01f, 4.78846448e-01f,
+        5.05345717e-01f, 5.32956079e-01f, 5.61729623e-01f, 5.91723220e-01f, 6.22998983e-01f, 6.55624768e-01f,
+        6.89674714e-01f, 7.25229845e-01f, 7.62378724e-01f, 8.01218171e-01f, 8.41854062e-01f, 8.84402205e-01f,
+        9.28989312e-01f, 9.75754080e-01f, 1.02484839e+00f, 1.07643865e+00f, 1.13070727e+00f, 1.18785434e+00f,
+        1.24809950e+00f, 1.31168403e+00f, 1.37887320e+00f, 1.44995892e+00f, 1.52526270e+00f, 1.60513906e+00f,
+        1.68997931e+00f, 1.78021589e+00f, 1.87632722e+00f, 1.97884333e+00f, 2.08835213e+00f, 2.20550671e+00f,
+        2.33103353e+00f, 2.46574193e+00f, 2.61053497e+00f, 2.76642183e+00f, 2.93453226e+00f, 3.11613304e+00f,
+        3.31264716e+00f, 3.52567596e+00f, 3.75702486e+00f, 4.00873326e+00f, 4.28310945e+00f, 4.58277134e+00f,
+        4.91069419e+00f, 5.27026666e+00f, 5.66535674e+00f, 6.10038953e+00f, 6.58043928e+00f, 7.11133842e+00f,
+        7.69980735e+00f, 8.35360902e+00f, 9.08173387e+00f, 9.89462150e+00f, 1.08044272e+01f, 1.18253437e+01f,
+        1.29739897e+01f, 1.42698826e+01f, 1.57360130e+01f, 1.73995473e+01f, 1.92926887e+01f, 2.14537359e+01f,
+        2.39283915e+01f, 2.67713817e+01f, 3.00484719e+01f, 3.38389827e+01f, 3.82389447e+01f, 4.33650689e+01f,
+        4.93597649e+01f, 5.63975118e+01f, 6.46929803e+01f, 7.45114359e+01f, 8.61821250e+01f, 1.00115581e+02f,
+        1.16826112e+02f, 1.36961158e+02f, 1.61339834e+02f, 1.91003781e+02f, 2.27284639e+02f, 2.71894067e+02f,
+        3.27044548e+02f, 3.95612465e+02f, 4.81359585e+02f, 5.89235756e+02f, 7.25795284e+02f, 8.99773468e+02f,
+        1.12289036e+03f, 1.41097920e+03f, 1.78558211e+03f, 2.27622329e+03f, 2.92367233e+03f, 3.78466551e+03f,
+        4.93879227e+03f, 6.49862329e+03f, 8.62473434e+03f, 1.15481896e+04f, 1.56044945e+04f, 2.12853507e+04f,
+        2.93183077e+04f, 4.07905708e+04f, 5.73434125e+04f, 8.14806753e+04f, 1.17063646e+05f, 1.70113785e+05f,
+        2.50129854e+05f, 3.72274789e+05f, 5.61051155e+05f, 8.56556497e+05f, 1.32526810e+06f, 2.07888648e+06f,
+        3.30771485e+06f, 5.34063130e+06f, 8.75442405e+06f, 1.45761434e+07f, 2.46634599e+07f, 4.24311457e+07f,
+        7.42617251e+07f, 1.32291588e+08f, 2.40011058e+08f, 4.43725882e+08f, 8.36456588e+08f, 1.60874083e+09f,
+        3.15878598e+09f, 6.33624483e+09f, 1.29932136e+10f, 2.72570398e+10f, 5.85372779e+10f, 1.28795973e+11f,
+        2.90551047e+11f, 6.72570892e+11f, 1.59884056e+12f, 3.90652847e+12f, 9.81916374e+12f, 2.54124546e+13f,
+        6.77814197e+13f, 1.86501681e+14f, 5.29897885e+14f, 1.55625904e+15f, 4.72943011e+15f, 1.48882761e+16f,
+        4.86043448e+16f, 1.64741373e+17f, 5.80423410e+17f, 2.12831536e+18f, 8.13255421e+18f, };
+
+__constant__ float m_abscissas_float_8[527] =
+      { 5.20331508e-23f, 1.15324162e-22f, 2.52466875e-22f, 5.46028730e-22f, 1.16690465e-21f, 2.46458927e-21f,
+        5.14543768e-21f, 1.06205431e-20f, 2.16767715e-20f, 4.37564009e-20f, 8.73699691e-20f, 1.72595588e-19f,
+        3.37377643e-19f, 6.52669145e-19f, 1.24976973e-18f, 2.36916845e-18f, 4.44691383e-18f, 8.26580373e-18f,
+        1.52174118e-17f, 2.77517606e-17f, 5.01415830e-17f, 8.97689232e-17f, 1.59270821e-16f, 2.80084735e-16f,
+        4.88253693e-16f, 8.43846463e-16f, 1.44610939e-15f, 2.45762595e-15f, 4.14251017e-15f, 6.92627770e-15f,
+        1.14889208e-14f, 1.89084205e-14f, 3.08802476e-14f, 5.00504297e-14f, 8.05169965e-14f, 1.28579121e-13f,
+        2.03847833e-13f, 3.20880532e-13f, 5.01568631e-13f, 7.78600100e-13f, 1.20044498e-12f, 1.83848331e-12f,
+        2.79712543e-12f, 4.22808302e-12f, 6.35035779e-12f, 9.47805307e-12f, 1.40588174e-11f, 2.07266430e-11f,
+        3.03739182e-11f, 4.42491437e-11f, 6.40886341e-11f, 9.22929507e-11f, 1.32161843e-10f, 1.88205259e-10f,
+        2.66552657e-10f, 3.75488615e-10f, 5.26149742e-10f, 7.33426418e-10f, 1.01712318e-09f, 1.40344387e-09f,
+        1.92688222e-09f, 2.63261606e-09f, 3.57952343e-09f, 4.84396276e-09f, 6.52448685e-09f, 8.74769197e-09f,
+        1.16754399e-08f, 1.55137320e-08f, 2.05235608e-08f, 2.70341184e-08f, 3.54587968e-08f, 4.63144836e-08f,
+        6.02447248e-08f, 7.80474059e-08f, 1.00707687e-07f, 1.29437018e-07f, 1.65719157e-07f, 2.11364220e-07f,
+        2.68571894e-07f, 3.40005066e-07f, 4.28875221e-07f, 5.39041105e-07f, 6.75122241e-07f, 8.42629031e-07f,
+        1.04811127e-06f, 1.29932703e-06f, 1.60543396e-06f, 1.97720518e-06f, 2.42727196e-06f, 2.97039558e-06f,
+        3.62377065e-06f, 4.40736236e-06f, 5.34428013e-06f, 6.46118994e-06f, 7.78876789e-06f, 9.36219733e-06f,
+        1.12217116e-05f, 1.34131848e-05f, 1.59887725e-05f, 1.90076038e-05f, 2.25365270e-05f, 2.66509096e-05f,
+        3.14354940e-05f, 3.69853096e-05f, 4.34066412e-05f, 5.08180543e-05f, 5.93514765e-05f, 6.91533342e-05f,
+        8.03857429e-05f, 9.32277499e-05f, 1.07876627e-04f, 1.24549208e-04f, 1.43483273e-04f, 1.64938971e-04f,
+        1.89200275e-04f, 2.16576471e-04f, 2.47403671e-04f, 2.82046341e-04f, 3.20898851e-04f, 3.64387021e-04f,
+        4.12969671e-04f, 4.67140163e-04f, 5.27427922e-04f, 5.94399942e-04f, 6.68662248e-04f, 7.50861330e-04f,
+        8.41685517e-04f, 9.41866302e-04f, 1.05217960e-03f, 1.17344692e-03f, 1.30653650e-03f, 1.45236427e-03f,
+        1.61189482e-03f, 1.78614219e-03f, 1.97617055e-03f, 2.18309485e-03f, 2.40808123e-03f, 2.65234740e-03f,
+        2.91716284e-03f, 3.20384886e-03f, 3.51377855e-03f, 3.84837661e-03f, 4.20911898e-03f, 4.59753235e-03f,
+        5.01519359e-03f, 5.46372894e-03f, 5.94481312e-03f, 6.46016832e-03f, 7.01156301e-03f, 7.60081065e-03f,
+        8.22976829e-03f, 8.90033499e-03f, 9.61445021e-03f, 1.03740920e-02f, 1.11812753e-02f, 1.20380497e-02f, 
+        1.29464978e-02f, 1.39087327e-02f, 1.49268962e-02f, 1.60031562e-02f, 1.71397050e-02f, 1.83387564e-02f,
+        1.96025436e-02f, 2.09333170e-02f, 2.23333419e-02f, 2.38048956e-02f, 2.53502659e-02f, 2.69717481e-02f,
+        2.86716433e-02f, 3.04522558e-02f, 3.23158911e-02f, 3.42648538e-02f, 3.63014456e-02f, 3.84279634e-02f,
+        4.06466974e-02f, 4.29599296e-02f, 4.53699317e-02f, 4.78789641e-02f, 5.04892744e-02f, 5.32030959e-02f,
+        5.60226468e-02f, 5.89501290e-02f, 6.19877276e-02f, 6.51376099e-02f, 6.84019251e-02f, 7.17828036e-02f,
+        7.52823576e-02f, 7.89026802e-02f, 8.26458461e-02f, 8.65139116e-02f, 9.05089155e-02f, 9.46328794e-02f,
+        9.88878087e-02f, 1.03275694e-01f, 1.07798510e-01f, 1.12458223e-01f, 1.17256783e-01f, 1.22196135e-01f,
+        1.27278214e-01f, 1.32504950e-01f, 1.37878272e-01f, 1.43400107e-01f, 1.49072382e-01f, 1.54897032e-01f,
+        1.60875997e-01f, 1.67011231e-01f, 1.73304700e-01f, 1.79758387e-01f, 1.86374297e-01f, 1.93154462e-01f,
+        2.00100939e-01f, 2.07215821e-01f, 2.14501238e-01f, 2.21959362e-01f, 2.29592410e-01f, 2.37402653e-01f,
+        2.45392415e-01f, 2.53564085e-01f, 2.61920117e-01f, 2.70463037e-01f, 2.79195450e-01f, 2.88120044e-01f,
+        2.97239599e-01f, 3.06556989e-01f, 3.16075193e-01f, 3.25797297e-01f, 3.35726506e-01f, 3.45866147e-01f,
+        3.56219679e-01f, 3.66790698e-01f, 3.77582948e-01f, 3.88600328e-01f, 3.99846898e-01f, 4.11326892e-01f,
+        4.23044723e-01f, 4.35004995e-01f, 4.47212512e-01f, 4.59672288e-01f, 4.72389556e-01f, 4.85369781e-01f,
+        4.98618671e-01f, 5.12142186e-01f, 5.25946554e-01f, 5.40038281e-01f, 5.54424165e-01f, 5.69111309e-01f,
+        5.84107138e-01f, 5.99419409e-01f, 6.15056232e-01f, 6.31026081e-01f, 6.47337815e-01f, 6.64000696e-01f,
+        6.81024405e-01f, 6.98419060e-01f, 7.16195243e-01f, 7.34364016e-01f, 7.52936944e-01f, 7.71926120e-01f,
+        7.91344191e-01f, 8.11204381e-01f, 8.31520518e-01f, 8.52307069e-01f, 8.73579162e-01f, 8.95352625e-01f,
+        9.17644013e-01f, 9.40470650e-01f, 9.63850664e-01f, 9.87803022e-01f, 1.01234758e+00f, 1.03750512e+00f,
+        1.06329740e+00f, 1.08974721e+00f, 1.11687839e+00f, 1.14471595e+00f, 1.17328606e+00f, 1.20261614e+00f,
+        1.23273496e+00f, 1.26367264e+00f, 1.29546076e+00f, 1.32813247e+00f, 1.36172249e+00f, 1.39626730e+00f,
+        1.43180514e+00f, 1.46837616e+00f, 1.50602252e+00f, 1.54478848e+00f, 1.58472055e+00f, 1.62586760e+00f,
+        1.66828098e+00f, 1.71201469e+00f, 1.75712551e+00f, 1.80367319e+00f, 1.85172058e+00f, 1.90133388e+00f,
+        1.95258276e+00f, 2.00554062e+00f, 2.06028484e+00f, 2.11689693e+00f, 2.17546288e+00f, 2.23607339e+00f,
+        2.29882418e+00f, 2.36381627e+00f, 2.43115639e+00f, 2.50095725e+00f, 2.57333803e+00f, 2.64842468e+00f,
+        2.72635049e+00f, 2.80725648e+00f, 2.89129193e+00f, 2.97861498e+00f, 3.06939317e+00f, 3.16380413e+00f,
+        3.26203621e+00f, 3.36428929e+00f, 3.47077553e+00f, 3.58172026e+00f, 3.69736291e+00f, 3.81795798e+00f,
+        3.94377618e+00f, 4.07510558e+00f, 4.21225285e+00f, 4.35554468e+00f, 4.50532923e+00f, 4.66197775e+00f,
+        4.82588634e+00f, 4.99747780e+00f, 5.17720373e+00f, 5.36554672e+00f, 5.56302277e+00f, 5.77018396e+00f,
+        5.98762126e+00f, 6.21596768e+00f, 6.45590164e+00f, 6.70815069e+00f, 6.97349551e+00f, 7.25277437e+00f,
+        7.54688785e+00f, 7.85680417e+00f, 8.18356491e+00f, 8.52829128e+00f, 8.89219104e+00f, 9.27656603e+00f,
+        9.68282047e+00f, 1.01124700e+01f, 1.05671518e+01f, 1.10486353e+01f, 1.15588347e+01f, 1.20998217e+01f,
+        1.26738407e+01f, 1.32833247e+01f, 1.39309131e+01f, 1.46194716e+01f, 1.53521138e+01f, 1.61322255e+01f,
+        1.69634913e+01f, 1.78499242e+01f, 1.87958987e+01f, 1.98061868e+01f, 2.08859991e+01f, 2.20410294e+01f,
+        2.32775056e+01f, 2.46022448e+01f, 2.60227166e+01f, 2.75471124e+01f, 2.91844234e+01f, 3.09445281e+01f,
+        3.28382897e+01f, 3.48776660e+01f, 3.70758319e+01f, 3.94473180e+01f, 4.20081658e+01f, 4.47761023e+01f,
+        4.77707378e+01f, 5.10137879e+01f, 5.45293247e+01f, 5.83440613e+01f, 6.24876734e+01f, 6.69931639e+01f,
+        7.18972765e+01f, 7.72409663e+01f, 8.30699343e+01f, 8.94352364e+01f, 9.63939781e+01f, 1.04010108e+02f,
+        1.12355322e+02f, 1.21510104e+02f, 1.31564914e+02f, 1.42621552e+02f, 1.54794728e+02f, 1.68213867e+02f,
+        1.83025185e+02f, 1.99394097e+02f, 2.17507985e+02f, 2.37579409e+02f, 2.59849828e+02f, 2.84593917e+02f,
+        3.12124587e+02f, 3.42798827e+02f, 3.77024517e+02f, 4.15268384e+02f, 4.58065302e+02f, 5.06029199e+02f,
+        5.59865843e+02f, 6.20387872e+02f, 6.88532497e+02f, 7.65382367e+02f, 8.52190227e+02f, 9.50408087e+02f,
+        1.06172182e+03f, 1.18809220e+03f, 1.33180384e+03f, 1.49552334e+03f, 1.68236894e+03f, 1.89599367e+03f,
+        2.14068513e+03f, 2.42148533e+03f, 2.74433485e+03f, 3.11624675e+03f, 3.54551666e+03f, 4.04197722e+03f,
+        4.61730674e+03f, 5.28540457e+03f, 6.06284853e+03f, 6.96945350e+03f, 8.02895513e+03f, 9.26984864e+03f,
+        1.07264200e+04f, 1.24400169e+04f, 1.44606187e+04f, 1.68487805e+04f, 1.96780458e+04f, 2.30379493e+04f,
+        2.70377620e+04f, 3.18111749e+04f, 3.75221715e+04f, 4.43724093e+04f, 5.26105241e+04f, 6.25438881e+04f,
+        7.45535092e+04f, 8.91129656e+04f, 1.06812532e+05f, 1.28390012e+05f, 1.54770253e+05f, 1.87115940e+05f,
+        2.26893075e+05f, 2.75955654e+05f, 3.36655497e+05f, 4.11985149e+05f, 5.05764405e+05f, 6.22884544e+05f,
+        7.69629183e+05f, 9.54097173e+05f, 1.18676186e+06f, 1.48121324e+06f, 1.85514609e+06f, 2.33168052e+06f,
+        2.94113264e+06f, 3.72339780e+06f, 4.73116974e+06f, 6.03430539e+06f, 7.72576515e+06f, 9.92972861e+06f,
+        1.28127257e+07f, 1.65989637e+07f, 2.15915179e+07f, 2.82017465e+07f, 3.69902945e+07f, 4.87244884e+07f,
+        6.44590226e+07f, 8.56498776e+07f, 1.14315868e+08f, 1.53268759e+08f, 2.06442545e+08f, 2.79366798e+08f,
+        3.79850300e+08f, 5.18973079e+08f, 7.12532948e+08f, 9.83165083e+08f, 1.36346329e+09f, 1.90059962e+09f,
+        2.66319659e+09f, 3.75160395e+09f, 5.31334782e+09f, 7.56648043e+09f, 1.08350637e+10f, 1.56033907e+10f,
+        2.25993074e+10f, 3.29229832e+10f, 4.82470799e+10f, 7.11297379e+10f, 1.05506900e+11f, 1.57471442e+11f,
+        2.36513804e+11f, 3.57509889e+11f, 5.43926613e+11f, 8.33024431e+11f, 1.28435637e+12f, 1.99374510e+12f,
+        3.11642465e+12f, 4.90561997e+12f, 7.77731247e+12f, 1.24197380e+13f, 1.99798484e+13f, 3.23831600e+13f,
+        5.28864904e+13f, 8.70403770e+13f, 1.44377694e+14f, 2.41399528e+14f, 4.06896744e+14f, 6.91510621e+14f,
+        1.18504970e+15f, 2.04811559e+15f, 3.57034809e+15f, 6.27861398e+15f, 1.11397125e+16f, 1.99435267e+16f,
+        3.60337498e+16f, 6.57141972e+16f, 1.20980371e+17f, 2.24875057e+17f, 4.22089025e+17f, 8.00147402e+17f,
+        1.53216987e+18f, 2.96403754e+18f, 5.79389087e+18f, 1.14455803e+19f, 2.28537992e+19f, };
+
+__constant__ float* m_abscissas_float[8] = {
+    m_abscissas_float_1,
+    m_abscissas_float_2,
+    m_abscissas_float_3,
+    m_abscissas_float_4,
+    m_abscissas_float_5,
+    m_abscissas_float_6,
+    m_abscissas_float_7,
+    m_abscissas_float_8,
+};
+
+__constant__ float m_weights_float_1[9] = 
+      { 1.79979618e-21f, 1.07218106e-07f, 7.05786060e-03f, 2.72310168e-01f, 1.18863515e+00f, 8.77655464e+00f, 
+        5.33879432e+02f, 5.98892409e+06f, 9.60751551e+16f, };
+
+__constant__ float m_weights_float_2[8] =
+      { 7.59287827e-13f, 1.18886775e-04f, 7.27332179e-02f, 6.09156795e-01f, 2.71431234e+00f, 4.68800805e+01f, 
+        2.06437304e+04f, 4.85431236e+10f, };
+
+__constant__ float m_weights_float_3[16] = 
+      { 1.30963564e-16f, 6.14135316e-10f, 5.67743391e-06f, 1.21108690e-03f, 2.67259824e-02f, 1.54234107e-01f, 
+        4.23412860e-01f, 8.47913037e-01f, 1.73632925e+00f, 4.63203354e+00f, 1.88206826e+01f, 1.40643917e+02f, 
+        2.73736946e+03f, 2.55633252e+05f, 3.18438602e+08f, 2.86363931e+13f, };
+
+__constant__ float m_weights_float_4[33] = 
+      { 6.93769555e-19f, 1.31670336e-14f, 2.68107110e-11f, 9.60294960e-09f, 8.89417585e-07f, 2.87650015e-05f, 
+        4.10649371e-04f, 3.10797444e-03f, 1.43958814e-02f, 4.56980985e-02f, 1.08787148e-01f, 2.08910486e-01f,
+        3.43887471e-01f, 5.11338439e-01f, 7.19769211e-01f, 1.00073403e+00f, 1.42660267e+00f, 2.14966467e+00f,
+        3.50341221e+00f, 6.28632057e+00f, 1.26369961e+01f, 2.90949180e+01f, 7.91163114e+01f, 2.65103292e+02f,
+        1.15872311e+03f, 7.11886439e+03f, 6.77324248e+04f, 1.13081650e+06f, 3.88995005e+07f, 3.38857764e+09f,
+        9.74063570e+11f, 1.29789430e+15f, 1.24001927e+19f, };
+
+__constant__ float m_weights_float_5[66] = 
+      { 3.88541434e-20f, 1.03646493e-17f, 1.41388360e-15f, 1.06725054e-13f, 4.77908002e-12f, 1.34999345e-10f,
+        2.53970414e-09f, 3.33804787e-08f, 3.19755978e-07f, 2.31724882e-06f, 1.31302324e-05f, 5.98917639e-05f,
+        2.25650360e-04f, 7.18397083e-04f, 1.97196929e-03f, 4.75106406e-03f, 1.02072514e-02f, 1.98317011e-02f,
+        3.52844239e-02f, 5.81350403e-02f, 8.95955146e-02f, 1.30335749e-01f, 1.80445384e-01f, 2.39557131e-01f,
+        3.07102681e-01f, 3.82648608e-01f, 4.66260909e-01f, 5.58867257e-01f, 6.62616429e-01f, 7.81267733e-01f,
+        9.20677638e-01f, 1.08949034e+00f, 1.30019425e+00f, 1.57079633e+00f, 1.92752387e+00f, 2.40924883e+00f,
+        3.07485695e+00f, 4.01578082e+00f, 5.37784753e+00f, 7.40045071e+00f, 1.04890228e+01f, 1.53538346e+01f,
+        2.32861156e+01f, 3.67307348e+01f, 6.05296516e+01f, 1.04761593e+02f, 1.91598840e+02f, 3.72918009e+02f,
+        7.78738763e+02f, 1.76101294e+03f, 4.35837629e+03f, 1.19484066e+04f, 3.67841605e+04f, 1.29157756e+05f,
+        5.26424122e+05f, 2.54082527e+06f, 1.48545930e+07f, 1.07925566e+08f, 1.00317513e+09f, 1.23283860e+10f,
+        2.07922173e+11f, 5.01997049e+12f, 1.82006578e+14f, 1.04617001e+16f, 1.01373023e+18f, 1.77530238e+20f, };
+
+__constant__ float m_weights_float_6[132] = 
+      { 8.56958007e-21f, 1.68000718e-19f, 2.74008750e-18f, 3.75978801e-17f, 4.38589881e-16f, 4.39263787e-15f,
+        3.81223973e-14f, 2.89198757e-13f, 1.93338859e-12f, 1.14783389e-11f, 6.09544349e-11f, 2.91499607e-10f,
+        1.26339559e-09f, 4.99234840e-09f, 1.80872790e-08f, 6.03998541e-08f, 1.86829770e-07f, 5.37807971e-07f,
+        1.44704121e-06f, 3.65421571e-06f, 8.69454276e-06f, 1.95621880e-05f, 4.17628758e-05f, 8.48713297e-05f,
+        1.64680159e-04f, 3.05960283e-04f, 5.45748909e-04f, 9.36950301e-04f, 1.55189915e-03f, 2.48542560e-03f,
+        3.85690505e-03f, 5.81079770e-03f, 8.51529070e-03f, 1.21588421e-02f, 1.69446644e-02f, 2.30834400e-02f,
+        3.07847946e-02f, 4.02482241e-02f, 5.16542634e-02f, 6.51566792e-02f, 8.08763802e-02f, 9.88975757e-02f,
+        1.19266512e-01f, 1.41992893e-01f, 1.67053901e-01f, 1.94400532e-01f, 2.23965873e-01f, 2.55674859e-01f,
+        2.89455038e-01f, 3.25247905e-01f, 3.63020457e-01f, 4.02776696e-01f, 4.44568958e-01f, 4.88509042e-01f,
+        5.34779290e-01f, 5.83643845e-01f, 6.35460497e-01f, 6.90693630e-01f, 7.49928915e-01f, 8.13890578e-01f,
+        8.83462209e-01f, 9.59712352e-01f, 1.04392634e+00f, 1.13764623e+00f, 1.24272128e+00f, 1.36137177e+00f,
+        1.49627028e+00f, 1.65064527e+00f, 1.82841374e+00f, 2.03435175e+00f, 2.27431458e+00f, 2.55552245e+00f,
+        2.88693336e+00f, 3.27973254e+00f, 3.74797919e+00f, 4.30946679e+00f, 4.98687594e+00f, 5.80933099e+00f,
+        6.81451887e+00f, 8.05159726e+00f, 9.58522167e+00f, 1.15011733e+01f, 1.39143002e+01f, 1.69798351e+01f,
+        2.09096993e+01f, 2.59962450e+01f, 3.26472377e+01f, 4.14380231e+01f, 5.31903193e+01f, 6.90928164e+01f,
+        9.08883744e+01f, 1.21168895e+02f, 1.63847041e+02f, 2.24923217e+02f, 3.13754154e+02f, 4.45189215e+02f,
+        6.43236850e+02f, 9.47484116e+02f, 1.42457583e+03f, 2.18920236e+03f, 3.44338342e+03f, 5.55184130e+03f,
+        9.19045432e+03f, 1.56468513e+04f, 2.74471462e+04f, 4.97037777e+04f, 9.31107740e+04f, 1.80835335e+05f,
+        3.64968793e+05f, 7.67360053e+05f, 1.68525439e+06f, 3.87686515e+06f, 9.37022570e+06f, 2.38705733e+07f,
+        6.43128750e+07f, 1.83920179e+08f, 5.60444636e+08f, 1.82722217e+09f, 6.40182180e+09f, 2.42153053e+10f,
+        9.93804949e+10f, 4.44863150e+11f, 2.18425069e+12f, 1.18337660e+13f, 7.11948688e+13f, 4.78870731e+14f,
+        3.62710215e+15f, 3.11747341e+16f, 3.06542975e+17f, 3.47854955e+18f, 4.59768243e+19f, 7.14806140e+20f, };
+
+__constant__ float m_weights_float_7[263] = 
+      { 3.95175890e-21f, 1.83575349e-20f, 8.12661397e-20f, 3.43336935e-19f, 1.38634563e-18f, 5.35757029e-18f, 
+        1.98424944e-17f, 7.05221126e-17f, 2.40827550e-16f, 7.91175869e-16f, 2.50347754e-15f, 7.63871031e-15f,
+        2.25003103e-14f, 6.40502166e-14f, 1.76389749e-13f, 4.70424252e-13f, 1.21618334e-12f, 3.05082685e-12f,
+        7.43273471e-12f, 1.76028616e-11f, 4.05602375e-11f, 9.10055013e-11f, 1.98994391e-10f, 4.24390078e-10f,
+        8.83436580e-10f, 1.79636925e-09f, 3.57059250e-09f, 6.94247187e-09f, 1.32133371e-08f, 2.46332536e-08f,
+        4.50110843e-08f, 8.06630537e-08f, 1.41856144e-07f, 2.44958654e-07f, 4.15579069e-07f, 6.93056106e-07f,
+        1.13675616e-06f, 1.83473665e-06f, 2.91544023e-06f, 4.56318858e-06f, 7.03833675e-06f, 1.07030190e-05f,
+        1.60534529e-05f, 2.37597559e-05f, 3.47141604e-05f, 5.00883685e-05f, 7.14005734e-05f, 1.00592372e-04f,
+        1.40115414e-04f, 1.93027181e-04f, 2.63094779e-04f, 3.54905080e-04f, 4.73978972e-04f, 6.26886955e-04f,
+        8.21362793e-04f, 1.06641153e-03f, 1.37240787e-03f, 1.75118071e-03f, 2.21607971e-03f, 2.78201983e-03f,
+        3.46550010e-03f, 4.28459361e-03f, 5.25890609e-03f, 6.40950150e-03f, 7.75879384e-03f, 9.33040551e-03f,
+        1.11489935e-02f, 1.32400455e-02f, 1.56296499e-02f, 1.83442433e-02f, 2.14103400e-02f, 2.48542509e-02f,
+        2.87017958e-02f, 3.29780164e-02f, 3.77068968e-02f, 4.29110964e-02f, 4.86117029e-02f, 5.48280093e-02f,
+        6.15773214e-02f, 6.88747982e-02f, 7.67333308e-02f, 8.51634602e-02f, 9.41733378e-02f, 1.03768728e-01f,
+        1.13953051e-01f, 1.24727473e-01f, 1.36091031e-01f, 1.48040798e-01f, 1.60572082e-01f, 1.73678660e-01f,
+        1.87353038e-01f, 2.01586736e-01f, 2.16370598e-01f, 2.31695113e-01f, 2.47550758e-01f, 2.63928342e-01f,
+        2.80819365e-01f, 2.98216379e-01f, 3.16113348e-01f, 3.34506011e-01f, 3.53392244e-01f, 3.72772414e-01f,
+        3.92649735e-01f, 4.13030618e-01f, 4.33925021e-01f, 4.55346789e-01f, 4.77314001e-01f, 4.99849320e-01f,
+        5.22980337e-01f, 5.46739932e-01f, 5.71166640e-01f, 5.96305036e-01f, 6.22206131e-01f, 6.48927802e-01f,
+        6.76535247e-01f, 7.05101473e-01f, 7.34707835e-01f, 7.65444619e-01f, 7.97411688e-01f, 8.30719192e-01f,
+        8.65488366e-01f, 9.01852407e-01f, 9.39957463e-01f, 9.79963735e-01f, 1.02204672e+00f, 1.06639858e+00f,
+        1.11322974e+00f, 1.16277062e+00f, 1.21527359e+00f, 1.27101525e+00f, 1.33029891e+00f, 1.39345744e+00f,
+        1.46085648e+00f, 1.53289803e+00f, 1.61002461e+00f, 1.69272386e+00f, 1.78153384e+00f, 1.87704900e+00f,
+        1.97992701e+00f, 2.09089644e+00f, 2.21076567e+00f, 2.34043290e+00f, 2.48089770e+00f, 2.63327413e+00f,
+        2.79880590e+00f, 2.97888368e+00f, 3.17506505e+00f, 3.38909744e+00f, 3.62294469e+00f, 3.87881764e+00f,
+        4.15920968e+00f, 4.46693789e+00f, 4.80519096e+00f, 5.17758497e+00f, 5.58822853e+00f, 6.04179895e+00f,
+        6.54363157e+00f, 7.09982467e+00f, 7.71736306e+00f, 8.40426388e+00f, 9.16974906e+00f, 1.00244499e+01f,
+        1.09806502e+01f, 1.20525758e+01f, 1.32567410e+01f, 1.46123627e+01f, 1.61418586e+01f, 1.78714466e+01f,
+        1.98318690e+01f, 2.20592694e+01f, 2.45962577e+01f, 2.74932084e+01f, 3.08098460e+01f, 3.46171893e+01f,
+        3.89999428e+01f, 4.40594471e+01f, 4.99173320e+01f, 5.67200545e+01f, 6.46445583e+01f, 7.39053537e+01f,
+        8.47634121e+01f, 9.75373786e+01f, 1.12617765e+02f, 1.30484989e+02f, 1.51732386e+02f, 1.77095712e+02f,
+        2.07491096e+02f, 2.44064119e+02f, 2.88253545e+02f, 3.41874461e+02f, 4.07227291e+02f, 4.87241400e+02f,
+        5.85665251e+02f, 7.07319497e+02f, 8.58435639e+02f, 1.04711167e+03f, 1.28392853e+03f, 1.58278901e+03f,
+        1.96206607e+03f, 2.44618436e+03f, 3.06781187e+03f, 3.87091688e+03f, 4.91505977e+03f, 6.28145970e+03f,
+        8.08162997e+03f, 1.04697579e+04f, 1.36605846e+04f, 1.79554230e+04f, 2.37803156e+04f, 3.17424455e+04f,
+        4.27142204e+04f, 5.79596727e+04f, 7.93261335e+04f, 1.09537503e+05f, 1.52647130e+05f, 2.14743829e+05f,
+        3.05063335e+05f, 4.37755687e+05f, 6.34724899e+05f, 9.30240305e+05f, 1.37850753e+06f, 2.06623977e+06f,
+        3.13377596e+06f, 4.81098405e+06f, 7.47905793e+06f, 1.17782423e+07f, 1.87980927e+07f, 3.04180655e+07f,
+        4.99257437e+07f, 8.31551852e+07f, 1.40614107e+08f, 2.41519712e+08f, 4.21576502e+08f, 7.48209440e+08f,
+        1.35089892e+09f, 2.48263348e+09f, 4.64662007e+09f, 8.86235204e+09f, 1.72348930e+10f, 3.41967381e+10f,
+        6.92714904e+10f, 1.43352142e+11f, 3.03269524e+11f, 6.56345865e+11f, 1.45422052e+12f, 3.30099910e+12f,
+        7.68267630e+12f, 1.83474885e+13f, 4.49980389e+13f, 1.13430702e+14f, 2.94148450e+14f, 7.85402504e+14f,
+        2.16127995e+15f, 6.13534293e+15f, 1.79847736e+16f, 5.44944507e+16f, 1.70858922e+17f, 5.54922744e+17f,
+        1.86905990e+18f, 6.53599225e+18f, 2.37582887e+19f, 8.98810682e+19f, 3.54341330e+20f, };
+
+__constant__ float m_weights_float_8[527] = 
+      { 2.67108015e-21f, 5.82833463e-21f, 1.25616316e-20f, 2.67469785e-20f, 5.62745845e-20f, 1.17014394e-19f, 
+        2.40511019e-19f, 4.88739481e-19f, 9.82072303e-19f, 1.95168062e-18f, 3.83661097e-18f, 7.46163208e-18f,
+        1.43594942e-17f, 2.73485792e-17f, 5.15573612e-17f, 9.62223075e-17f, 1.77810682e-16f, 3.25389618e-16f,
+        5.89765054e-16f, 1.05888451e-15f, 1.88354538e-15f, 3.31989417e-15f, 5.79902273e-15f, 1.00398818e-14f,
+        1.72308010e-14f, 2.93186753e-14f, 4.94655967e-14f, 8.27635884e-14f, 1.37343706e-13f, 2.26082511e-13f,
+        3.69205736e-13f, 5.98228147e-13f, 9.61866975e-13f, 1.53484658e-12f, 2.43090464e-12f, 3.82185577e-12f,
+        5.96531965e-12f, 9.24474797e-12f, 1.42267754e-11f, 2.17427910e-11f, 3.30041201e-11f, 4.97635091e-11f,
+        7.45399354e-11f, 1.10929412e-10f, 1.64031748e-10f, 2.41032586e-10f, 3.51991946e-10f, 5.10905560e-10f,
+        7.37124150e-10f, 1.05723929e-09f, 1.50757352e-09f, 2.13744796e-09f, 3.01344401e-09f, 4.22492806e-09f,
+        5.89117093e-09f, 8.17046854e-09f, 1.12717587e-08f, 1.54693324e-08f, 2.11213594e-08f, 2.86930859e-08f,
+        3.87857241e-08f, 5.21722335e-08f, 6.98414017e-08f, 9.30518593e-08f, 1.23397923e-07f, 1.62889442e-07f,
+        2.14048123e-07f, 2.80023159e-07f, 3.64729321e-07f, 4.73011070e-07f, 6.10836627e-07f, 7.85526363e-07f,
+        1.00602028e-06f, 1.28318979e-06f, 1.63019938e-06f, 2.06292424e-06f, 2.60043021e-06f, 3.26552286e-06f,
+        4.08537275e-06f, 5.09222413e-06f, 6.32419483e-06f, 7.82617466e-06f, 9.65083023e-06f, 1.18597236e-05f,
+        1.45245521e-05f, 1.77285168e-05f, 2.15678251e-05f, 2.61533347e-05f, 3.16123436e-05f, 3.80905295e-05f,
+        4.57540432e-05f, 5.47917575e-05f, 6.54176707e-05f, 7.78734661e-05f, 9.24312223e-05f, 1.09396271e-04f,
+        1.29110197e-04f, 1.51953965e-04f, 1.78351176e-04f, 2.08771424e-04f, 2.43733750e-04f, 2.83810168e-04f,
+        3.29629253e-04f, 3.81879756e-04f, 4.41314233e-04f, 5.08752659e-04f, 5.85085996e-04f, 6.71279692e-04f,
+        7.68377076e-04f, 8.77502620e-04f, 9.99865030e-04f, 1.13676015e-03f, 1.28957360e-03f, 1.45978322e-03f,
+        1.64896113e-03f, 1.85877551e-03f, 2.09099200e-03f, 2.34747474e-03f, 2.63018699e-03f, 2.94119122e-03f,
+        3.28264890e-03f, 3.65681963e-03f, 4.06605991e-03f, 4.51282135e-03f, 4.99964828e-03f, 5.52917497e-03f,
+        6.10412222e-03f, 6.72729343e-03f, 7.40157020e-03f, 8.12990738e-03f, 8.91532760e-03f, 9.76091537e-03f,
+        1.06698107e-02f, 1.16452023e-02f, 1.26903202e-02f, 1.38084285e-02f, 1.50028172e-02f, 1.62767940e-02f,
+        1.76336759e-02f, 1.90767806e-02f, 2.06094173e-02f, 2.22348784e-02f, 2.39564300e-02f, 2.57773028e-02f,
+        2.77006834e-02f, 2.97297055e-02f, 3.18674406e-02f, 3.41168899e-02f, 3.64809756e-02f, 3.89625331e-02f,
+        4.15643030e-02f, 4.42889240e-02f, 4.71389254e-02f, 5.01167213e-02f, 5.32246039e-02f, 5.64647382e-02f,
+        5.98391571e-02f, 6.33497571e-02f, 6.69982939e-02f, 7.07863800e-02f, 7.47154815e-02f, 7.87869165e-02f,
+        8.30018539e-02f, 8.73613125e-02f, 9.18661613e-02f, 9.65171203e-02f, 1.01314762e-01f, 1.06259513e-01f,
+        1.11351656e-01f, 1.16591337e-01f, 1.21978563e-01f, 1.27513213e-01f, 1.33195039e-01f, 1.39023671e-01f,
+        1.44998628e-01f, 1.51119321e-01f, 1.57385061e-01f, 1.63795066e-01f, 1.70348473e-01f, 1.77044340e-01f,
+        1.83881662e-01f, 1.90859375e-01f, 1.97976367e-01f, 2.05231492e-01f, 2.12623572e-01f, 2.20151415e-01f,
+        2.27813822e-01f, 2.35609599e-01f, 2.43537565e-01f, 2.51596569e-01f, 2.59785494e-01f, 2.68103274e-01f,
+        2.76548903e-01f, 2.85121445e-01f, 2.93820047e-01f, 3.02643950e-01f, 3.11592502e-01f, 3.20665165e-01f,
+        3.29861530e-01f, 3.39181328e-01f, 3.48624439e-01f, 3.58190905e-01f, 3.67880941e-01f, 3.77694943e-01f,
+        3.87633504e-01f, 3.97697421e-01f, 4.07887708e-01f, 4.18205605e-01f, 4.28652591e-01f, 4.39230391e-01f,
+        4.49940993e-01f, 4.60786652e-01f, 4.71769905e-01f, 4.82893580e-01f, 4.94160809e-01f, 5.05575036e-01f,
+        5.17140031e-01f, 5.28859900e-01f, 5.40739096e-01f, 5.52782432e-01f, 5.64995090e-01f, 5.77382639e-01f,
+        5.89951040e-01f, 6.02706666e-01f, 6.15656310e-01f, 6.28807202e-01f, 6.42167019e-01f, 6.55743908e-01f,
+        6.69546490e-01f, 6.83583887e-01f, 6.97865729e-01f, 7.12402181e-01f, 7.27203953e-01f, 7.42282322e-01f,
+        7.57649155e-01f, 7.73316926e-01f, 7.89298740e-01f, 8.05608358e-01f, 8.22260217e-01f, 8.39269463e-01f,
+        8.56651970e-01f, 8.74424378e-01f, 8.92604116e-01f, 9.11209442e-01f, 9.30259469e-01f, 9.49774208e-01f,
+        9.69774604e-01f, 9.90282579e-01f, 1.01132107e+00f, 1.03291408e+00f, 1.05508673e+00f, 1.07786529e+00f,
+        1.10127728e+00f, 1.12535146e+00f, 1.15011796e+00f, 1.17560829e+00f, 1.20185546e+00f, 1.22889400e+00f,
+        1.25676010e+00f, 1.28549162e+00f, 1.31512826e+00f, 1.34571158e+00f, 1.37728514e+00f, 1.40989460e+00f,
+        1.44358784e+00f, 1.47841507e+00f, 1.51442894e+00f, 1.55168471e+00f, 1.59024039e+00f, 1.63015687e+00f,
+        1.67149810e+00f, 1.71433126e+00f, 1.75872698e+00f, 1.80475947e+00f, 1.85250679e+00f, 1.90205105e+00f,
+        1.95347869e+00f, 2.00688065e+00f, 2.06235275e+00f, 2.11999592e+00f, 2.17991652e+00f, 2.24222670e+00f,
+        2.30704472e+00f, 2.37449538e+00f, 2.44471039e+00f, 2.51782884e+00f, 2.59399766e+00f, 2.67337209e+00f,
+        2.75611628e+00f, 2.84240383e+00f, 2.93241843e+00f, 3.02635449e+00f, 3.12441791e+00f, 3.22682682e+00f,
+        3.33381238e+00f, 3.44561973e+00f, 3.56250887e+00f, 3.68475574e+00f, 3.81265333e+00f, 3.94651282e+00f,
+        4.08666490e+00f, 4.23346116e+00f, 4.38727553e+00f, 4.54850596e+00f, 4.71757611e+00f, 4.89493722e+00f,
+        5.08107015e+00f, 5.27648761e+00f, 5.48173646e+00f, 5.69740032e+00f, 5.92410235e+00f, 6.16250823e+00f,
+        6.41332946e+00f, 6.67732689e+00f, 6.95531455e+00f, 7.24816384e+00f, 7.55680807e+00f, 7.88224735e+00f,
+        8.22555401e+00f, 8.58787841e+00f, 8.97045530e+00f, 9.37461076e+00f, 9.80176975e+00f, 1.02534643e+01f,
+        1.07313428e+01f, 1.12371793e+01f, 1.17728848e+01f, 1.23405187e+01f, 1.29423019e+01f, 1.35806306e+01f,
+        1.42580922e+01f, 1.49774818e+01f, 1.57418213e+01f, 1.65543795e+01f, 1.74186947e+01f, 1.83385994e+01f,
+        1.93182476e+01f, 2.03621450e+01f, 2.14751816e+01f, 2.26626686e+01f, 2.39303784e+01f, 2.52845893e+01f,
+        2.67321348e+01f, 2.82804577e+01f, 2.99376708e+01f, 3.17126238e+01f, 3.36149769e+01f, 3.56552840e+01f,
+        3.78450835e+01f, 4.01970005e+01f, 4.27248599e+01f, 4.54438126e+01f, 4.83704762e+01f, 5.15230921e+01f,
+        5.49217006e+01f, 5.85883374e+01f, 6.25472527e+01f, 6.68251567e+01f, 7.14514957e+01f, 7.64587609e+01f,
+        8.18828353e+01f, 8.77633847e+01f, 9.41442967e+01f, 1.01074176e+02f, 1.08606902e+02f, 1.16802259e+02f,
+        1.25726650e+02f, 1.35453899e+02f, 1.46066166e+02f, 1.57654979e+02f, 1.70322410e+02f, 1.84182406e+02f,
+        1.99362306e+02f, 2.16004568e+02f, 2.34268740e+02f, 2.54333703e+02f, 2.76400239e+02f, 3.00693971e+02f,
+        3.27468728e+02f, 3.57010397e+02f, 3.89641362e+02f, 4.25725590e+02f, 4.65674502e+02f, 5.09953726e+02f,
+        5.59090900e+02f, 6.13684688e+02f, 6.74415211e+02f, 7.42056139e+02f, 8.17488717e+02f, 9.01718069e+02f,
+        9.95892168e+02f, 1.10132394e+03f, 1.21951707e+03f, 1.35219615e+03f, 1.50134197e+03f, 1.66923291e+03f,
+        1.85849349e+03f, 2.07215152e+03f, 2.31370536e+03f, 2.58720328e+03f, 2.89733724e+03f, 3.24955383e+03f,
+        3.65018587e+03f, 4.10660860e+03f, 4.62742547e+03f, 5.22268956e+03f, 5.90416786e+03f, 6.68565726e+03f,
+        7.58336313e+03f, 8.61635357e+03f, 9.80710572e+03f, 1.11821637e+04f, 1.27729327e+04f, 1.46166396e+04f,
+        1.67574960e+04f, 1.92481112e+04f, 2.21512104e+04f, 2.55417295e+04f, 2.95093735e+04f, 3.41617487e+04f,
+        3.96282043e+04f, 4.60645561e+04f, 5.36589049e+04f, 6.26388223e+04f, 7.32802431e+04f, 8.59184957e+04f,
+        1.00962017e+05f, 1.18909442e+05f, 1.40370957e+05f, 1.66095034e+05f, 1.97001996e+05f, 2.34226253e+05f,
+        2.79169596e+05f, 3.33568603e+05f, 3.99580125e+05f, 4.79889989e+05f, 5.77851588e+05f, 6.97663062e+05f,
+        8.44594440e+05f, 1.02527965e+06f, 1.24809298e+06f, 1.52363581e+06f, 1.86536786e+06f, 2.29042802e+06f,
+        2.82070529e+06f, 3.48424008e+06f, 4.31706343e+06f, 5.36561882e+06f, 6.68996113e+06f, 8.36799594e+06f,
+        1.05011160e+07f, 1.32217203e+07f, 1.67032788e+07f, 2.11738506e+07f, 2.69343047e+07f, 3.43829654e+07f,
+        4.40490690e+07f, 5.66383460e+07f, 7.30953564e+07f, 9.46890531e+07f, 1.23130681e+08f, 1.60736861e+08f,
+        2.10656057e+08f, 2.77184338e+08f, 3.66207397e+08f, 4.85821891e+08f, 6.47212479e+08f, 8.65895044e+08f,
+        1.16348659e+09f, 1.57023596e+09f, 2.12865840e+09f, 2.89877917e+09f, 3.96573294e+09f, 5.45082863e+09f,
+        7.52773593e+09f, 1.04462776e+10f, 1.45675716e+10f, 2.04161928e+10f, 2.87579864e+10f, 4.07167363e+10f,
+        5.79499965e+10f, 8.29154750e+10f, 1.19276754e+11f, 1.72524570e+11f, 2.50933409e+11f, 3.67042596e+11f,
+        5.39962441e+11f, 7.98985690e+11f, 1.18927611e+12f, 1.78088199e+12f, 2.68310388e+12f, 4.06753710e+12f,
+        6.20525592e+12f, 9.52719664e+12f, 1.47228407e+13f, 2.29025392e+13f, 3.58662837e+13f, 5.65517100e+13f,
+        8.97859411e+13f, 1.43556057e+14f, 2.31171020e+14f, 3.74966777e+14f, 6.12702071e+14f, 1.00868013e+15f,
+        1.67323268e+15f, 2.79711270e+15f, 4.71267150e+15f, 8.00353033e+15f, 1.37027503e+16f, 2.36538022e+16f,
+        4.11734705e+16f, 7.22793757e+16f, 1.27982244e+17f, 2.28603237e+17f, 4.11976277e+17f, 7.49169358e+17f,
+        1.37488861e+18f, 2.54681529e+18f, 4.76248383e+18f, 8.99167123e+18f, 1.71428840e+19f, 3.30088717e+19f,
+        6.42020070e+19f, 1.26155602e+20f, 2.50480806e+20f, 5.02601059e+20f, 1.01935525e+21f, };
+
+__constant__ float* m_weights_float[8] = {
+    m_weights_float_1,
+    m_weights_float_2,
+    m_weights_float_3,
+    m_weights_float_4,
+    m_weights_float_5,
+    m_weights_float_6,
+    m_weights_float_7,
+    m_weights_float_8
+};
+
+__constant__ double m_abscissas_double_1[13] =
+      { 7.241670621354483269e-163, 2.257639733856759198e-60, 1.153241619257215165e-22, 8.747691973876861825e-09, 
+        1.173446923800022477e-03, 1.032756936219208144e-01, 7.719261204224504866e-01, 4.355544675823585545e+00,
+        1.215101039066652656e+02, 6.228845436711506169e+05, 6.278613977336989392e+15, 9.127414935180233465e+42, 
+        6.091127771174027909e+116, };
+
+__constant__ double m_abscissas_double_2[12] =
+      { 4.547459836328942014e-99, 6.678756542928857080e-37, 5.005042973041566360e-14, 1.341318484151208960e-05, 
+        1.833875636365939263e-02, 3.257972971286326131e-01, 1.712014688483495078e+00, 1.613222549264089627e+01, 
+        3.116246745274236447e+03, 3.751603952020919663e+09, 1.132259067258797346e+26, 6.799257464097374238e+70, };
+
+__constant__ double m_abscissas_double_3[25] =
+      { 5.314690663257815465e-127, 2.579830034615362946e-77, 3.534801062399966878e-47, 6.733941646704537777e-29, 
+        8.265803726974829043e-18, 4.424914371157762285e-11, 5.390411046738629465e-07, 1.649389713333761449e-04, 
+        5.463728936866216652e-03, 4.787896410534771955e-02, 1.931544616590306846e-01, 5.121421856617965197e-01, 
+        1.144715949265016019e+00, 2.648424684387670480e+00, 7.856804169938798917e+00, 3.944731803343517708e+01, 
+        5.060291993016831194e+02, 3.181117494063683297e+04, 2.820174654949211729e+07, 1.993745099515255184e+12, 
+        1.943469269499068563e+20, 2.858803732300638372e+33, 1.457292199029008637e+55, 8.943565831706355607e+90,
+        9.016198369791554655e+149, };
+
+__constant__ double m_abscissas_double_4[49] =
+      { 8.165631636299519857e-144, 3.658949309353149331e-112, 1.635242513882908826e-87, 2.578381184977746454e-68,
+        2.305546416275824199e-53, 1.016725540031465162e-41, 1.191823622917539774e-32, 1.379018088205016509e-25, 
+        4.375640088826073184e-20, 8.438464631330991606e-16, 1.838483310261119782e-12, 7.334264181393092650e-10, 
+        7.804740587931068021e-08, 2.970395577741681504e-06, 5.081805431666579484e-05, 4.671401627620431498e-04, 
+        2.652347404231090523e-03, 1.037409202661683856e-02, 3.045225582205323946e-02, 7.178280364982721201e-02, 
+        1.434001065841990688e-01, 2.535640852949085796e-01, 4.113268917643175920e-01, 6.310260805648534613e-01,
+        9.404706503455087817e-01, 1.396267301972783068e+00, 2.116896928689963277e+00, 3.364289290471596568e+00,
+        5.770183960005836987e+00, 1.104863531218761752e+01, 2.460224479439805859e+01, 6.699316387888639988e+01,
+        2.375794092475844708e+02, 1.188092202760116066e+03, 9.269848635975416108e+03, 1.283900116155671304e+05,
+        3.723397798030112514e+06, 2.793667983952389721e+08, 7.112973790863854188e+10, 8.704037695808749572e+13,
+        8.001474015782459984e+17, 9.804091819390540578e+22, 3.342777673392873288e+29, 8.160092668471508447e+37,
+        4.798775331663586528e+48, 3.228614320248853938e+62, 1.836986041572136151e+80, 1.153145986877483804e+103,
+        2.160972586723647751e+132, };
+
+__constant__ double m_abscissas_double_5[98] =
+      { 4.825077401709435655e-153, 3.813781211050297560e-135, 2.377824349780240844e-119, 2.065817295388293122e-105,
+        4.132105770181358886e-93, 2.963965169989404311e-82, 1.127296662046635391e-72, 3.210346399945695041e-64,
+        9.282992368222161062e-57, 3.565977853916619677e-50, 2.306962519220473637e-44, 3.098751038516535098e-39,
+        1.039558064722960891e-34, 1.025256027381235200e-30, 3.432612000569885403e-27, 4.429681881379089961e-24,
+        2.464589267395236846e-21, 6.526691446363344923e-19, 8.976892324445928684e-17, 6.926277695183452225e-15,
+        3.208805316815751272e-13, 9.478053068835988899e-12, 1.882052586691155400e-10, 2.632616062773909009e-09,
+        2.703411837703917665e-08, 2.113642195965330965e-07, 1.299327029813074013e-06, 6.461189935136030673e-06,
+        2.665090959570723827e-05, 9.322774986189288194e-05, 2.820463407940068813e-04, 7.508613300035051413e-04,
+        1.786142185986551786e-03, 3.848376610765768211e-03, 7.600810651854199771e-03, 1.390873269178271700e-02,
+        2.380489559528694982e-02, 3.842796337748997654e-02, 5.895012901671883992e-02, 8.651391160689367948e-02,
+        1.221961347398101671e-01, 1.670112314557845555e-01, 2.219593619059930701e-01, 2.881200442770917241e-01,
+        3.667906976948184315e-01, 4.596722879563388211e-01, 5.691113093602836208e-01, 6.984190600916228379e-01,
+        8.523070690462583711e-01, 1.037505121571600249e+00, 1.263672635742961915e+00, 1.544788480334120896e+00,
+        1.901333876886441433e+00, 2.363816272813317635e+00, 2.978614980117902904e+00, 3.817957977526709364e+00,
+        4.997477803461245639e+00, 6.708150685706236545e+00, 9.276566033183386532e+00, 1.328332469239125539e+01,
+        1.980618680552458639e+01, 3.094452809319702849e+01, 5.101378787119006225e+01, 8.943523638413590523e+01,
+        1.682138665185088325e+02, 3.427988270281270587e+02, 7.653823671943767281e+02, 1.895993667030670343e+03,
+        5.285404568827643942e+03, 1.684878049282191210e+04, 6.254388805482299369e+04, 2.759556544455721132e+05,
+        1.481213238071008345e+06, 9.929728611179601424e+06, 8.564987764771851841e+07, 9.831650826344826952e+08,
+        1.560339073978569502e+10, 3.575098885016726922e+11, 1.241973798101884982e+13, 6.915106205748805839e+14,
+        6.571419716645131084e+16, 1.144558033138694099e+19, 3.960915669532823553e+21, 2.984410558028297842e+24,
+        5.430494850258846715e+27, 2.683747612498502676e+31, 4.114885708325522701e+35, 2.276004816861421600e+40,
+        5.387544917595833246e+45, 6.623575732955432303e+51, 5.266881304835239338e+58, 3.473234812654772210e+66,
+        2.517492645985977377e+75, 2.759797646289240629e+85, 6.569603829502412077e+96, 5.116181648220647995e+109,
+        2.073901892339407423e+124, 7.406462446666255838e+140, };
+
+__constant__ double m_abscissas_double_6[196] =
+      { 7.053618140948655098e-158, 2.343354218558056628e-148, 2.062509087689351439e-139, 5.212388628332260488e-131,
+        4.079380320868843387e-123, 1.061481285006738214e-115, 9.816727607793017691e-109, 3.435400719609722581e-102,
+        4.825198574681495574e-96, 2.874760995089533358e-90, 7.652499977338879996e-85, 9.556944498127119032e-80, 
+        5.862241023038227937e-75, 1.843934000129616663e-70, 3.096983980846232911e-66, 2.885057452402340330e-62,
+        1.544904681826443837e-58, 4.917572705671511534e-55, 9.602608566391652866e-52, 1.184882375237471009e-48,
+        9.499223316355714793e-46, 5.078965858882528461e-43, 1.856080838373584123e-40, 4.744245560917271585e-38,
+        8.667497891102658240e-36, 1.155086178652063612e-33, 1.144541329818836153e-31, 8.585083084065812874e-30,
+        4.957702933032408922e-28, 2.239353794616277882e-26, 8.030405447708765492e-25, 2.318459271131684362e-23,
+        5.460287296679086677e-22, 1.062054307071706375e-20, 1.725955878033239909e-19, 2.369168446274347137e-18,
+        2.775176063916613602e-17, 2.800847352316621903e-16, 2.457625954357892245e-15, 1.890842052364646528e-14,
+        1.285791209258834942e-13, 7.786001004707878219e-13, 4.228083024410741194e-12, 2.072664297543567489e-11,
+        9.229295073519997559e-11, 3.754886152592311575e-10, 1.403443871774813834e-09, 4.843962757371872495e-09,
+        1.551373196623161433e-08, 4.631448362339623514e-08, 1.294370176865168120e-07, 3.400050664017164356e-07,
+        8.426290307581447654e-07, 1.977205177561996033e-06, 4.407362363338667830e-06, 9.362197325373404563e-06,
+        1.900760383449277992e-05, 3.698530963711860636e-05, 6.915333419235766653e-05, 1.245492076251852927e-04,
+        2.165764713808099093e-04, 3.643870211078977292e-04, 5.943999416122372516e-04, 9.418663022314558591e-04,
+        1.452364274261880083e-03, 2.183094846035196562e-03, 3.203848855069215278e-03, 4.597532353031862490e-03,
+        6.460168315117479792e-03, 8.900334989802041559e-03, 1.203804973137064275e-02, 1.600315622064554965e-02,
+        2.093331703849583304e-02, 2.697174812170771748e-02, 3.426485378063329473e-02, 4.295992956149806344e-02,
+        5.320309587203163231e-02, 6.513760993479510261e-02, 7.890268021756337834e-02, 9.463287940877026649e-02,
+        1.124582226719385153e-01, 1.325049504086213973e-01, 1.548970316076579260e-01, 1.797583869192584860e-01,
+        2.072158210677632145e-01, 2.374026527414815016e-01, 2.704630368855767324e-01, 3.065569893452247137e-01,
+        3.458661469783558388e-01, 3.886003277325320632e-01, 4.350049951304795319e-01, 4.853697810067132707e-01,
+        5.400382807495678589e-01, 5.994194092045578293e-01, 6.640006964388650918e-01, 7.343640159321037167e-01,
+        8.112043806284638130e-01, 8.953526245122194172e-01, 9.878030224123093447e-01, 1.089747207002141516e+00,
+        1.202616144679226559e+00, 1.328132465995424226e+00, 1.468376159872979355e+00, 1.625867601500928277e+00,
+        1.803673186618691186e+00, 2.005540624723209206e+00, 2.236073393446881709e+00, 2.500957254018255004e+00,
+        2.807256477663534857e+00, 3.163804128101147487e+00, 3.581720263742550029e+00, 4.075105576391566303e+00,
+        4.661977749936137761e+00, 5.365546718714963091e+00, 6.215967676434536043e+00, 7.252774367330402583e+00,
+        8.528291278204291331e+00, 1.011247001122720391e+01, 1.209982167952718578e+01, 1.461947158782994207e+01,
+        1.784992423404041042e+01, 2.204102944968352178e+01, 2.754711235628932374e+01, 3.487766600641650640e+01,
+        4.477610230214251576e+01, 5.834406132739843834e+01, 7.724096630394042216e+01, 1.040101075374387191e+02,
+        1.426215523101601730e+02, 1.993940974645466479e+02, 2.845939167898235356e+02, 4.152683836292551147e+02,
+        6.203878718481709769e+02, 9.504080873581791535e+02, 1.495523342124078853e+03, 2.421485328006836634e+03,
+        4.041977218227396500e+03, 6.969453497454785202e+03, 1.244001690461442846e+04, 2.303794930506892099e+04,
+        4.437240927040385250e+04, 8.911296561746717657e+04, 1.871159398849787994e+05, 4.119851492265743330e+05,
+        9.540971729944126398e+05, 2.331680521880789706e+06, 6.034305391011695472e+06, 1.659896369452266448e+07,
+        4.872448839341613053e+07, 1.532687586549090392e+08, 5.189730792935011722e+08, 1.900599621040508288e+09,
+        7.566480431232731818e+09, 3.292298322781643849e+10, 1.574714421665075635e+11, 8.330244306239795892e+11,
+        4.905619969814187571e+12, 3.238316002757222702e+13, 2.413995281454699076e+14, 2.048115587426077343e+15,
+        1.994352670766892066e+16, 2.248750566422739144e+17, 2.964037541992353401e+18, 4.613233119968213445e+19,
+        8.569680508342001161e+20, 1.921851711942844799e+22, 5.266829246099861758e+23, 1.786779952992288976e+25,
+        7.607919705736976491e+26, 4.125721424346450007e+28, 2.894340142292214313e+30, 2.670720269656428272e+32,
+        3.299248229135205151e+34, 5.560105583582310103e+36, 1.304167266599523020e+39, 4.349382146382717353e+41,
+        2.109720387774341509e+44, 1.524825352702403324e+47, 1.684941265105084589e+50, 2.925572737558413426e+53,
+        8.217834961057481281e+56, 3.852117991896536784e+60, 3.114452310394384063e+64, 4.498555465873245751e+68,
+        1.205113215232800796e+73, 6.230864727145221322e+77, 6.487131248948465269e+82, 1.422810109167834249e+88,
+        6.897656089181724717e+93, 7.779163462756485195e+99, 2.155213251859555072e+106, 1.554347160152705281e+113,
+        3.103875072425192272e+120, 1.832673821557018634e+128, 3.431285951865278376e+136, 2.194542081542393530e+145, };
+
+__constant__ double m_abscissas_double_7[393] =
+      { 2.363803632659058081e-160, 1.926835442612677686e-155, 1.109114905180506786e-150, 4.556759282087534164e-146,
+        1.350172241067816232e-141, 2.914359263635229435e-137, 4.627545976953585825e-133, 5.456508344460398758e-129,
+        4.821828861306345485e-125, 3.221779152402086241e-121, 1.641732102111619421e-117, 6.433569189921227126e-114,
+        1.954582672700428961e-110, 4.639912078942456372e-107, 8.671928891742699827e-104, 1.285485264305858782e-100,
+        1.522161801460927566e-97, 1.449767844425295085e-94, 1.118122255504445235e-91, 7.028344777398825069e-89,
+        3.623454064991238081e-86, 1.541513438874996543e-83, 5.443699502170284982e-81, 1.604913673768949456e-78,
+        3.972206240977317536e-76, 8.297975554162539562e-74, 1.470748835855054032e-71, 2.222935801472624670e-69,
+        2.879160361851977720e-67, 3.210837413250902178e-65, 3.097303984958235490e-63, 2.595974479763180595e-61,
+        1.898656799199089593e-59, 1.216865518398435626e-57, 6.862041810601184397e-56, 3.418134121780773218e-54,
+        1.509758535747580387e-52, 5.934924977563731784e-51, 2.083865009061241099e-49, 6.558128104492290092e-48,
+        1.856133016606468181e-46, 4.739964621828176249e-45, 1.095600459825324697e-43, 2.299177139060262518e-42,
+        4.393663812095906869e-41, 7.667728102142858487e-40, 1.225476279042445010e-38, 1.798526997315960782e-37,
+        2.430201154741018716e-36, 3.030993518975438712e-35, 3.497966609954172613e-34, 3.744308272796551045e-33,
+        3.726132797819332658e-32, 3.455018936399215381e-31, 2.991524108706319604e-30, 2.423818520801870809e-29,
+        1.841452809687011486e-28, 1.314419760826235421e-27, 8.831901010260867670e-27, 5.596660060604091621e-26,
+        3.350745417080507841e-25, 1.898675566025820409e-24, 1.019982287418197376e-23, 5.203315082978366918e-23,
+        2.524668746906057148e-22, 1.166904646009344233e-21, 5.145437675264868732e-21, 2.167677145279166596e-20,
+        8.736996911006110678e-20, 3.373776431076593266e-19, 1.249769727462160008e-18, 4.446913832647864892e-18,
+        1.521741180930875343e-17, 5.014158301377399707e-17, 1.592708205361177316e-16, 4.882536933653862982e-16,
+        1.446109387544416586e-15, 4.142510168443201880e-15, 1.148892083132325407e-14, 3.088024760858924214e-14,
+        8.051699653634442236e-14, 2.038478329249539199e-13, 5.015686309363884049e-13, 1.200444984849900298e-12,
+        2.797125428309156462e-12, 6.350357793399881333e-12, 1.405881744263466936e-11, 3.037391821635123795e-11,
+        6.408863411016101449e-11, 1.321618431565916164e-10, 2.665526566207284474e-10, 5.261497418654313068e-10,
+        1.017123184766088896e-09, 1.926882221639203388e-09, 3.579523428497157488e-09, 6.524486847652635035e-09,
+        1.167543991262942921e-08, 2.052356080018121741e-08, 3.545879678923676129e-08, 6.024472481556065885e-08,
+        1.007076869023518125e-07, 1.657191565891799652e-07, 2.685718943404479677e-07, 4.288752213761154116e-07,
+        6.751222405372943925e-07, 1.048111270324302884e-06, 1.605433960692314060e-06, 2.427271958412371013e-06,
+        3.623770645356477660e-06, 5.344280132492750309e-06, 7.788767891027678939e-06, 1.122171160022519082e-05,
+        1.598877254198599908e-05, 2.253652700952153115e-05, 3.143549403208496646e-05, 4.340664122305257288e-05,
+        5.935147653125578529e-05, 8.038574285450253209e-05, 1.078766266062957565e-04, 1.434832731669987826e-04,
+        1.892002753957224677e-04, 2.474036705329449166e-04, 3.208988510028906069e-04, 4.129696713145546995e-04,
+        5.274279220384250390e-04, 6.686622480794640482e-04, 8.416855170641220285e-04, 1.052179598744440400e-03,
+        1.306536501050643762e-03, 1.611894824798787196e-03, 1.976170547826080496e-03, 2.408081229927640721e-03,
+        2.917162840577481875e-03, 3.513778549028205519e-03, 4.209118976964403112e-03, 5.015193592567630665e-03,
+        5.944813116164644191e-03, 7.011563005746090924e-03, 8.229768289624073049e-03, 9.614450207543986041e-03,
+        1.118127530523730813e-02, 1.294649779580742160e-02, 1.492689615029751590e-02, 1.713970500593860526e-02,
+        1.960254358145296755e-02, 2.233334186285684056e-02, 2.535026586984720664e-02, 2.867164333232700310e-02,
+        3.231589109997912964e-02, 3.630144557680610965e-02, 4.064669741956638109e-02, 4.536993166688766414e-02,
+        5.048927437769432941e-02, 5.602264675683979161e-02, 6.198772763597769678e-02, 6.840192506222012774e-02,
+        7.528235762939712171e-02, 8.264584606994605986e-02, 9.050891551257121825e-02, 9.888780870447738360e-02,
+        1.077985103995250356e-01, 1.172567830270636607e-01, 1.272782136821146663e-01, 1.378782724173011162e-01,
+        1.490723817714478840e-01, 1.608759974398061173e-01, 1.733046999768424060e-01, 1.863742974247175786e-01,
+        2.001009387790379976e-01, 2.145012382381487190e-01, 2.295924102330349785e-01, 2.453924153016625057e-01,
+        2.619201169541956490e-01, 2.791954497739298773e-01, 2.972395991130188526e-01, 3.160751928723792943e-01,
+        3.357265060019327741e-01, 3.562196785212496373e-01, 3.775829480426418792e-01, 3.998468979800887046e-01,
+        4.230447228497335035e-01, 4.472125123131631074e-01, 4.723895558858634018e-01, 4.986186705332947608e-01,
+        5.259465537097384485e-01, 5.544241647649479754e-01, 5.841071380560416511e-01, 6.150562315632864018e-01,
+        6.473378153258308278e-01, 6.810244045956889952e-01, 7.161952432654565143e-01, 7.529369438691556459e-01,
+        7.913441913000366617e-01, 8.315205183502086596e-01, 8.735791622734589226e-01, 9.176440128265773576e-01,
+        9.638506636817484398e-01, 1.012347580753402101e+00, 1.063297402882930381e+00, 1.116878392515788506e+00,
+        1.173286056537125469e+00, 1.232734960362603918e+00, 1.295460761779549539e+00, 1.361722494981910846e+00,
+        1.431805139837984876e+00, 1.506022516788234345e+00, 1.584720554029819354e+00, 1.668280980969603645e+00,
+        1.757125510515793421e+00, 1.851720582866847453e+00, 1.952582755329533200e+00, 2.060284836698905963e+00,
+        2.175462881275503983e+00, 2.298824177179966629e+00, 2.431156386859774759e+00, 2.573338025304717222e+00,
+        2.726350494395667363e+00, 2.891291931102408784e+00, 3.069393174263124520e+00, 3.262036211067640944e+00,
+        3.470775532153801919e+00, 3.697362905908153155e+00, 3.943776181224350319e+00, 4.212252847439515687e+00,
+        4.505329225191826639e+00, 4.825886338442190807e+00, 5.177203733275742875e+00, 5.563022772612923373e+00,
+        5.987621259260909859e+00, 6.455901637501497370e+00, 6.973495514195020291e+00, 7.546887847708181032e+00,
+        8.183564906772872855e+00, 8.892191039842283431e+00, 9.682820467523296204e+00, 1.056715177903931837e+01,
+        1.155883465937652851e+01, 1.267384070151528947e+01, 1.393091310389918289e+01, 1.535211379418177923e+01,
+        1.696349128797309510e+01, 1.879589868990482198e+01, 2.088599907466058846e+01, 2.327750557804054323e+01,
+        2.602271658731131093e+01, 2.918442338619305962e+01, 3.283828974258811174e+01, 3.707583192189045823e+01,
+        4.200816575721451990e+01, 4.777073782243997224e+01, 5.452932468101429049e+01, 6.248767344468634478e+01,
+        7.189727649240108469e+01, 8.306993427631743111e+01, 9.639397813652482031e+01, 1.123553215857374919e+02,
+        1.315649140340119335e+02, 1.547947284376312334e+02, 1.830251850988715552e+02, 2.175079854175568113e+02,
+        2.598498278995140400e+02, 3.121245867818556035e+02, 3.770245173783702458e+02, 4.580653020257635092e+02,
+        5.598658426219653689e+02, 6.885324967857802403e+02, 8.521902266884453403e+02, 1.061721815114114004e+03,
+        1.331803836529085656e+03, 1.682368940494210217e+03, 2.140685129891926443e+03, 2.744334847491432747e+03,
+        3.545516659371773357e+03, 4.617306735234797694e+03, 6.062848530677391758e+03, 8.028955134017154634e+03,
+        1.072641999277462936e+04, 1.446061873485939411e+04, 1.967804579389513789e+04, 2.703776201447279367e+04,
+        3.752217148194723312e+04, 5.261052412010591097e+04, 7.455350923854624329e+04, 1.068125318497402759e+05,
+        1.547702528541975911e+05, 2.268930751685412563e+05, 3.366554971645478061e+05, 5.057644049026088560e+05,
+        7.696291826884134742e+05, 1.186761864945790800e+06, 1.855146094294667715e+06, 2.941132644236832276e+06,
+        4.731169740596920355e+06, 7.725765147199987935e+06, 1.281272565991955126e+07, 2.159151785284808339e+07,
+        3.699029448836502904e+07, 6.445902263727884020e+07, 1.143158678867853615e+08, 2.064425450996979446e+08,
+        3.798502995329785506e+08, 7.125329484929003007e+08, 1.363463294023391629e+09, 2.663196590686555077e+09,
+        5.313347815419462975e+09, 1.083506369700027396e+10, 2.259930737910197667e+10, 4.824707991473375387e+10,
+        1.055069002818752104e+11, 2.365138040635727209e+11, 5.439266129959972285e+11, 1.284356371641026839e+12,
+        3.116424654245920797e+12, 7.777312465656280419e+12, 1.997984843259596733e+13, 5.288649037339853118e+13,
+        1.443776937640548342e+14, 4.068967444890414804e+14, 1.185049702391501141e+15, 3.570348091883284324e+15,
+        1.113971254034978026e+16, 3.603374982229766184e+16, 1.209803708182151942e+17, 4.220890251904870611e+17,
+        1.532169872312865862e+18, 5.793890867821715890e+18, 2.285379920879842924e+19, 9.415714369232187727e+19,
+        4.057471211245170887e+20, 1.831405465804324767e+21, 8.671209773404504008e+21, 4.313209261217173994e+22,
+        2.257498454242656934e+23, 1.245267136898199709e+24, 7.251536499435180219e+24, 4.465573963364524765e+25,
+        2.913233420596266283e+26, 2.017063171206072979e+27, 1.485014353353330393e+28, 1.164811091759882662e+29,
+        9.753661264047912784e+29, 8.737124417851167566e+30, 8.390503265508677363e+31, 8.657362701430272680e+32,
+        9.619472292454361392e+33, 1.153735498483960294e+35, 1.497284701983562213e+36, 2.107816695320163748e+37,
+        3.227106623185610745e+38, 5.387696372515021985e+39, 9.835496017627849225e+40, 1.968904749086105300e+42,
+        4.334704147416758275e+43, 1.052717645113369473e+45, 2.829013521120326147e+46, 8.439656297525588822e+47,
+        2.804279894508234869e+49, 1.041383695988523864e+51, 4.337366591019718310e+52, 2.033523569151676725e+54,
+        1.077238847489773081e+56, 6.472891251891105455e+57, 4.429404678715878536e+59, 3.466135480828349864e+61,
+        3.114928656972704276e+63, 3.228947925415990689e+65, 3.878402486902381042e+67, 5.423187597439531197e+69,
+        8.870779393460412583e+71, 1.705832285076755970e+74, 3.876224350373120420e+76, 1.046359534886878004e+79,
+        3.373858809560757544e+81, 1.306762499786044015e+84, 6.115300889685679832e+86, 3.478550048884517349e+89,
+        2.420073578988056289e+92, 2.072453567501123129e+95, 2.199029867204449277e+98, 2.910868575802139983e+101,
+        4.840699137490951163e+104, 1.018669397739170369e+108, 2.733025017438095928e+111, 9.420797277586029837e+114,
+        4.205525105722885986e+118, 2.451352708852151939e+122, 1.881577053794165543e+126, 1.918506219134233785e+130,
+        2.622069659115564900e+134, 4.848463485415763756e+138, 1.224645005481997780e+143, 4.267387286482591954e+147,
+        2.072505613372582377e+152, };
+
+__constant__ double m_abscissas_double_8[786] =
+      { 1.323228129684237783e-161, 4.129002973520822791e-159, 1.178655462569548882e-156, 3.082189008893206231e-154, 
+        7.393542832199414487e-152, 1.629100644355328639e-149, 3.301545529059822941e-147, 6.162031390854241227e-145,
+        1.060528194470986309e-142, 1.685225757497235089e-140, 2.475534097582263629e-138, 3.365764749507587192e-136,
+        4.240562683924022383e-134, 4.956794227885611715e-132, 5.381716367914161520e-130, 5.433507172294988849e-128,
+        5.107031242794315420e-126, 4.473704932098646394e-124, 3.656376947377888629e-122, 2.791170022694259001e-120,
+        1.992200238692415032e-118, 1.330894359393789718e-116, 8.330356767359890503e-115, 4.890256639970245146e-113,
+        2.695128935451165447e-111, 1.395829605415630844e-109, 6.799997527188085942e-108, 3.119037767379032293e-106,
+        1.348260131419216291e-104, 5.497526018943990804e-103, 2.116384670251198533e-101, 7.699148714858061209e-100,
+        2.649065347250598345e-98, 8.628189263549727753e-97, 2.662520943248368922e-95, 7.790698623582886341e-94,
+        2.163354866683077281e-92, 5.705576739797220361e-91, 1.430338193028564913e-89, 3.411040781372328747e-88,
+        7.744268073516449037e-87, 1.675136564303435813e-85, 3.454795810595704816e-84, 6.798573137099477363e-83,
+        1.277474708033782661e-81, 2.293702139426309483e-80, 3.938021700015175030e-79, 6.469593934876300124e-78,
+        1.017725266990912471e-76, 1.534019529793324951e-75, 2.216999886838860916e-74, 3.074100747562803362e-73,
+        4.092295330837549092e-72, 5.233434175636538471e-71, 6.433506079763357418e-70, 7.607042677901362161e-69,
+        8.656714387163425357e-68, 9.486746058685489974e-67, 1.001756724248288397e-65, 1.019853943834854330e-64,
+        1.001591106610665630e-63, 9.494277822444263952e-63, 8.691422918891890649e-62, 7.687977047887448276e-61,
+        6.574408104196605248e-60, 5.438162502918425191e-59, 4.353340831363003212e-58, 3.374338762181243411e-57,
+        2.533770921173042330e-56, 1.844048925248616738e-55, 1.301410812308480184e-54, 8.910466744374470063e-54,
+        5.921538384124132331e-53, 3.821356134297705127e-52, 2.395780657353036891e-51, 1.459882187581820236e-50,
+        8.650105472076777327e-50, 4.985933550797199316e-49, 2.796911903237435916e-48, 1.527570118993503332e-47,
+        8.126314048196993302e-47, 4.212436363948578182e-46, 2.128604050242564662e-45, 1.048938356323431072e-44,
+        5.042753142653687842e-44, 2.365999225494165364e-43, 1.083813462091040325e-42, 4.848963367960316169e-42,
+        2.119612873737657277e-41, 9.055947139022002648e-41, 3.782987192192666650e-40, 1.545649846917574765e-39,
+        6.178909752126026357e-39, 2.417597558625940386e-38, 9.261305999966332746e-38, 3.474712971194656115e-37,
+        1.277215890629181345e-36, 4.600938133935473864e-36, 1.624804314773052044e-35, 5.626808103137929972e-35,
+        1.911442429947086471e-34, 6.371300415498187125e-34, 2.084444531309441237e-33, 6.695356060065574234e-33,
+        2.112038435637792931e-32, 6.544802906551512393e-32, 1.992864937623987114e-31, 5.964358817764151755e-31,
+        1.754973231464949500e-30, 5.078231558861773863e-30, 1.445447866528259475e-29, 4.048099759391660786e-29,
+        1.115752878927994221e-28, 3.027334168442338592e-28, 8.087868498106224788e-28, 2.128106544151858936e-27,
+        5.516210113930227985e-27, 1.408890921124863906e-26, 3.546520734326774807e-26, 8.800636481096360494e-26,
+        2.153319509043984465e-25, 5.196136544731926346e-25, 1.236869058422202190e-24, 2.904891674490918873e-24,
+        6.732707317563258763e-24, 1.540253603361391055e-23, 3.478765727687221019e-23, 7.758450079933031976e-23,
+        1.708939324269830276e-22, 3.718467010568811152e-22, 7.994094376769029920e-22, 1.698336774318343123e-21,
+        3.566214469724002275e-21, 7.402848534866351662e-21, 1.519411719755297549e-20, 3.083993994528608740e-20,
+        6.191388817974459809e-20, 1.229625987010589227e-19, 2.416245949308411084e-19, 4.698551818749419706e-19,
+        9.042992978848520439e-19, 1.722880198390020817e-18, 3.249832858354112322e-18, 6.070120594586457562e-18,
+        1.122871881646098441e-17, 2.057429235664205922e-17, 3.734613207742816399e-17, 6.716694369267842075e-17,
+        1.197063025055043952e-16, 2.114419661115663617e-16, 3.702017138231021853e-16, 6.425665498746337860e-16,
+        1.105830903726985419e-15, 1.887156051660563224e-15, 3.193979018679125833e-15, 5.361881977473204459e-15,
+        8.929318568606692809e-15, 1.475330560958586660e-14, 2.418708636765824964e-14, 3.935078350904051302e-14,
+        6.354047096308654479e-14, 1.018416666466509442e-13, 1.620423782999307693e-13, 2.559817517056126166e-13,
+        4.015273886294212810e-13, 6.254532358261761291e-13, 9.675981021394182858e-13, 1.486832112534566186e-12,
+        2.269557377760486879e-12, 3.441736008766365832e-12, 5.185793859860652413e-12, 7.764217889314004663e-12,
+        1.155228105746548036e-11, 1.708313121464262097e-11, 2.510951856086201897e-11, 3.668776978510952341e-11,
+        5.329131813941740314e-11, 7.696325397299480856e-11, 1.105200723643722855e-10, 1.578221843796034825e-10,
+        2.241309672940976766e-10, 3.165773201144956642e-10, 4.447730510871610704e-10, 6.216041661455164049e-10,
+        8.642544905395987868e-10, 1.195519306516659349e-09, 1.645482121417189823e-09, 2.253643612941620883e-09,
+        3.071610576496751310e-09, 4.166474690460445927e-09, 5.625036504185181035e-09, 7.559059638953998396e-09,
+        1.011177417876491092e-08, 1.346588701906267454e-08, 1.785340092957703350e-08, 2.356759364235337519e-08,
+        3.097756373337616088e-08, 4.054581171302714730e-08, 5.284939280085554173e-08, 6.860525247854168448e-08,
+        8.870043714076795346e-08, 1.142279599340281637e-07, 1.465291959965373757e-07, 1.872437814520259903e-07,
+        2.383680961705324062e-07, 3.023235208219232784e-07, 3.820357732606947876e-07, 4.810267467496160044e-07,
+        6.035203917139166314e-07, 7.545643021775656875e-07, 9.401687861337141280e-07, 1.167465314019272078e-06,
+        1.444886349199346242e-06, 1.782368666762205796e-06, 2.191582359683820240e-06, 2.686187812137005286e-06,
+        3.282122985909738110e-06, 3.997923415034129149e-06, 4.855077333283880469e-06, 5.878418366687560187e-06,
+        7.096558206229387964e-06, 8.542361632206236097e-06, 1.025346618920209381e-05, 1.227284870748632855e-05,
+        1.464944073127878202e-05, 1.743879474552002742e-05, 2.070380288967650755e-05, 2.451546960924430874e-05,
+        2.895373942298085844e-05, 3.410838067694928604e-05, 4.007992581615393488e-05, 4.698066833232878622e-05,
+        5.493571614427227251e-05, 6.408410073746518169e-05, 7.457994093551813828e-05, 8.659365970069775654e-05,
+        1.003132518682442285e-04, 1.159456002136906496e-04, 1.337178367385581674e-04, 1.538787455425709779e-04,
+        1.767002031351005554e-04, 2.024786515302844608e-04, 2.315365989746650402e-04, 2.642241426787982083e-04,
+        3.009205074706080013e-04, 3.420355938637258307e-04, 3.880115286439000550e-04, 4.393242107257947798e-04,
+        4.964848447258090522e-04, 5.600414544382562271e-04, 6.305803681962314437e-04, 7.087276679481586600e-04,
+        7.951505937892094439e-04, 8.905588956558126794e-04, 9.957061239230124343e-04, 1.111390850739538593e-03,
+        1.238457814094548688e-03, 1.377798976832850428e-03, 1.530354493121150144e-03, 1.697113575214988470e-03,
+        1.879115253782404405e-03, 2.077449025503311209e-03, 2.293255382179820056e-03, 2.527726216158548279e-03,
+        2.782105097477072741e-03, 3.057687418798497807e-03, 3.355820404885606963e-03, 3.677902984083964409e-03,
+        4.025385520026097270e-03, 4.399769402530814407e-03, 4.802606497446985045e-03, 5.235498455973840111e-03,
+        5.700095884774212336e-03, 6.198097378977308725e-03, 6.731248420937948614e-03, 7.301340148374219834e-03,
+        7.910207996239952125e-03, 8.559730217397303903e-03, 9.251826287833445298e-03, 9.988455202809488913e-03,
+        1.077161367093554544e-02, 1.160333421372954856e-02, 1.248568317873621646e-02, 1.342075867475355427e-02,
+        1.441068843813546585e-02, 1.545762763950860648e-02, 1.656375664055830135e-02, 1.773127871080136402e-02,
+        1.896241771447260382e-02, 2.025941577780677588e-02, 2.162453094709917839e-02, 2.306003484797691421e-02,
+        2.456821035631025318e-02, 2.615134929114115217e-02, 2.781175013990572523e-02, 2.955171582608151263e-02,
+        3.137355152920124081e-02, 3.327956256694509270e-02, 3.527205234875621605e-02, 3.735332041012234938e-02,
+        3.952566053633324126e-02, 4.179135898416228534e-02, 4.415269280953487221e-02, 4.661192830883879903e-02,
+        4.917131958110712872e-02, 5.183310721786459418e-02, 5.459951712697841302e-02, 5.747275949639657337e-02,
+        6.045502790319455825e-02, 6.354849857288828754e-02, 6.675532979350985865e-02, 7.007766148848641979e-02,
+        7.351761495191403887e-02, 7.707729274938041525e-02, 8.075877878706524317e-02, 8.456413855143733669e-02,
+        8.849541952147546057e-02, 9.255465175496720496e-02, 9.674384865008904765e-02, 1.010650078831426502e-01,
+        1.055201125230189472e-01, 1.101111323226840632e-01, 1.148400251877307103e-01, 1.197087388218165293e-01,
+        1.247192125486176994e-01, 1.298733793097628269e-01, 1.351731678380792159e-01, 1.406205050053816316e-01,
+        1.462173183439629526e-01, 1.519655387409069424e-01, 1.578671033043359383e-01, 1.639239584007306411e-01,
+        1.701380628625154331e-01, 1.765113913651907042e-01, 1.830459379734134606e-01, 1.897437198555789051e-01,
+        1.966067811666385690e-01, 2.036371970991047974e-01, 2.108370781024367852e-01, 2.182085742712797843e-01,
+        2.257538799033364379e-01, 2.334752382279873511e-01, 2.413749463071469410e-01, 2.494553601102403241e-01,
+        2.577188997656175820e-01, 2.661680549911833443e-01, 2.748053907075124803e-01, 2.836335528372471376e-01,
+        2.926552742951268547e-01, 3.018733811735925662e-01, 3.112907991295277084e-01, 3.209105599783561596e-01,
+        3.307358085024083972e-01, 3.407698094811951648e-01, 3.510159549519934555e-01, 3.614777717099542274e-01,
+        3.721589290577866932e-01, 3.830632468159621812e-01, 3.941947036053136035e-01, 4.055574454148868711e-01,
+        4.171557944689308074e-01, 4.289942584079951543e-01, 4.410775398002453309e-01, 4.534105460003012245e-01,
+        4.659983993741692944e-01, 4.788464479101668631e-01, 4.919602762371392109e-01, 5.053457170727489659e-01, 
+        5.190088631261786795e-01, 5.329560794812372669e-01, 5.471940164876055195e-01, 5.617296231898020413e-01, 
+        5.765701613254061793e-01, 5.917232199261468491e-01, 6.071967305576643327e-01, 6.229989832360855492e-01, 
+        6.391386430620321596e-01, 6.556247676153161584e-01, 6.724668251563812272e-01, 6.896747136835329047e-01, 
+        7.072587808981804764e-01, 7.252298451337033758e-01, 7.435992173071710726e-01, 7.623787239570054101e-01, 
+        7.815807314337971290e-01, 8.012181713158943859e-01, 8.213045671260926392e-01, 8.418540624307963733e-01, 
+        8.628814504084197628e-01, 8.844022049795737430e-01, 9.064325135977815717e-01, 9.289893118061069464e-01, 
+        9.520903196722039764e-01, 9.757540802219457353e-01, 1.000000000000000000e+00, 1.024848391894543008e+00, 
+        1.050320520372784475e+00, 1.076438649284173871e+00, 1.103226092399127978e+00, 1.130707266862927052e+00, 
+        1.158907749757141229e+00, 1.187854337974646084e+00, 1.217575111629048984e+00, 1.248099501235266386e+00, 
+        1.279458358915164500e+00, 1.311684033900709062e+00, 1.344810452627081143e+00, 1.378873203729832710e+00, 
+        1.413909628283517352e+00, 1.449958915644490754e+00, 1.487062205287898607e+00, 1.525262695058439148e+00, 
+        1.564605756286502811e+00, 1.605139056255971231e+00, 1.646912688547541313e+00, 1.689979311822189937e+00, 
+        1.734394297653598793e+00, 1.780215888066332921e+00, 1.827505363488657555e+00, 1.876327221885466881e+00,
+        1.926749369898304239e+00, 1.978843326886336694e+00, 2.032684442834914613e+00, 2.088352131177556992e+00,
+        2.145930117663470432e+00, 2.205506706496711366e+00, 2.267175065075584681e+00, 2.331033528772661605e+00,
+        2.397185927317806037e+00, 2.465741934479827004e+00, 2.536817442887937264e+00, 2.610534965993323711e+00,
+        2.687024069345184956e+00, 2.766421833546071979e+00, 2.848873351459948781e+00, 2.934532262474922666e+00,
+        3.023561326873131923e+00, 3.116133043635102211e+00, 3.212430315307524598e+00, 3.312647163894682976e+00, 
+        3.416989502097797957e+00, 3.525675964626843197e+00, 3.638938804749809967e+00, 3.757024861729272487e+00, 
+        3.880196605330264341e+00, 4.008733264172298986e+00, 4.142932045347867609e+00, 4.283109453446644399e+00, 
+        4.429602717916437040e+00, 4.582771338567048147e+00, 4.742998759991079249e+00, 4.910694186746867507e+00, 
+        5.086294552335034437e+00, 5.270266656314831820e+00, 5.463109485364516396e+00, 5.665356735708146927e+00, 
+        5.877579556128345480e+00, 6.100389532781943879e+00, 6.334441939256981670e+00, 6.580439277782222274e+00, 
+        6.839135140254664526e+00, 7.111338420820842566e+00, 7.397917915172903763e+00, 7.699807345544508469e+00, 
+        8.018010854664294474e+00, 8.353609016702406728e+00, 8.707765418592385473e+00, 9.081733871099147484e+00, 
+        9.476866315716376006e+00, 9.894621501007146275e+00, 1.033657451045679019e+01, 1.080442723340841910e+01, 
+        1.130001988133777781e+01, 1.182534366375335115e+01, 1.238255475156052427e+01, 1.297398967101161563e+01, 
+        1.360218228861306245e+01, 1.426988256684760289e+01, 1.498007729260327644e+01, 1.573601300513857081e+01, 
+        1.654122137866316500e+01, 1.739954734664685784e+01, 1.831518029132688981e+01, 1.929268866318984532e+01, 
+        2.033705844217826172e+01, 2.145373590584482942e+01, 2.264867523060898736e+01, 2.392839152177298272e+01, 
+        2.530001994731418268e+01, 2.677138174118011529e+01, 2.835105794560498805e+01, 3.004847188085487195e+01, 
+        3.187398146713610639e+01, 3.383898267989664904e+01, 3.595602559959535672e+01, 3.823894472392493310e+01, 
+        4.070300544879345396e+01, 4.336506889917953679e+01, 4.624377760823269784e+01, 4.935976490967979071e+01, 
+        5.273589133292714765e+01, 5.639751178186770847e+01, 6.037277784867852275e+01, 6.469298027622754351e+01, 
+        6.939293735292118365e+01, 7.451143592061966836e+01, 8.009173272176674066e+01, 8.618212503236856949e+01, 
+        9.283660095406551480e+01, 1.001155814082968890e+02, 1.080867678325352448e+02, 1.168261118752949279e+02, 
+        1.264189260858047240e+02, 1.369611577708331715e+02, 1.485608519349011866e+02, 1.613398336385932743e+02, 
+        1.754356453320629017e+02, 1.910037809024609590e+02, 2.082202655019913565e+02, 2.272846389233001078e+02, 
+        2.484234106336023257e+02, 2.718940668983047258e+02, 2.979897251188232016e+02, 3.270445480633676878e+02, 
+        3.594400516741229885e+02, 3.956124653087335485e+02, 4.360613334959077953e+02, 4.813595846269808355e+02, 
+        5.321653357808338203e+02, 5.892357556996862196e+02, 6.534433717775449045e+02, 7.257952842284018994e+02, 
+        8.074558443729566627e+02, 8.997734679339701200e+02, 1.004312392957944252e+03, 1.122890361185594877e+03,
+        1.257623408459775530e+03, 1.410979202907522234e+03, 1.585840680166573460e+03, 1.785582106601447262e+03, 
+        2.014160171499825914e+03, 2.276223289283167479e+03, 2.577243010007973485e+03, 2.923672325162804598e+03, 
+        3.323136759290736047e+03, 3.784665511113575050e+03, 4.318971620160236406e+03, 4.938792274850918489e+03, 
+        5.659303058273368331e+03, 6.498623292476395004e+03, 7.478433875318933386e+03, 8.624734342286166238e+03, 
+        9.968772633484590145e+03, 1.154818959559393902e+04, 1.340843110702649390e+04, 1.560449453908580443e+04, 
+        1.820309391023133793e+04, 2.128535066649680777e+04, 2.495014598048375046e+04, 2.931830770482188047e+04,
+        3.453785313845473397e+04, 4.079057084931056631e+04, 4.830030527863206410e+04, 5.734341246586992004e+04,
+        6.826199159022146453e+04, 8.148067525594191464e+04, 9.752799507478730867e+04, 1.170636462204808295e+05,
+        1.409133795481584143e+05, 1.701137853111825512e+05, 2.059699426710509940e+05, 2.501298539735692463e+05,
+        3.046808435555379486e+05, 3.722747886360361411e+05, 4.562913164460176067e+05, 5.610511554921845541e+05, 
+        6.920959565810343691e+05, 8.565564972181198149e+05, 1.063638800552326000e+06, 1.325268101226286025e+06,
+        1.656944841847240121e+06, 2.078886479301160156e+06, 2.617555920130068069e+06, 3.307714852226224955e+06,
+        4.195192293202626259e+06, 5.340631300250745566e+06, 6.824578495767020734e+06, 8.754424053248831818e+06,
+        1.127390159772263517e+07, 1.457614342739689625e+07, 1.892169326841938100e+07, 2.466345986800667442e+07,
+        3.228142821711217588e+07, 4.243114571539869754e+07, 5.601173714434088431e+07, 7.426172509723072112e+07,
+        9.889461357830121731e+07, 1.322915875470427182e+08, 1.777766240727455981e+08, 2.400110583389834263e+08,
+        3.255621033641982742e+08, 4.437258820593761403e+08, 6.077246218504877165e+08, 8.364565879857375417e+08,
+        1.157066594326456169e+09, 1.608740826498742961e+09, 2.248337657948688269e+09, 3.158785978851336228e+09,
+        4.461677081363911380e+09, 6.336244831048209270e+09, 9.048130159588677560e+09, 1.299321362309972265e+10,
+        1.876478261212947929e+10, 2.725703976712888971e+10, 3.982553459064288940e+10, 5.853727794017415415e+10,
+        8.656299089553103385e+10, 1.287959733041898747e+11, 1.928345065430099883e+11, 2.905510467545806044e+11,
+        4.406145488098485809e+11, 6.725708918778493152e+11, 1.033486938212196930e+12, 1.598840557086695854e+12,
+        2.490490134218272825e+12, 3.906528466724583921e+12, 6.171225147961354244e+12, 9.819163736485109137e+12,
+        1.573800106991564475e+13, 2.541245461530031221e+13, 4.134437628407981776e+13, 6.778141973485971528e+13,
+        1.119906286595884492e+14, 1.865016806041768967e+14, 3.130890948724989738e+14, 5.298978847669068280e+14,
+        9.042973899804181753e+14, 1.556259036818991439e+15, 2.701230066368200812e+15, 4.729430105054711279e+15,
+        8.353779033096586530e+15, 1.488827606293191651e+16, 2.677653466031614956e+16, 4.860434481369499270e+16,
+        8.905735519300993312e+16, 1.647413728306871552e+17, 3.077081325673016377e+17, 5.804234101329097680e+17,
+        1.105828570628099614e+18, 2.128315358808074026e+18, 4.138651532085235581e+18, 8.132554212123920035e+18,
+        1.615146503312570855e+19, 3.242548467260718193e+19, 6.581494581080701321e+19, 1.350831366183090003e+20,
+        2.804093832520937396e+20, 5.888113683467563837e+20, 1.250923435312468276e+21, 2.689280279098215635e+21,
+        5.851582825664479700e+21, 1.288917231788944660e+22, 2.874582763768997631e+22, 6.492437335109217869e+22,
+        1.485286605867082177e+23, 3.442469159113307066e+23, 8.084930196860438207e+23, 1.924506778048094878e+24,
+        4.643992662491470729e+24, 1.136281452083591334e+25, 2.819664891060694571e+25, 7.097781559991856367e+25,
+        1.812838850127688486e+26, 4.699012851344539124e+26, 1.236419707162832951e+27, 3.303236261210411286e+27,
+        8.962558097638891218e+27, 2.470294852986226117e+28, 6.918270960555942883e+28, 1.969189447958411510e+29,
+        5.698092609453981289e+29, 1.676626156396922084e+30, 5.017901520171556970e+30, 1.527929892279834489e+31,
+        4.734762318366711949e+31, 1.493572546446777040e+32, 4.797441164681908184e+32, 1.569538296400998732e+33,
+        5.231651156910242454e+33, 1.777206511525290941e+34, 6.154587299576916134e+34, 2.173469781356604872e+35,
+        7.829529896526581616e+35, 2.877935554073076917e+36, 1.079761320923458592e+37, 4.136337730951207042e+37,
+        1.618408489711185844e+38, 6.469770640447824771e+38, 2.643413654859316358e+39, 1.104246728308525703e+40,
+        4.717842641881260665e+40, 2.062296462389327711e+41, 9.226680005161257219e+41, 4.226544071632731963e+42,
+        1.983043729707066518e+43, 9.533448690970155039e+43, 4.697914578740208606e+44, 2.373923101980436574e+45,
+        1.230570211868531753e+46, 6.546344338411695147e+46, 3.575371819335804914e+47, 2.005642453538335506e+48,
+        1.156055268028903078e+49, 6.849867807870312958e+49, 4.174004815218951121e+50, 2.616872034052857472e+51,
+        1.688750346837297725e+52, 1.122275666009684101e+53, 7.683968740248677071e+53, 5.422849612654278583e+54,
+        3.946686701799533415e+55, 2.963543587288132884e+56, 2.297086395798939516e+57, 1.838856414208555761e+58,
+        1.521049475711243996e+59, 1.300732291175071112e+60, 1.150559591141716740e+61, 1.053265997373725461e+62,
+        9.984114209879020836e+62, 9.805325615938694719e+63, 9.982463564199115995e+64, 1.054102211457911410e+66,
+        1.155172684780782463e+67, 1.314571302334116663e+68, 1.554362407685457310e+69, 1.910791206002645077e+70,
+        2.443616403890711206e+71, 3.252983822318823232e+72, 4.510600140020139737e+73, 6.518821831001902447e+74,
+        9.825834460774267633e+75, 1.545692063622722856e+77, 2.539346088408163253e+78, 4.359763993811836117e+79,
+        7.827943627464404744e+80, 1.470896877674301183e+82, 2.894527071420674290e+83, 5.969662541607915492e+84,
+        1.291277613981057357e+86, 2.931656535626877923e+87, 6.991353547531463135e+88, 1.752671194525972852e+90,
+        4.622450137056020715e+91, 1.283581933169566226e+93, 3.755839001138390788e+94, 1.158991729845978702e+96,
+        3.774916315438862678e+97, 1.298844894462381673e+99, 4.725038949943384889e+100, 1.819000031203286740e+102,
+        7.416966330876906188e+103, 3.206116996910598204e+105, 1.470588770071975193e+107, 7.164198238238641057e+108,
+        3.710397624567077270e+110, 2.044882454279709373e+112, 1.200428778654730225e+114, 7.513744370030172114e+115,
+        5.019575746343410636e+117, 3.582726927665698318e+119, 2.734947775877248560e+121, 2.235283764078944248e+123,
+        1.958084751118243323e+125, 1.840431913109305657e+127, 1.858143260692831108e+129, 2.017432949655777136e+131,
+        2.358177615888101494e+133, 2.971092974178603610e+135, 4.039532321435816302e+137, 5.933923069661132195e+139,
+        9.429263693444953240e+141, 1.622841456932873872e+144, 3.028884476067694180e+146, 6.138356175015339477e+148,
+        1.352531557191942648e+151, 3.244447362295582945e+153, };
+
+__constant__ double* m_abscissas_double[8] = {
+    m_abscissas_double_1,
+    m_abscissas_double_2,
+    m_abscissas_double_3,
+    m_abscissas_double_4,
+    m_abscissas_double_5,
+    m_abscissas_double_6,
+    m_abscissas_double_7,
+    m_abscissas_double_8,
+};
+
+__constant__ double m_weights_double_1[13] =
+      { 2.703640234162693583e-160, 3.100862940179668765e-58, 5.828334625665462970e-21, 1.628894422402653830e-07,
+        8.129907377394029252e-03, 2.851214447180802931e-01, 1.228894002317118650e+00, 9.374610761705565881e+00,
+        6.136846875218162167e+02, 8.367995944653844271e+06, 2.286032371256753845e+17, 9.029964022492184559e+44,
+        1.637973037681055808e+119, };
+
+__constant__ double m_weights_double_2[12] =
+      { 1.029757744225565290e-96, 5.564174008086804112e-35, 1.534846576427062716e-12, 1.519539651119905182e-04,
+        7.878691652861874032e-02, 6.288072016384128612e-01, 2.842403831496369386e+00, 5.152309209026500589e+01,
+        2.554172947873109927e+04, 8.291547503290989754e+10, 6.794911791960761587e+27, 1.108995159102362663e+73, };
+
+__constant__ double m_weights_double_3[25] =
+      { 1.545310485347377408e-124, 4.549745016271158113e-75, 3.781189989988588481e-45, 4.369440793304363176e-27,
+        3.253896178006708087e-16, 1.057239289288944987e-09, 7.826174663495492476e-06, 1.459783224353939263e-03,
+        2.972970552567852420e-02, 1.637950661613330541e-01, 4.392303913269138921e-01, 8.744243777287317807e-01,
+        1.804759465860974506e+00, 4.894937215283148383e+00, 2.036214502429748943e+01, 1.576549789679037479e+02,
+        3.249553828744194733e+03, 3.335686029489862584e+05, 4.858218914917275532e+08, 5.655171002571584464e+13,
+        9.084276291356790926e+21, 2.202757570781655071e+35, 1.851176020895552142e+57, 1.873046373612647920e+93,
+        3.113183070605141140e+152, };
+
+__constant__ double m_weights_double_4[49] =
+      { 2.690380169654157101e-141, 9.388760099830475385e-110, 3.267856956418766261e-85, 4.012903562780032075e-66,
+        2.794595941054873674e-51, 9.598140333687791635e-40, 8.762766371925782803e-31, 7.896919977115783593e-24,
+        1.951680620313826776e-18, 2.931867534349928041e-14, 4.976350908135118762e-11, 1.546933241860617074e-08,
+        1.283189791774752963e-06, 3.809052946018782340e-05, 5.087526585392884730e-04, 3.656819625189471368e-03,
+        1.627679402690602992e-02, 5.011672130624018967e-02, 1.165913368715250324e-01, 2.201514148384271336e-01,
+        3.581909054968942386e-01, 5.288599003801643436e-01, 7.422823219366348741e-01, 1.032914080772662205e+00,
+        1.478415067523268199e+00, 2.242226697017918644e+00, 3.684755742578570582e+00, 6.677326887819023056e+00,
+        1.358063058433697357e+01, 3.171262375809110066e+01, 8.776338468947827779e+01, 3.006939713363920293e+02,
+        1.352196150715330628e+03, 8.616353573310419356e+03, 8.591849573350877359e+04, 1.523635814554291966e+06,
+        5.663834603448267056e+07, 5.450828629396188577e+09, 1.780881993484818221e+12, 2.797112703281894578e+15,
+        3.300887168363313931e+19, 5.192538272313512016e+24, 2.273085973059979872e+31, 7.124498195222272142e+39,
+        5.379592741425673874e+50, 4.647296508337283075e+64, 3.395147156494395571e+82, 2.736576372417856435e+105,
+        6.584825756536212781e+134, };
+
+__constant__ double m_weights_double_5[98] =
+      { 1.692276285171240629e-150, 1.180420021590838281e-132, 6.494931071412232065e-117, 4.979673804239645358e-103, 
+        8.790122245397054202e-91, 5.564311726870413043e-80, 1.867634664877268411e-70, 4.693767384843440310e-62,
+        1.197772698674604837e-54, 4.060530886983702887e-48, 2.318268710612758367e-42, 2.748088060676949794e-37,
+        8.136086869664039226e-33, 7.081491999860360593e-29, 2.092407629019781417e-25, 2.383020547076997517e-22,
+        1.170143938604536054e-19, 2.734857915002515580e-17, 3.319894174569245506e-15, 2.260825106530477104e-13,
+        9.244747974241858562e-12, 2.410325858091057071e-10, 4.224928060220423782e-09, 5.217223349652829804e-08,
+        4.730110697329046717e-07, 3.265522864288710545e-06, 1.772851678458610971e-05, 7.787346612077215804e-05,
+        2.838101678971546354e-04, 8.775026198694109646e-04, 2.347474744139291716e-03, 5.529174974874315725e-03,
+        1.164520226280038968e-02, 2.223487842904240574e-02, 3.896253311038730452e-02, 6.334975706136386464e-02,
+        9.651712033300261848e-02, 1.390236708907266445e-01, 1.908593745910709887e-01, 2.515965688234414960e-01,
+        3.206651646562737595e-01, 3.976974208167367099e-01, 4.828935799767836828e-01, 5.773826389735376677e-01,
+        6.835838865575605461e-01, 8.056083579298257627e-01, 9.497742078309479997e-01, 1.125351459431134254e+00,
+        1.345711576612114788e+00, 1.630156867495860456e+00, 2.006880650908830857e+00, 2.517828844916874130e+00,
+        3.226826819856410846e+00, 4.233461155863004269e+00, 5.697400323487776530e+00, 7.882247346334201378e+00,
+        1.123717929435969530e+01, 1.655437952523069781e+01, 2.528458931361129124e+01, 4.019700050163276117e+01,
+        6.682515670231120695e+01, 1.168022589948424530e+02, 2.160045684819153702e+02, 4.257255901158116698e+02,
+        9.017180693982791021e+02, 2.072151523320542727e+03, 5.222689557952776194e+03, 1.461663959276604441e+04,
+        4.606455611513396576e+04, 1.660950339384278845e+05, 6.976630616605097333e+05, 3.484240083705972727e+06,
+        2.117385064786894718e+07, 1.607368605379557548e+08, 1.570235957877638143e+09, 2.041619284762317483e+10,
+        3.670425964529826371e+11, 9.527196643411724126e+12, 3.749667772735766186e+14, 2.365380223523087981e+16,
+        2.546815287226970627e+18, 5.026010591299970789e+20, 1.970775914722195502e+23, 1.682531038342715298e+26,
+        3.469062187981719410e+29, 1.942614547946028081e+33, 3.375034694941022784e+37, 2.115298406181711256e+42,
+        5.673738540911562268e+47, 7.904099301170483654e+53, 7.121903115084356741e+60, 5.321820777644930491e+68,
+        4.370977753639010591e+77, 5.429657931755513797e+87, 1.464602226824232950e+99, 1.292445035662836561e+112,
+        5.936633203060705474e+126, 2.402419924621336913e+143, };
+
+__constant__ double m_weights_double_6[196] =
+      { 2.552410363565288863e-155, 7.965872719315690060e-146, 6.586401422963018216e-137, 1.563673437419490296e-128, 
+        1.149636272392214573e-120, 2.810189759625314580e-113, 2.441446149780773329e-106, 8.026292508555041710e-100,
+        1.059034284623927886e-93, 5.927259046205893861e-88, 1.482220909125121967e-82, 1.738946448501809732e-77,
+        1.002047910184021813e-72, 2.960929073720769637e-68, 4.671749731809402860e-64, 4.088398674807775827e-60,
+        2.056642628601930023e-56, 6.149878578966749305e-53, 1.128142221531950274e-49, 1.307702777646013040e-46,
+        9.848757125541659318e-44, 4.946847667192787369e-41, 1.698284656321589089e-38, 4.077947349805764486e-36,
+        6.998897321243266048e-34, 8.762183229651405846e-32, 8.156281709801700633e-30, 5.747366069381804213e-28,
+        3.117951907317865517e-26, 1.323052992594482858e-24, 4.457166057119926322e-23, 1.208896132634708032e-21,
+        2.674697849739340358e-20, 4.887394807742436672e-19, 7.461632083041868391e-18, 9.622230748739818989e-17,
+        1.058884510032627118e-15, 1.003988180288807180e-14, 8.276358838778374127e-14, 5.982281469656734375e-13,
+        3.821855766886203088e-12, 2.174279097299082001e-11, 1.109294120074848583e-10, 5.109055596902086022e-10,
+        2.137447956882816268e-09, 8.170468538364022161e-09, 2.869308592926374871e-08, 9.305185930419436742e-08,
+        2.800231592227134982e-07, 7.855263634214717091e-07, 2.062924236714395731e-06, 5.092224131071637441e-06,
+        1.185972357373608535e-05, 2.615333473470835518e-05, 5.479175746096322166e-05, 1.093962713107868416e-04,
+        2.087714243290528595e-04, 3.818797556417767457e-04, 6.712796918790164790e-04, 1.136760145626956604e-03,
+        1.858775505765622915e-03, 2.941191222579735746e-03, 4.512821350378020080e-03, 6.727293426938802892e-03,
+        9.760915371480980900e-03, 1.380842853102550981e-02, 1.907678055354397196e-02, 2.577730275571060412e-02,
+        3.411688991056810143e-02, 4.428892397843486143e-02, 5.646473816310556552e-02, 7.078637998740884103e-02,
+        8.736131246718460273e-02, 1.062595125372295046e-01, 1.275132133780278017e-01, 1.511193209351630349e-01,
+        1.770443400812491404e-01, 2.052314915777496186e-01, 2.356095985715091716e-01, 2.681032744853198083e-01,
+        3.026439500331752405e-01, 3.391813282438962329e-01, 3.776949427111484449e-01, 4.182056049753837852e-01,
+        4.607866519948383101e-01, 5.055750360563806155e-01, 5.527824318481410262e-01, 6.027066663808878454e-01,
+        6.557439076684384801e-01, 7.124021812071310501e-01, 7.733169258916167748e-01, 8.392694625821144443e-01,
+        9.112094418201526544e-01, 9.902825786957198607e-01, 1.077865293953107863e+00, 1.175608288920191064e+00,
+        1.285491624542001346e+00, 1.409894601042286311e+00, 1.551684711657329886e+00, 1.714331263928885829e+00,
+        1.902051053858215699e+00, 2.119995922515087770e+00, 2.374495377438728901e+00, 2.673372087884984440e+00,
+        3.026354489757871517e+00, 3.445619726158519068e+00, 3.946512819227006419e+00, 4.548505964859933724e+00,
+        5.276487613615791435e+00, 6.162508226184798743e+00, 7.248163842886806184e+00, 8.587878410768473380e+00,
+        1.025346434903602082e+01, 1.234051869120733230e+01, 1.497748183201988157e+01, 1.833859935862139637e+01,
+        2.266266859437541631e+01, 2.828045768298752298e+01, 3.565528397044830339e+01, 4.544381261232990127e+01,
+        5.858833744254070379e+01, 7.645876087681923606e+01, 1.010741758687003802e+02, 1.354538987141142977e+02,
+        1.841824059064608872e+02, 2.543337025162468240e+02, 3.570103970895535977e+02, 5.099537256432247190e+02,
+        7.420561390174965949e+02, 1.101323941193719451e+03, 1.669232910686306616e+03, 2.587203282090385703e+03,
+        4.106608602134535014e+03, 6.685657263550896700e+03, 1.118216368762133982e+04, 1.924811115485038079e+04,
+        3.416174865734933127e+04, 6.263882227839496242e+04, 1.189094418952240294e+05, 2.342262528110389793e+05,
+        4.798899889628646876e+05, 1.025279649144740527e+06, 2.290428015483177407e+06, 5.365618820221241118e+06,
+        1.322172034826883742e+07, 3.438296542047893623e+07, 9.468905314460992170e+07, 2.771843378168242512e+08,
+        8.658950437199969679e+08, 2.898779165825890846e+09, 1.044627762990198184e+10, 4.071673625087267154e+10,
+        1.725245696783106160e+11, 7.989856904303845909e+11, 4.067537100664303783e+12, 2.290253922913114847e+13,
+        1.435560574531699914e+14, 1.008680130601194048e+15, 8.003530334765274913e+15, 7.227937568629809266e+16,
+        7.491693576707361828e+17, 8.991671234614216799e+18, 1.261556024888540618e+20, 2.090038400033346091e+21,
+        4.132773073376509056e+22, 9.865671928781943336e+23, 2.877978132616007671e+25, 1.039303004928044064e+27,
+        4.710544722984128252e+28, 2.719194692980296464e+30, 2.030608169419634520e+32, 1.994536427964099457e+34,
+        2.622806931876485852e+36, 4.705142628855489738e+38, 1.174794916996875010e+41, 4.170574236544843559e+43,
+        2.153441953645800917e+46, 1.656794933445123415e+49, 1.948830907651317326e+52, 3.601980393005358786e+55,
+        1.077033440153993124e+59, 5.374188883861674378e+62, 4.625267105826449467e+66, 7.111646979020385006e+70,
+        2.027996051444846521e+75, 1.116168784120367146e+80, 1.237019821283735086e+85, 2.888108172342166477e+90,
+        1.490426937972460544e+96, 1.789306677271856318e+102, 5.276973875344766848e+108, 4.051217867886536330e+115,
+        8.611617868168979525e+122, 5.412634353380155695e+130, 1.078756609821147465e+139, 7.344353246966125053e+147, };
+
+__constant__ double m_weights_double_7[393] =
+      { 8.688318611421924613e-158, 6.864317997043424201e-153, 3.829638174036322920e-148, 1.524985558970066863e-143, 
+        4.379527631402474835e-139, 9.162408388991747001e-135, 1.410086556664696347e-130, 1.611529786006329005e-126,
+        1.380269212504431613e-122, 8.938739565456142404e-119, 4.414803004265274778e-115, 1.676831992534574674e-111,
+        4.937648515671545377e-108, 1.136068312653058895e-104, 2.057969760853201132e-101, 2.956779836249922681e-98,
+        3.393449014375824853e-95, 3.132619285740674842e-92, 2.341677665639346254e-89, 1.426656997926173190e-86,
+        7.128825597334931865e-84, 2.939485275517928205e-81, 1.006113300119903410e-78, 2.874969402023240560e-76,
+        6.896713338909433222e-74, 1.396405038640012785e-71, 2.398869799873387326e-69, 3.514180228970525006e-67,
+        4.411557600438730779e-65, 4.768408435763044172e-63, 4.458287229998440383e-61, 3.621710763086768959e-59,
+        2.567373174003034094e-57, 1.594829856885795944e-55, 8.716746897177859412e-54, 4.208424534880021226e-52,
+        1.801637343401221381e-50, 6.864432292330768862e-49, 2.336084584516383243e-47, 7.125716658075193173e-46,
+        1.954733295862350631e-44, 4.838195020814970471e-43, 1.083903033389729471e-41, 2.204655424309513426e-40,
+        4.083431629921110537e-39, 6.907095608064865023e-38, 1.069951518082577963e-36, 1.521972185061747284e-35,
+        1.993254198127980161e-34, 2.409552194902670884e-33, 2.695243589253751811e-32, 2.796309045342585624e-31,
+        2.697138787161831243e-30, 2.423968619042656074e-29, 2.034233848004972409e-28, 1.597498662808006882e-27,
+        1.176341105034547043e-26, 8.138404856556384931e-26, 5.300199402716282910e-25, 3.255367628680633536e-24,
+        1.889060856810273071e-23, 1.037502167741821871e-22, 5.402129194695882094e-22, 2.671080147950250592e-21,
+        1.256163163817414397e-20, 5.627458451375099018e-20, 2.405110192151924414e-19, 9.820723025892385774e-19,
+        3.836610965933493002e-18, 1.435949417965440387e-17, 5.155736116435221852e-17, 1.778106820243535736e-16,
+        5.897650538103448384e-16, 1.883545377386949394e-15, 5.799022727889041128e-15, 1.723080101027408120e-14,
+        4.946559668895564981e-14, 1.373437058883951037e-13, 3.692057356296675476e-13, 9.618669754374864080e-13,
+        2.430904641718059201e-12, 5.965319652795549281e-12, 1.422677541958913512e-11, 3.300412010407028696e-11,
+        7.453993539444124847e-11, 1.640317480539372495e-10, 3.519919455549922227e-10, 7.371241496931924727e-10,
+        1.507573517782825692e-09, 3.013444008176544118e-09, 5.891170930525923854e-09, 1.127175867596519203e-08,
+        2.112135943063526334e-08, 3.878572405868819131e-08, 6.984140168311147329e-08, 1.233979234102365865e-07,
+        2.140481233406505212e-07, 3.647293211756793211e-07, 6.108366265875129839e-07, 1.006020283089617901e-06,
+        1.630199379920459998e-06, 2.600430208375972125e-06, 4.085372746054298735e-06, 6.324194831966406940e-06,
+        9.650830226718535837e-06, 1.452455211307694488e-05, 2.156782506321975658e-05, 3.161234361554654466e-05,
+        4.575404320696170555e-05, 6.541767069965264068e-05, 9.243122234114186712e-05, 1.291101968446571125e-04,
+        1.783511762821284409e-04, 2.437337497712608884e-04, 3.296292528289701234e-04, 4.413142327104518440e-04,
+        5.850859955683163216e-04, 7.683770763700705263e-04, 9.998650298180469208e-04, 1.289573601590465490e-03,
+        1.648961132392222413e-03, 2.090991995585424661e-03, 2.630186988492201910e-03, 3.282648895332118799e-03,
+        4.066059914467245175e-03, 4.999648283080481820e-03, 6.104122218554241819e-03, 7.401570199659662364e-03,
+        8.915327597805008451e-03, 1.066981070009509413e-02, 1.269032020049755525e-02, 1.500281723149735994e-02,
+        1.763367592672867332e-02, 2.060941730962251417e-02, 2.395642996410886880e-02, 2.770068343772389725e-02,
+        3.186744063963193757e-02, 3.648097561865623097e-02, 4.156430303997019336e-02, 4.713892543167989540e-02,
+        5.322460385886412684e-02, 5.983915712308283792e-02, 6.699829390463281224e-02, 7.471548149065050122e-02,
+        8.300185389391494996e-02, 9.186616129460712899e-02, 1.013147618591979452e-01, 1.113516561340355690e-01,
+        1.219785634003157786e-01, 1.331950386328042665e-01, 1.449986280439946752e-01, 1.573850606313672716e-01,
+        1.703484726870446791e-01, 1.838816618814874884e-01, 1.979763672973498048e-01, 2.126235716643688402e-01,
+        2.278138220265254991e-01, 2.435375651517067386e-01, 2.597854941629632707e-01, 2.765489031191654411e-01,
+        2.938200465906351752e-01, 3.115925016510994851e-01, 3.298615301301230823e-01, 3.486244394295739435e-01,
+        3.678809406939879716e-01, 3.876335036292959599e-01, 4.078877077798518471e-01, 4.286525905940105684e-01,
+        4.499409931290513174e-01, 4.717699047639316286e-01, 4.941608088016098926e-01, 5.171400313514193966e-01,
+        5.407390963876342256e-01, 5.649950903858123945e-01, 5.899510404480374918e-01, 6.156563103475134535e-01,
+        6.421670194591982411e-01, 6.695464901047961714e-01, 6.978657294374126896e-01, 7.272039526349696447e-01,
+        7.576491548751669105e-01, 7.892987403432202489e-01, 8.222602173936578230e-01, 8.566519699682320391e-01,
+        8.926041164852169437e-01, 9.302594686857616145e-01, 9.697746043788558519e-01, 1.011321069700320644e+00,
+        1.055086728430498711e+00, 1.101277278143300224e+00, 1.150117955536247302e+00, 1.201855456275760449e+00,
+        1.256760098152647779e+00, 1.315128260359919236e+00, 1.377285136373095709e+00, 1.443587843343442141e+00,
+        1.514428937238563465e+00, 1.590240390338335337e+00, 1.671498096302065311e+00, 1.758726978084942299e+00,
+        1.852506785760205887e+00, 1.953478685110838140e+00, 2.062352754065132708e+00, 2.179916523112736371e+00,
+        2.307044718290330681e+00, 2.444710391817196957e+00, 2.593997656772008968e+00, 2.756116279277535182e+00,
+        2.932418425642610903e+00, 3.124417914187536020e+00, 3.333812383735923205e+00, 3.562508865047068391e+00,
+        3.812653330296280988e+00, 4.086664902155689132e+00, 4.387275531849634155e+00, 4.717576109385405085e+00,
+        5.081070154695596855e+00, 5.481736462718817995e+00, 5.924102347216244340e+00, 6.413329458204850426e+00,
+        6.955314549766230740e+00, 7.556808065486941215e+00, 8.225554008952760095e+00, 8.970455302965185036e+00,
+        9.801769746699598466e+00, 1.073134279679936208e+01, 1.177288477943655549e+01, 1.294230185297226511e+01,
+        1.425809217068106541e+01, 1.574182134943112610e+01, 1.741869467329444792e+01, 1.931824763074534781e+01,
+        2.147518163232618457e+01, 2.393037838236259586e+01, 2.673213477270754163e+01, 2.993767083537830673e+01,
+        3.361497689655818107e+01, 3.784508348524495401e+01, 4.272485990900652026e+01, 4.837047622725585887e+01,
+        5.492170063250241752e+01, 6.254725265973777743e+01, 7.145149574983117631e+01, 8.188283528217430591e+01,
+        9.414429671899321190e+01, 1.086069017070108772e+02, 1.257266497442910506e+02, 1.460661655727672308e+02,
+        1.703224100743601641e+02, 1.993623058409479084e+02, 2.342687403011957198e+02, 2.764002385528330658e+02,
+        3.274687277481591846e+02, 3.896413615832930151e+02, 4.656745019682919178e+02, 5.590908996105107215e+02,
+        6.744152109571297875e+02, 8.174887172033244140e+02, 9.958921680864290197e+02, 1.219517071629880108e+03,
+        1.501341972869855447e+03, 1.858493492282554856e+03, 2.313705362529768409e+03, 2.897337235279879262e+03,
+        3.650185874628374320e+03, 4.627425468074182920e+03, 5.904167858279871204e+03, 7.583363128219763259e+03,
+        9.807105719965428472e+03, 1.277293273832114230e+04, 1.675749596877978193e+04, 2.215121038263169759e+04,
+        2.950937349291504490e+04, 3.962820433513419525e+04, 5.365890489878942635e+04, 7.328024305737981431e+04,
+        1.009620167752942516e+05, 1.403709568321740997e+05, 1.970019955923188504e+05, 2.791695960502382133e+05,
+        3.995801250202947693e+05, 5.778515877588312220e+05, 8.445944401474017243e+05, 1.248092975135001687e+06,
+        1.865367859966950385e+06, 2.820705292493674480e+06, 4.317063433830483499e+06, 6.689961127164684387e+06,
+        1.050111601631327499e+07, 1.670327884792325766e+07, 2.693430470211696200e+07, 4.404906898054894166e+07,
+        7.309535640536363311e+07, 1.231306812701882145e+08, 2.106560568719367745e+08, 3.662073971851359192e+08,
+        6.472124787519330196e+08, 1.163486593592585616e+09, 2.128658395254150452e+09, 3.965732938755983605e+09,
+        7.527735928223242836e+09, 1.456757162128879538e+10, 2.875798636941021041e+10, 5.794999654160054887e+10,
+        1.192767536774485257e+11, 2.509334090779650360e+11, 5.399624414800303207e+11, 1.189276111740286910e+12,
+        2.683103883355551677e+12, 6.205255919751506427e+12, 1.472284072112162717e+13, 3.586628373992547853e+13,
+        8.978594107356889337e+13, 2.311710197091641250e+14, 6.127020712804348908e+14, 1.673232679378485978e+15,
+        4.712671499032329365e+15, 1.370275025680988289e+16, 4.117347054027612886e+16, 1.279822436878842710e+17,
+        4.119762767831332886e+17, 1.374888606936629814e+18, 4.762483833659790733e+18, 1.714288404980390540e+19,
+        6.420200704842635702e+19, 2.504808062315322558e+20, 1.019355251138167687e+21, 4.332952958521756932e+21,
+        1.926416464889827426e+22, 8.971059571108856501e+22, 4.382317748928748816e+23, 2.249003059943548727e+24,
+        1.214458587662725100e+25, 6.911683912813140938e+25, 4.152578123301633020e+26, 2.638346388179288086e+27,
+        1.775811490887700718e+28, 1.268552401544524965e+29, 9.635786341213661742e+29, 7.797939379813000783e+30,
+        6.736900087983560033e+31, 6.226288752443836475e+32, 6.169035287163451891e+33, 6.567250104576983172e+34,
+        7.528666735185428595e+35, 9.316271421365627344e+36, 1.247410737003664698e+38, 1.811787648043939987e+39,
+        2.861918583157116420e+40, 4.929657099622567574e+41, 9.284951278562156071e+42, 1.917687997037326435e+44,
+        4.355948096683946408e+45, 1.091453486585817118e+47, 3.026206402784023251e+48, 9.314478983991942688e+49,
+        3.193195693823940775e+51, 1.223447678968662613e+53, 5.257403184148516426e+54, 2.543108925126136766e+56,
+        1.389947584026783879e+58, 8.616987336205957549e+59, 6.083777056769299984e+61, 4.911841077800001710e+63,
+        4.554259483169784661e+65, 4.870815185962582259e+67, 6.036211886847067841e+69, 8.708377755587698026e+71,
+        1.469655296381977267e+74, 2.915822924489215887e+76, 6.836044306573246016e+78, 1.903917300559946782e+81,
+        6.333813341980360028e+83, 2.531082268773868753e+86, 1.222077360592898816e+89, 7.172167453276776330e+91,
+        5.148160232410244898e+94, 4.548619807672339638e+97, 4.979632843475864923e+100, 6.800802744782331957e+103,
+        1.166855497965918386e+107, 2.533457765534279043e+110, 7.012864641215147208e+113, 2.494083354169569414e+117,
+        1.148722178881219993e+121, 6.908313932158993510e+124, 5.470912484744367184e+128, 5.755359832684120769e+132,
+        8.115681923907451939e+136, 1.548304780334447081e+141, 4.034912159113614601e+145, 1.450632759611715526e+150,
+        7.268799665580789770e+154, };
+
+__constant__ double m_weights_double_8[786] =
+      { 4.901759085947701448e-159, 1.505832423620814399e-156, 4.231872109262999523e-154, 1.089479701785106001e-151,
+        2.572922387150651649e-149, 5.581311054334156941e-147, 1.113575900126970040e-144, 2.046165051332286084e-142,
+        3.466994885004770636e-140, 5.423795404073501922e-138, 7.843833272402847010e-136, 1.049922957933194415e-133,
+        1.302301071957418603e-131, 1.498659737828393008e-129, 1.601906622414286282e-127, 1.592248618401983561e-125,
+        1.473375345916436274e-123, 1.270651551394009593e-121, 1.022408263525766209e-119, 7.683762602329562781e-118,
+        5.399268127233373186e-116, 3.551074274853494676e-114, 2.188235409519121010e-112, 1.264667515430816934e-110,
+        6.861807566737243712e-109, 3.498691686825209963e-107, 1.678016807398375157e-105, 7.577439431441931490e-104,
+        3.224703770159386809e-102, 1.294487090677705963e-100, 4.906133250963454139e-99, 1.757121317988153326e-97,
+        5.952042491454320383e-96, 1.908566653286417264e-94, 5.798224459236429212e-93, 1.670293239978334727e-91,
+        4.566236673398083038e-90, 1.185617342791547945e-88, 2.926160027801296929e-87, 6.870061134126707137e-86,
+        1.535565783500379945e-84, 3.270036736778401257e-83, 6.639558007206580362e-82, 1.286319750967398593e-80,
+        2.379566581139022958e-79, 4.206268231398883425e-78, 7.109719237833379433e-77, 1.149915104115372777e-75,
+        1.780876201255594220e-74, 2.642703796179329883e-73, 3.760085375941719327e-72, 5.132920951124251993e-71,
+        6.727100274601427696e-70, 8.469585621347697498e-69, 1.025032382672232848e-67, 1.193219127557863348e-66,
+        1.336816930381306582e-65, 1.442283479679798385e-64, 1.499374555004793991e-63, 1.502797203133501438e-62,
+        1.453005969318485303e-61, 1.355980448377862540e-60, 1.222072412212552127e-59, 1.064223180270520159e-58,
+        8.959667396075636845e-58, 7.296288808079294105e-57, 5.750255296190181158e-56, 4.388011664829013518e-55,
+        3.243852451291832398e-54, 2.324239357665538806e-53, 1.614869776203026446e-52, 1.088524605545274842e-51,
+        7.121755574192829045e-51, 4.524647662549067074e-50, 2.792730715818793035e-49, 1.675384879603864227e-48,
+        9.773114328777676091e-48, 5.545910766847627082e-47, 3.062809705627873645e-46, 1.646862118038266234e-45,
+        8.625108513887155847e-45, 4.401687663868890701e-44, 2.189755778847646746e-43, 1.062345336449265889e-42,
+        5.028036663485684049e-42, 2.322524635717249223e-41, 1.047406593898341306e-40, 4.613438388449698168e-40,
+        1.985397445118162005e-39, 8.351027367454628343e-39, 3.434440903484543389e-38, 1.381489131877196646e-37,
+        5.437051201310225224e-37, 2.094357548080647717e-36, 7.898676618592006902e-36, 2.917536870947471272e-35,
+        1.055788886022716597e-34, 3.744333812160330812e-34, 1.301801185251957290e-33, 4.438346216893387768e-33,
+        1.484348268951816542e-32, 4.871001129849836971e-32, 1.568903000742513942e-31, 4.961295315917935235e-31,
+        1.540773910027990821e-30, 4.700558022172014910e-30, 1.409115230718949596e-29, 4.151913103955692034e-29,
+        1.202737613715427748e-28, 3.426327374934496736e-28, 9.601405359397026012e-28, 2.647278642033773301e-27,
+        7.183442220565147103e-27, 1.918850545981494042e-26, 5.046974779455992494e-26, 1.307394799925911700e-25,
+        3.336342198236957082e-25, 8.389259581136262194e-25, 2.079051813513548608e-24, 5.079178967243765280e-24,
+        1.223501794357837278e-23, 2.906654911057549530e-23, 6.811668606095015470e-23, 1.574985938238025303e-22,
+        3.593796788969348326e-22, 8.094185411205212564e-22, 1.799796183237481721e-21, 3.951758901641017285e-21,
+        8.569580068050865775e-21, 1.835753486517298696e-20, 3.885414339966022317e-20, 8.126613972895021790e-20,
+        1.680007182889503141e-19, 3.433369351563962828e-19, 6.937695550399427499e-19, 1.386345631008981755e-18,
+        2.740087497759230881e-18, 5.357570288683386626e-18, 1.036464933022803784e-17, 1.984249442010084992e-17,
+        3.759788006060003409e-17, 7.052211261821684795e-17, 1.309635641529546221e-16, 2.408275496109180528e-16,
+        4.385898809611711552e-16, 7.911758686849121285e-16, 1.413883597877183873e-15, 2.503477536644680210e-15,
+        4.392637866550705827e-15, 7.638710306960574612e-15, 1.316703360377476041e-14, 2.250031027275448919e-14,
+        3.812239733412214953e-14, 6.405021660191363479e-14, 1.067250538270319484e-13, 1.763897493784721010e-13,
+        2.891987565334547756e-13, 4.704242520369958085e-13, 7.592878273512691990e-13, 1.216183338372525172e-12,
+        1.933388593436624879e-12, 3.050826852442290751e-12, 4.779080020017636657e-12, 7.432734713385425098e-12,
+        1.147833888125873666e-11, 1.760286160372422754e-11, 2.681071101623953168e-11, 4.056023754295965437e-11,
+        6.095443492241537222e-11, 9.100550129616064211e-11, 1.349993452136967652e-10, 1.989943912395156051e-10,
+        2.914996073619059788e-10, 4.243900781412219621e-10, 6.141353162671391082e-10, 8.834365795894798511e-10,
+        1.263395594025933170e-09, 1.796369250051716047e-09, 2.539704143326480862e-09, 3.570592498287890499e-09,
+        4.992348403150539107e-09, 6.942471870489931483e-09, 9.602949600164561371e-09, 1.321333712761666777e-08,
+        1.808727901635346390e-08, 2.463325364767791516e-08, 3.338047870136870496e-08, 4.501108426108505069e-08,
+        6.039985413333259594e-08, 8.066305374526097834e-08, 1.072181059018892614e-07, 1.418561443795353991e-07,
+        1.868297699836383305e-07, 2.449586539172972009e-07, 3.197559780442760832e-07, 4.155790690867544334e-07,
+        5.378079713325544678e-07, 6.930561064776686194e-07, 8.894175852502122454e-07, 1.136756157868726006e-06,
+        1.447041212534730898e-06, 1.834736645332833504e-06, 2.317248822354253644e-06, 2.915440225825303911e-06,
+        3.654215709863551870e-06, 4.563188576773760151e-06, 5.677433909482232878e-06, 7.038336747307571784e-06,
+        8.694542758083067228e-06, 1.070301902702759858e-05, 1.313023243937403750e-05, 1.605345286789073897e-05,
+        1.956218797728780449e-05, 2.375975591555218862e-05, 2.876500146954361208e-05, 3.471416041263076209e-05,
+        4.176287576185915239e-05, 5.008836848967403773e-05, 5.989176390181730373e-05, 7.140057340280213227e-05,
+        8.487132973049760036e-05, 1.005923719620999934e-04, 1.188867746885496973e-04, 1.401154137398069279e-04,
+        1.646801587388731249e-04, 1.930271805904271778e-04, 2.256503597954330556e-04, 2.630947792533707128e-04,
+        3.059602829980946180e-04, 3.549050801425155303e-04, 4.106493712131842727e-04, 4.739789720708565436e-04,
+        5.457489087697051069e-04, 6.268869550379884668e-04, 7.183970825975973673e-04, 8.213627933082928901e-04,
+        9.369503011517966364e-04, 1.066411531385725184e-03, 1.211086903819095417e-03, 1.372407867107646339e-03,
+        1.551899151252505624e-03, 1.751180706119547318e-03, 1.971969294784470944e-03, 2.216079711850908971e-03,
+        2.485425598581779636e-03, 2.782019828718993257e-03, 3.107974441230220176e-03, 3.465500098895993776e-03,
+        3.856905054613959619e-03, 4.284593610523639393e-03, 4.751064058515097225e-03, 5.258906094345618421e-03,
+        5.810797701414435799e-03, 6.409501504198915943e-03, 7.057860595396970186e-03, 7.758793844909123446e-03,
+        8.515290702888369372e-03, 9.330405513145299523e-03, 1.020725135717912572e-02, 1.114899345297222760e-02,
+        1.215884213639836574e-02, 1.324004545661629463e-02, 1.439588142011718850e-02, 1.562964992113485073e-02,
+        1.694466439888404584e-02, 1.834424326453982033e-02, 1.983170114298836870e-02, 2.141033997615067889e-02,
+        2.308344003609062690e-02, 2.485425089716015368e-02, 2.672598241710042669e-02, 2.870179577730820310e-02,
+        3.078479463239356953e-02, 3.297801641870515720e-02, 3.528442387069167064e-02, 3.770689679281728890e-02,
+        4.024822413326941635e-02, 4.291109640390936770e-02, 4.569809848884132640e-02, 4.861170288163592155e-02,
+        5.165426338866744454e-02, 5.482800933323496446e-02, 5.813504029216542680e-02, 6.157732139347005467e-02,
+        6.515667920037330165e-02, 6.887479820368566403e-02, 7.273321794107712090e-02, 7.673333075835566151e-02,
+        8.087638022439339824e-02, 8.516346020789830747e-02, 8.959551462082867423e-02, 9.417333782991444898e-02,
+        9.889757573450802477e-02, 1.037687275058577967e-01, 1.087871479799008567e-01, 1.139530506928239996e-01,
+        1.192665115459606141e-01, 1.247274730840887416e-01, 1.303357493688843496e-01, 1.360910314271734020e-01,
+        1.419928932517243620e-01, 1.480407983306351483e-01, 1.542341066798992024e-01, 1.605720823524863565e-01,
+        1.670539013962460335e-01, 1.736786602321317742e-01, 1.804453844236544912e-01, 1.873530378080931153e-01,
+        1.944005319598201097e-01, 2.015867359561292115e-01, 2.089104864161762672e-01, 2.163705977840528187e-01,
+        2.239658728275971045e-01, 2.316951133252986765e-01, 2.395571309145607347e-01, 2.475507580756380088e-01,
+        2.556748592267567912e-01, 2.639283419072366399e-01, 2.723101680268593668e-01, 2.808193651612593497e-01,
+        2.894550378747292326e-01, 2.982163790535362503e-01, 3.071026812346166036e-01, 3.161133479163487600e-01,
+        3.252479048399920142e-01, 3.345060112323053140e-01, 3.438874710018250777e-01, 3.533922438832718793e-01, 
+        3.630204565265675291e-01, 3.727724135289699431e-01, 3.826486084108677024e-01, 3.926497345378144818e-01,
+        4.027766959934214472e-01, 4.130306184097598756e-01, 4.234128597639539906e-01, 4.339250211516634154e-01,
+        4.445689575501645526e-01, 4.553467885857401860e-01, 4.662609093220769612e-01, 4.773140010883521767e-01,
+        4.885090423676662636e-01, 4.998493197684479070e-01, 5.113384391034281429e-01, 5.229803366027518117e-01,
+        5.347792902897740156e-01, 5.467399315500809553e-01, 5.588672569262846167e-01, 5.711666401731758417e-01,
+        5.836438446098876156e-01, 5.963050358078278898e-01, 6.091567946552975691e-01, 6.222061308419237716e-01,
+        6.354604968083211637e-01, 6.489278022087558681e-01, 6.626164289370386795e-01, 6.765352467684294227e-01,
+        6.906936296730053994e-01, 7.051014728587479919e-01, 7.197692106055475377e-01, 7.347078349544334315e-01,
+        7.499289153196209421e-01, 7.654446190944464391e-01, 7.812677333259577661e-01, 7.974116875368567865e-01,
+        8.138905777776784362e-01, 8.307191919965581771e-01, 8.479130368187123741e-01, 8.654883658328603475e-01,
+        8.834622094872810766e-01, 9.018524067040521621e-01, 9.206776383262963142e-01, 9.399574625199963151e-01,
+        9.597123522591707284e-01, 9.799637350309700387e-01, 1.000734034905599933e+00, 1.022046717124952010e+00,
+        1.043926335373472893e+00, 1.066398581905185161e+00, 1.089490340711946628e+00, 1.113229743930062164e+00,
+        1.137646231695313314e+00, 1.162770615670420260e+00, 1.188635146483979071e+00, 1.215273585336112390e+00,
+        1.242721280043529050e+00, 1.271015245815510799e+00, 1.300194251072644711e+00, 1.330298908642019971e+00,
+        1.361371772686240192e+00, 1.393457441749111730e+00, 1.426602668328411758e+00, 1.460856475415888358e+00,
+        1.496270280476785338e+00, 1.532898027375920169e+00, 1.570796326794896619e+00, 1.610024605725646420e+00,
+        1.650645266669431435e+00, 1.692723857217988332e+00, 1.736329250744977731e+00, 1.781533838991654903e+00,
+        1.828413737391087381e+00, 1.877049004040720448e+00, 1.927523873304087635e+00, 1.979927005099477087e+00,
+        2.034351751016940433e+00, 2.090896438495766214e+00, 2.149664674393090421e+00, 2.210765669381402212e+00,
+        2.274314584729113927e+00, 2.340432903144970240e+00, 2.409248825504827076e+00, 2.480897695429288043e+00,
+        2.555522453844001656e+00, 2.633274125832370887e+00, 2.714312342284411608e+00, 2.798805899057066353e+00,
+        2.886933356592141886e+00, 2.978883683190077867e+00, 3.074856945413050211e+00, 3.175065049391765683e+00,
+        3.279732537139255280e+00, 3.389097442334834102e+00, 3.503412210435275865e+00, 3.622944688401595705e+00,
+        3.747979189802462585e+00, 3.878817641573403805e+00, 4.015780819279312670e+00, 4.159209678351536168e+00,
+        4.309466789455788368e+00, 4.466937886899736897e+00, 4.632033539816493591e+00, 4.805190956770360727e+00,
+        4.986875935432896972e+00, 5.177584970080537688e+00, 5.377847530880629761e+00, 5.588228530273088035e+00,
+        5.809330993233640059e+00, 6.041798949837089488e+00, 6.286320570342285919e+00, 6.543631565013652661e+00,
+        6.814518873098582608e+00, 7.099824667819718682e+00, 7.400450706942931008e+00, 7.717363061475788814e+00,
+        8.051597258371279584e+00, 8.404263876795383951e+00, 8.776554641607500109e+00, 9.169749062247565207e+00,
+        9.585221670276993889e+00, 1.002444991444300704e+01, 1.048902277839603856e+01, 1.098065019316492606e+01,
+        1.150117332427169985e+01, 1.205257582204547280e+01, 1.263699613338454324e+01, 1.325674098404332380e+01,
+        1.391430015262873368e+01, 1.461236267104086712e+01, 1.535383460126837531e+01, 1.614185855545811846e+01,
+        1.697983514525758524e+01, 1.787144656784601339e+01, 1.882068256013178484e+01, 1.983186897964764985e+01,
+        2.090969930111845450e+01, 2.205926935196095527e+01, 2.328611564861881683e+01, 2.459625773922860138e+01,
+        2.599624500732998276e+01, 2.749320844694889238e+01, 2.909491798228195984e+01, 3.080984597641076715e+01,
+        3.264723765414180400e+01, 3.461718925554321861e+01, 3.673073484057443067e+01, 3.899994278315456980e+01,
+        4.143802312713618427e+01, 4.405944712930142330e+01, 4.688008048840357439e+01, 4.991733195758662298e+01,
+        5.319031926387298369e+01, 5.672005451703465811e+01, 6.052965158594831140e+01, 6.464455825915836491e+01,
+        6.909281639443131774e+01, 7.390535370725211687e+01, 7.911631135942343489e+01, 8.476341209659472308e+01,
+        9.088837435982152722e+01, 9.753737857533253823e+01, 1.047615927251647361e+02, 1.126177653386554197e+02,
+        1.211688952437418817e+02, 1.304849888043593828e+02, 1.406439169773708701e+02, 1.517323863863765989e+02,
+        1.638470407739824279e+02, 1.770957117100033620e+02, 1.915988403612775885e+02, 2.074910955409497265e+02,
+        2.249232172361061194e+02, 2.440641194630869936e+02, 2.651032917390266964e+02, 2.882535448280364212e+02,
+        3.137541538897424513e+02, 3.418744609277612322e+02, 3.729180087461214321e+02, 4.072272907593818790e+02,
+        4.451892153103389878e+02, 4.872414000388630927e+02, 5.338794318098249932e+02, 5.856652513400113117e+02,
+        6.432368496766822816e+02, 7.073194969336578611e+02, 7.787387632221277236e+02, 8.584356387770406827e+02,
+        9.474841163944599543e+02, 1.047111666301969297e+03, 1.158723113719277435e+03, 1.283928525349707755e+03,
+        1.424575826189363437e+03, 1.582789006393775706e+03, 1.761012944445459235e+03, 1.962066073573121788e+03,
+        2.189202360708354222e+03, 2.446184360349559652e+03, 2.737369460761187093e+03, 3.067811870808767638e+03,
+        3.443383419509962754e+03, 3.870916878218207705e+03, 4.358376293464465508e+03, 4.915059769420260559e+03,
+        5.551841303216967404e+03, 6.281459704453426129e+03, 7.118864385205665710e+03, 8.081629967627799596e+03,
+        9.190454321738597280e+03, 1.046975794051835702e+04, 1.194840663946247320e+04, 1.366058463062104793e+04,
+        1.564685131637809273e+04, 1.795542299179967539e+04, 2.064373043744082514e+04, 2.378031563732670807e+04,
+        2.744714621995650953e+04, 3.174244552480722739e+04, 3.678416050731336226e+04, 4.271422037773508051e+04,
+        4.970377768100323981e+04, 5.795967273138576164e+04, 6.773242484608792593e+04, 7.932613346949942761e+04,
+        9.311077397156915450e+04, 1.095375030536372224e+05, 1.291577556735669526e+05, 1.526471301608741586e+05,
+        1.808353350969648289e+05, 2.147438294770164181e+05, 2.556332515573999948e+05, 3.050633345562097502e+05,
+        3.649687926665853954e+05, 4.377556866857485380e+05, 5.264241222943208736e+05, 6.347248990108319410e+05,
+        7.673600526542426466e+05, 9.302403050337502786e+05, 1.130816502666451845e+06, 1.378507531155523742e+06,
+        1.685254393964162275e+06, 2.066239770168639390e+06, 2.540825270229354918e+06, 3.133775962036416630e+06,
+        3.876865148275802393e+06, 4.810984054018349430e+06, 5.988924089534678664e+06, 7.479057929608060924e+06,
+        9.370225698693408867e+06, 1.177824230977510661e+07, 1.485459301432580619e+07, 1.879809270383398104e+07,
+        2.387057334436346400e+07, 3.041806552258603202e+07, 3.889950046843262151e+07, 4.992574374586696017e+07,
+        6.431287504495613210e+07, 8.315518519925858136e+07, 1.079255664704117961e+08, 1.406141073390035115e+08,
+        1.839201785677305607e+08, 2.415197116904975365e+08, 3.184386015381112281e+08, 4.215765018929686736e+08,
+        5.604446356915114550e+08, 7.482094398046911572e+08, 1.003175129668246151e+09, 1.350898918997482870e+09,
+        1.827222165053491590e+09, 2.482633480831760933e+09, 3.388577637234919719e+09, 4.646620065299105644e+09,
+        6.401821801566297122e+09, 8.862352038053251473e+09, 1.232838602859196811e+10, 1.723489297480180023e+10,
+        2.421530528469447376e+10, 3.419673813208063025e+10, 4.854312364622606540e+10, 6.927149043760342676e+10,
+        9.938049490186203616e+10, 1.433521424759854145e+11, 2.079221734483088227e+11, 3.032695241820108158e+11,
+        4.448631503727710431e+11, 6.563458646477901051e+11, 9.740635696398910980e+11, 1.454220520059656158e+12,
+        2.184250688898627320e+12, 3.300999104757560757e+12, 5.019970485022749012e+12, 7.682676299017607834e+12,
+        1.183376596003983872e+13, 1.834748853557035315e+13, 2.863639312458363586e+13, 4.499803892715039958e+13,
+        7.119486876989154498e+13, 1.134307017980122346e+14, 1.820065782363618395e+14, 2.941484500615394037e+14,
+        4.788707305890930382e+14, 7.854025036928623551e+14, 1.297894304619860251e+15, 2.161279954782425640e+15,
+        3.627102147035003834e+15, 6.135342933440950378e+15, 1.046170006362244506e+16, 1.798477357839665686e+16,
+        3.117473412332331475e+16, 5.449445073049184222e+16, 9.607515505017978212e+16, 1.708589224452677852e+17,
+        3.065429751110228665e+17, 5.549227437451149511e+17, 1.013730232778046314e+18, 1.869059895876405824e+18,
+        3.478549552381578424e+18, 6.535992245975463763e+18, 1.240019272261066308e+19, 2.375828866910936629e+19,
+        4.597682433604432625e+19, 8.988106816837128428e+19, 1.775302379393632263e+20, 3.543413304390973486e+20,
+        7.148061397675525327e+20, 1.457620510577186305e+21, 3.005137124879829797e+21, 6.265024861633250697e+21,
+        1.320979941090283816e+22, 2.817487535902146221e+22, 6.079933041429805231e+22, 1.327658853647212083e+23,
+        2.934311759183641318e+23, 6.565087216807130026e+23, 1.487212273437937650e+24, 3.411840196076788128e+24,
+        7.928189928797018762e+24, 1.866451877029704857e+25, 4.452521859886739549e+25, 1.076545435174977662e+26,
+        2.638685681190697586e+26, 6.557908470244186498e+26, 1.652952243735585721e+27, 4.226383395914916199e+27,
+        1.096450394268080148e+28, 2.886822082999286080e+28, 7.715480389344015925e+28, 2.093728789309964846e+29,
+        5.770275789447655037e+29, 1.615463845391781140e+30, 4.595470055795608691e+30, 1.328629392686523255e+31,
+        3.905079681530784219e+31, 1.167134024271997252e+32, 3.548058538654277403e+32, 1.097378059358046160e+33,
+        3.454102978064445595e+33, 1.106745393701652323e+34, 3.610899559139069994e+34, 1.199946999283670567e+35,
+        4.062687014190878792e+35, 1.401835223893224514e+36, 4.931085527333162173e+36, 1.768812393284919500e+37,
+        6.472148293945199961e+37, 2.416453721739211922e+38, 9.208944720398123862e+38, 3.583297028622126676e+39,
+        1.424097482596699440e+40, 5.782627833426411524e+40, 2.399862204084363183e+41, 1.018291572042305460e+42,
+        4.419105414822034531e+42, 1.962126117680499311e+43, 8.916742424061253707e+43, 4.148882478294757720e+44,
+        1.977256529558276930e+45, 9.655300233875401080e+45, 4.832878898335598922e+46, 2.480575878223098058e+47,
+        1.306102809757654706e+48, 7.057565717289569232e+48, 3.915276522229618618e+49, 2.230898980943393318e+50,
+        1.306141334496309306e+51, 7.861021286656392627e+51, 4.865583758538451107e+52, 3.098487425915704674e+53,
+        2.031037614862563901e+54, 1.370999647608260200e+55, 9.534736274325001528e+55, 6.834959923166415407e+56,
+        5.052733546324789020e+57, 3.853810997282159979e+58, 3.034183107853208298e+59, 2.467161926009838899e+60,
+        2.072901039813580593e+61, 1.800563980579615383e+62, 1.617764027895344257e+63, 1.504283028250688329e+64,
+        1.448393206525427172e+65, 1.444855510980115799e+66, 1.494120428855029243e+67, 1.602566566107015722e+68,
+        1.783880504153942988e+69, 2.061999240572760738e+70, 2.476521794698572715e+71, 3.092349914153497358e+72,
+        4.016927238305985810e+73, 5.431607545226497387e+74, 7.650086824042822759e+75, 1.123017984114349288e+77,
+        1.719382952966052004e+78, 2.747335718690686674e+79, 4.584545010557684123e+80, 7.995082041539250252e+81,
+        1.458119909365899044e+83, 2.783001178679600175e+84, 5.562812231966194628e+85, 1.165338768982404578e+87,
+        2.560399126432838224e+88, 5.904549641859098192e+89, 1.430278474749838710e+91, 3.642046122956932563e+92,
+        9.756698571206402300e+93, 2.751946044275883051e+95, 8.179164793643197279e+96, 2.563704735086825890e+98,
+        8.481656496128255880e+99, 2.964260254403981007e+101, 1.095342970031208886e+103, 4.283148547584870628e+104,
+        1.773954352944319744e+106, 7.788991081894224760e+107, 3.628931721056821352e+109, 1.795729272516020592e+111,
+        9.446685151482835339e+112, 5.288263179614488101e+114, 3.153311236741401362e+116, 2.004807079683827669e+118,
+        1.360407192665237716e+120, 9.862825609807810517e+121, 7.647551788591128099e+123, 6.348802224871730088e+125,
+        5.649062361980019098e+127, 5.393248003523784781e+129, 5.530897191915703916e+131, 6.099598644640894333e+133,
+        7.242098433491964504e+135, 9.268083053637375570e+137, 1.279942702416040582e+140, 1.909796626960621302e+142,
+        3.082540300669885040e+144, 5.388809732384179657e+146, 1.021610251056626535e+149, 2.103005440072790650e+151,
+        4.706753990348725570e+153, 1.146834128125248991e+156, };
+
+__constant__ double* m_weights_double[8] = {
+    m_weights_double_1,
+    m_weights_double_2,
+    m_weights_double_3,
+    m_weights_double_4,
+    m_weights_double_5,
+    m_weights_double_6,
+    m_weights_double_7,
+    m_weights_double_8
+};
+
+__constant__ boost::math::size_t float_coefficients_size[8] = {9, 8, 16, 33, 66, 132, 263, 527};
+
+__constant__ boost::math::size_t double_coefficients_size[8] = {13, 12, 25, 49, 98, 196, 393, 786};
+
+template<typename T>
+struct coefficients_selector;
+
+template<>
+struct coefficients_selector<float>
+{
+    __device__ static const auto abscissas() { return m_abscissas_float; }
+    __device__ static const auto weights() { return m_weights_float; }
+    __device__ static const auto size() { return float_coefficients_size; }
+};
+
+template<>
+struct coefficients_selector<double>
+{
+    __device__ static const auto abscissas() { return m_abscissas_double; }
+    __device__ static const auto weights() { return m_weights_double; }
+    __device__ static const auto size() { return double_coefficients_size; }
+};
+
+
+template <typename F, typename Real, typename Policy = policies::policy<> >
+__device__ auto exp_sinh_integrate_impl(const F& f, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+{
+    using K = decltype(f(static_cast<Real>(0)));
+    using boost::math::constants::half;
+    using boost::math::constants::half_pi;
+
+   // This provided a nice error message for real valued integrals, but it's super awkward for complex-valued integrals:
+   /*K y_max = f(tools::max_value<Real>());
+   if(abs(y_max) > tools::epsilon<Real>() || !(boost::math::isfinite)(y_max))
+   {
+       K val = abs(y_max);
+       return static_cast<K>(policies::raise_domain_error(function, "The function you are trying to integrate does not go to zero at infinity, and instead evaluates to %1%", val, Policy()));
+   }*/
+
+   //std::cout << std::setprecision(5*std::numeric_limits<Real>::digits10);
+
+    // Get the party started with two estimates of the integral:
+    const auto m_abscissas = coefficients_selector<Real>::abscissas();
+    const auto m_weights = coefficients_selector<Real>::weights();
+    const auto m_size = coefficients_selector<Real>::size();
+    
+    Real min_abscissa{ 0 }, max_abscissa{ boost::math::tools::max_value<Real>() };
+    K I0 = 0;
+    Real L1_I0 = 0;
+    for(boost::math::size_t i = 0; i < m_size[0]; ++i)
+    {
+        K y = f(m_abscissas[0][i]);
+        K I0_last = I0;
+        I0 += y*m_weights[0][i];
+        L1_I0 += abs(y)*m_weights[0][i];
+        if ((I0_last == I0) && (abs(I0) != 0))
+        {
+           max_abscissa = m_abscissas[0][i];
+           break;
+        }
+    }
+
+    //std::cout << "First estimate : " << I0 << std::endl;
+    K I1 = I0;
+    Real L1_I1 = L1_I0;
+    bool have_first_j = false;
+    boost::math::size_t first_j = 0;
+    for (boost::math::size_t i = 0; (i < m_size[1]) && (m_abscissas[1][i] < max_abscissa); ++i)
+    {
+        K y = f(m_abscissas[1][i]);
+        K I1_last = I1;
+        I1 += y*m_weights[1][i];
+        L1_I1 += abs(y)*m_weights[1][i];
+        if (!have_first_j && (I1_last == I1))
+        {
+           // No change to the sum, disregard these values on the LHS:
+           if ((i < m_size[1] - 1) && (m_abscissas[1][i + 1] > max_abscissa))
+           {
+              // The summit is so high, that we found nothing in this row which added to the integral!!
+              have_first_j = true;
+           }
+           else
+           {
+              min_abscissa = m_abscissas[1][i];
+              first_j = i;
+           }
+        }
+        else
+        {
+           have_first_j = true;
+        }
+    }
+
+    if (I0 == static_cast<Real>(0))
+    {
+       // We failed to find anything, is the integral zero, or have we just not found it yet?
+       // We'll try one more level, if that still finds nothing then it'll terminate.
+       min_abscissa = 0;
+       max_abscissa = boost::math::tools::max_value<Real>();
+    }
+
+    I1 *= half<Real>();
+    L1_I1 *= half<Real>();
+    Real err = abs(I0 - I1);
+    //std::cout << "Second estimate: " << I1 << " Error estimate at level " << 1 << " = " << err << std::endl;
+
+    boost::math::size_t i = 2;
+    for(; i < 8U; ++i) // Magic number 8 is the number of precomputed levels
+    {
+        I0 = I1;
+        L1_I0 = L1_I1;
+
+        I1 = half<Real>()*I0;
+        L1_I1 = half<Real>()*L1_I0;
+        Real h = static_cast<Real>(1)/static_cast<Real>(1 << i);
+        K sum = 0;
+        Real absum = 0;
+
+        auto& abscissas_row = m_abscissas[i];
+        auto& weight_row = m_weights[i];
+
+        // appoximate location to start looking for lowest meaningful abscissa value
+        first_j = first_j == 0 ? 0 : 2 * first_j - 1;  
+        
+        boost::math::size_t j = first_j;
+        while (abscissas_row[j] < min_abscissa)
+        {
+           ++j;
+        }
+
+        for(; (j < m_size[i]) && (abscissas_row[j] < max_abscissa); ++j)
+        {
+            Real x = abscissas_row[j];
+            K y = f(x);
+            sum += y*weight_row[j];
+            Real abterm0 = abs(y)*weight_row[j];
+            absum += abterm0;
+        }
+
+        I1 += sum*h;
+        L1_I1 += absum*h;
+        err = abs(I0 - I1);
+        if (!(boost::math::isfinite)(L1_I1))
+        {
+            return static_cast<K>(policies::raise_evaluation_error("exp_sinh_integrate", "The exp_sinh quadrature evaluated your function at a singular point and returned %1%. Please ensure your function evaluates to a finite number over its entire domain.", I1, Policy()));
+        }
+        if (err <= tolerance*L1_I1)
+        {
+            break;
+        }
+    }
+
+    if (error)
+    {
+        *error = err;
+    }
+
+    if(L1)
+    {
+        *L1 = L1_I1;
+    }
+
+    if (levels)
+    {
+       *levels = i;
+    }
+
+    return I1;
+}
+
+} // namespace detail
+} // namespace quadrature
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
+#endif // BOOST_MATH_QUADRATURE_DETAIL_EXP_SINH_DETAIL_HPP
diff --git a/include/boost/math/quadrature/detail/sinh_sinh_detail.hpp b/include/boost/math/quadrature/detail/sinh_sinh_detail.hpp
index a9e1ef4931..7f7477a6e6 100644
--- a/include/boost/math/quadrature/detail/sinh_sinh_detail.hpp
+++ b/include/boost/math/quadrature/detail/sinh_sinh_detail.hpp
@@ -1,4 +1,5 @@
 // Copyright Nick Thompson, 2017
+// Copyright Matt Borland, 2024
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -7,6 +8,10 @@
 #ifndef BOOST_MATH_QUADRATURE_DETAIL_SINH_SINH_DETAIL_HPP
 #define BOOST_MATH_QUADRATURE_DETAIL_SINH_SINH_DETAIL_HPP
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <string>
 #include <vector>
@@ -15,7 +20,6 @@
 #include <boost/math/tools/atomic.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/trunc.hpp>
-#include <boost/math/tools/config.hpp>
 
 #ifdef BOOST_MATH_HAS_THREADS
 #include <mutex>
@@ -485,4 +489,865 @@ void sinh_sinh_detail<Real, Policy>::init(const std::integral_constant<int, 4>&)
 #endif
 
 }}}}
-#endif
+
+#endif // BOOST_MATH_HAS_NVRTC
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/special_functions/fpclassify.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+namespace boost { 
+namespace math { 
+namespace quadrature {
+namespace detail {
+
+__constant__ float m_abscissas_float_1[4] = 
+      { 3.08828742e+00f, 1.48993185e+02f, 3.41228925e+06f, 2.06932577e+18f, };
+
+__constant__ float m_abscissas_float_2[4] =
+      { 9.13048763e-01f, 1.41578929e+01f, 6.70421552e+03f, 9.64172533e+10f, };
+
+__constant__ float m_abscissas_float_3[8] =
+      { 4.07297690e-01f, 1.68206671e+00f, 6.15089799e+00f, 4.00396235e+01f, 7.92920025e+02f, 1.02984971e+05f, 
+        3.03862311e+08f, 1.56544547e+14f, };
+
+__constant__ float m_abscissas_float_4[16] =
+      { 1.98135272e-01f, 6.40155674e-01f, 1.24892870e+00f, 2.26608084e+00f, 4.29646270e+00f, 9.13029039e+00f, 
+        2.31110765e+01f, 7.42770603e+01f, 3.26720921e+02f, 2.15948569e+03f, 2.41501526e+04f, 5.31819400e+05f, 
+        2.80058686e+07f, 4.52406508e+09f, 3.08561257e+12f, 1.33882673e+16f, };
+
+__constant__ float m_abscissas_float_5[32] =
+      { 9.83967894e-02f, 3.00605618e-01f, 5.19857979e-01f, 7.70362083e-01f, 1.07131137e+00f, 1.45056976e+00f, 
+        1.95077855e+00f, 2.64003177e+00f, 3.63137237e+00f, 5.11991533e+00f, 7.45666098e+00f, 1.13022613e+01f, 
+        1.79641069e+01f, 3.01781070e+01f, 5.40387580e+01f, 1.04107731e+02f, 2.18029520e+02f, 5.02155699e+02f, 
+        1.28862131e+03f, 3.73921687e+03f, 1.24750730e+04f, 4.87639975e+04f, 2.28145658e+05f, 1.30877796e+06f, 
+        9.46084663e+06f, 8.88883120e+07f, 1.12416883e+09f, 1.99127673e+10f, 5.16743469e+11f, 2.06721881e+13f, 
+        1.35061503e+15f, 1.53854066e+17f, };
+
+__constant__ float m_abscissas_float_6[65] =
+      { 4.91151004e-02f, 1.48013150e-01f, 2.48938814e-01f, 3.53325424e-01f, 4.62733557e-01f, 5.78912068e-01f,
+        7.03870253e-01f, 8.39965859e-01f, 9.90015066e-01f, 1.15743257e+00f, 1.34641276e+00f, 1.56216711e+00f, 
+        1.81123885e+00f, 2.10192442e+00f, 2.44484389e+00f, 2.85372075e+00f, 3.34645891e+00f, 3.94664582e+00f, 
+        4.68567310e+00f, 5.60576223e+00f, 6.76433234e+00f, 8.24038318e+00f, 1.01439436e+01f, 1.26302471e+01f,
+        1.59213040e+01f, 2.03392186e+01f, 2.63584645e+01f, 3.46892633e+01f, 4.64129147e+01f, 6.32055079e+01f,
+        8.77149726e+01f, 1.24209693e+02f, 1.79718635e+02f, 2.66081728e+02f, 4.03727303e+02f, 6.28811307e+02f,
+        1.00707984e+03f, 1.66156823e+03f, 2.82965144e+03f, 4.98438627e+03f, 9.10154693e+03f, 1.72689266e+04f,
+        3.41309958e+04f, 7.04566898e+04f, 1.52340422e+05f, 3.46047978e+05f, 8.28472421e+05f, 2.09759615e+06f,
+        5.63695080e+06f, 1.61407141e+07f, 4.94473068e+07f, 1.62781052e+08f, 5.78533297e+08f, 2.23083854e+09f,
+        9.38239131e+09f, 4.32814954e+10f, 2.20307274e+11f, 1.24524507e+12f, 7.86900053e+12f, 5.59953143e+13f,
+        4.52148695e+14f, 4.17688952e+15f, 4.45286776e+16f, 5.52914285e+17f, 8.07573252e+18f, };
+
+__constant__ float m_abscissas_float_7[129] =
+      { 2.45471558e-02f, 7.37246687e-02f, 1.23152531e-01f, 1.73000138e-01f, 2.23440665e-01f, 2.74652655e-01f, 
+        3.26821679e-01f, 3.80142101e-01f, 4.34818964e-01f, 4.91070037e-01f, 5.49128046e-01f, 6.09243132e-01f,
+        6.71685571e-01f, 7.36748805e-01f, 8.04752842e-01f, 8.76048080e-01f, 9.51019635e-01f, 1.03009224e+00f,
+        1.11373586e+00f, 1.20247203e+00f, 1.29688123e+00f, 1.39761124e+00f, 1.50538689e+00f, 1.62102121e+00f,
+        1.74542840e+00f, 1.87963895e+00f, 2.02481711e+00f, 2.18228138e+00f, 2.35352849e+00f, 2.54026147e+00f,
+        2.74442267e+00f, 2.96823279e+00f, 3.21423687e+00f, 3.48535896e+00f, 3.78496698e+00f, 4.11695014e+00f,
+        4.48581137e+00f, 4.89677825e+00f, 5.35593629e+00f, 5.87038976e+00f, 6.44845619e+00f, 7.09990245e+00f,
+        7.83623225e+00f, 8.67103729e+00f, 9.62042778e+00f, 1.07035620e+01f, 1.19433001e+01f, 1.33670142e+01f,
+        1.50075962e+01f, 1.69047155e+01f, 1.91063967e+01f, 2.16710044e+01f, 2.46697527e+01f, 2.81898903e+01f,
+        3.23387613e+01f, 3.72490076e+01f, 4.30852608e+01f, 5.00527965e+01f, 5.84087761e+01f, 6.84769282e+01f,
+        8.06668178e+01f, 9.54992727e+01f, 1.13640120e+02f, 1.35945194e+02f, 1.63520745e+02f, 1.97804969e+02f,
+        2.40678754e+02f, 2.94617029e+02f, 3.62896953e+02f, 4.49886178e+02f, 5.61444735e+02f, 7.05489247e+02f,
+        8.92790773e+02f, 1.13811142e+03f, 1.46183599e+03f, 1.89233262e+03f, 2.46939604e+03f, 3.24931157e+03f,
+        4.31236711e+03f, 5.77409475e+03f, 7.80224724e+03f, 1.06426753e+04f, 1.46591538e+04f, 2.03952854e+04f,
+        2.86717062e+04f, 4.07403376e+04f, 5.85318231e+04f, 8.50568927e+04f, 1.25064927e+05f, 1.86137394e+05f,
+        2.80525578e+05f, 4.28278249e+05f, 6.62634051e+05f, 1.03944324e+06f, 1.65385743e+06f, 2.67031565e+06f,
+        4.37721203e+06f, 7.28807171e+06f, 1.23317299e+07f, 2.12155729e+07f, 3.71308625e+07f, 6.61457938e+07f,
+        1.20005529e+08f, 2.21862941e+08f, 4.18228294e+08f, 8.04370413e+08f, 1.57939299e+09f, 3.16812242e+09f,
+        6.49660681e+09f, 1.36285199e+10f, 2.92686390e+10f, 6.43979867e+10f, 1.45275523e+11f, 3.36285446e+11f,
+        7.99420279e+11f, 1.95326423e+12f, 4.90958187e+12f, 1.27062273e+13f, 3.38907099e+13f, 9.32508403e+13f,
+        2.64948942e+14f, 7.78129518e+14f, 2.36471505e+15f, 7.44413803e+15f, 2.43021724e+16f, 8.23706864e+16f,
+        2.90211705e+17f, 1.06415768e+18f, 4.06627711e+18f, };
+
+__constant__ float m_abscissas_float_8[259] =
+      { 1.22722792e-02f, 3.68272289e-02f, 6.14133763e-02f, 8.60515971e-02f, 1.10762884e-01f, 1.35568393e-01f,
+        1.60489494e-01f, 1.85547813e-01f, 2.10765290e-01f, 2.36164222e-01f, 2.61767321e-01f, 2.87597761e-01f,
+        3.13679240e-01f, 3.40036029e-01f, 3.66693040e-01f, 3.93675878e-01f, 4.21010910e-01f, 4.48725333e-01f,
+        4.76847237e-01f, 5.05405685e-01f, 5.34430786e-01f, 5.63953775e-01f, 5.94007101e-01f, 6.24624511e-01f,
+        6.55841151e-01f, 6.87693662e-01f, 7.20220285e-01f, 7.53460977e-01f, 7.87457528e-01f, 8.22253686e-01f,
+        8.57895297e-01f, 8.94430441e-01f, 9.31909591e-01f, 9.70385775e-01f, 1.00991475e+00f, 1.05055518e+00f,
+        1.09236885e+00f, 1.13542087e+00f, 1.17977990e+00f, 1.22551840e+00f, 1.27271289e+00f, 1.32144424e+00f,
+        1.37179794e+00f, 1.42386447e+00f, 1.47773961e+00f, 1.53352485e+00f, 1.59132774e+00f, 1.65126241e+00f,
+        1.71344993e+00f, 1.77801893e+00f, 1.84510605e+00f, 1.91485658e+00f, 1.98742510e+00f, 2.06297613e+00f,
+        2.14168493e+00f, 2.22373826e+00f, 2.30933526e+00f, 2.39868843e+00f, 2.49202464e+00f, 2.58958621e+00f,
+        2.69163219e+00f, 2.79843963e+00f, 2.91030501e+00f, 3.02754584e+00f, 3.15050230e+00f, 3.27953915e+00f,
+        3.41504770e+00f, 3.55744805e+00f, 3.70719145e+00f, 3.86476298e+00f, 4.03068439e+00f, 4.20551725e+00f,
+        4.38986641e+00f, 4.58438376e+00f, 4.78977239e+00f, 5.00679110e+00f, 5.23625945e+00f, 5.47906320e+00f,
+        5.73616037e+00f, 6.00858792e+00f, 6.29746901e+00f, 6.60402117e+00f, 6.92956515e+00f, 7.27553483e+00f,
+        7.64348809e+00f, 8.03511888e+00f, 8.45227058e+00f, 8.89695079e+00f, 9.37134780e+00f, 9.87784877e+00f,
+        1.04190601e+01f, 1.09978298e+01f, 1.16172728e+01f, 1.22807990e+01f, 1.29921443e+01f, 1.37554055e+01f,
+        1.45750793e+01f, 1.54561061e+01f, 1.64039187e+01f, 1.74244972e+01f, 1.85244301e+01f, 1.97109839e+01f,
+        2.09921804e+01f, 2.23768845e+01f, 2.38749023e+01f, 2.54970927e+01f, 2.72554930e+01f, 2.91634608e+01f,
+        3.12358351e+01f, 3.34891185e+01f, 3.59416839e+01f, 3.86140099e+01f, 4.15289481e+01f, 4.47120276e+01f,
+        4.81918020e+01f, 5.20002465e+01f, 5.61732106e+01f, 6.07509371e+01f, 6.57786566e+01f, 7.13072704e+01f,
+        7.73941341e+01f, 8.41039609e+01f, 9.15098607e+01f, 9.96945411e+01f, 1.08751694e+02f, 1.18787600e+02f,
+        1.29922990e+02f, 1.42295202e+02f, 1.56060691e+02f, 1.71397955e+02f, 1.88510933e+02f, 2.07632988e+02f,
+        2.29031559e+02f, 2.53013612e+02f, 2.79932028e+02f, 3.10193130e+02f, 3.44265522e+02f, 3.82690530e+02f,
+        4.26094527e+02f, 4.75203518e+02f, 5.30860437e+02f, 5.94045681e+02f, 6.65901543e+02f, 7.47761337e+02f,
+        8.41184173e+02f, 9.47996570e+02f, 1.07034233e+03f, 1.21074246e+03f, 1.37216724e+03f, 1.55812321e+03f,
+        1.77275819e+03f, 2.02098849e+03f, 2.30865326e+03f, 2.64270219e+03f, 3.03142418e+03f, 3.48472668e+03f,
+        4.01447750e+03f, 4.63492426e+03f, 5.36320995e+03f, 6.22000841e+03f, 7.23030933e+03f, 8.42439022e+03f,
+        9.83902287e+03f, 1.15189746e+04f, 1.35188810e+04f, 1.59055875e+04f, 1.87610857e+04f, 2.21862046e+04f,
+        2.63052621e+04f, 3.12719440e+04f, 3.72767546e+04f, 4.45564828e+04f, 5.34062659e+04f, 6.41950058e+04f,
+        7.73851264e+04f, 9.35579699e+04f, 1.13446538e+05f, 1.37977827e+05f, 1.68327749e+05f, 2.05992575e+05f,
+        2.52882202e+05f, 3.11442272e+05f, 3.84814591e+05f, 4.77048586e+05f, 5.93380932e+05f, 7.40606619e+05f,
+        9.27573047e+05f, 1.16584026e+06f, 1.47056632e+06f, 1.86169890e+06f, 2.36558487e+06f, 3.01715270e+06f,
+        3.86288257e+06f, 4.96486431e+06f, 6.40636283e+06f, 8.29948185e+06f, 1.07957589e+07f, 1.41008733e+07f,
+        1.84951472e+07f, 2.43622442e+07f, 3.22295113e+07f, 4.28249388e+07f, 5.71579339e+07f, 7.66343793e+07f,
+        1.03221273e+08f, 1.39683399e+08f, 1.89925150e+08f, 2.59486540e+08f, 3.56266474e+08f, 4.91582541e+08f,
+        6.81731647e+08f, 9.50299811e+08f, 1.33159830e+09f, 1.87580198e+09f, 2.65667391e+09f, 3.78324022e+09f,
+        5.41753185e+09f, 7.80169537e+09f, 1.12996537e+10f, 1.64614916e+10f, 2.41235400e+10f, 3.55648690e+10f,
+        5.27534501e+10f, 7.87357211e+10f, 1.18256902e+11f, 1.78754944e+11f, 2.71963306e+11f, 4.16512215e+11f,
+        6.42178186e+11f, 9.96872550e+11f, 1.55821233e+12f, 2.45280998e+12f, 3.88865623e+12f, 6.20986899e+12f,
+        9.98992422e+12f, 1.61915800e+13f, 2.64432452e+13f, 4.35201885e+13f, 7.21888469e+13f, 1.20699764e+14f,
+        2.03448372e+14f, 3.45755310e+14f, 5.92524851e+14f, 1.02405779e+15f, 1.78517405e+15f, 3.13930699e+15f,
+        5.56985627e+15f, 9.97176335e+15f, 1.80168749e+16f, 3.28570986e+16f, 6.04901854e+16f, 1.12437528e+17f,
+        2.11044513e+17f, 4.00073701e+17f, 7.66084936e+17f, 1.48201877e+18f, 2.89694543e+18f, 5.72279017e+18f,
+        1.14268996e+19f, };
+
+__constant__ float* m_abscissas_float[8] = {
+    m_abscissas_float_1,
+    m_abscissas_float_2,
+    m_abscissas_float_3,
+    m_abscissas_float_4,
+    m_abscissas_float_5,
+    m_abscissas_float_6,
+    m_abscissas_float_7,
+    m_abscissas_float_8,
+};
+
+__constant__ float m_weights_float_1[4] = 
+      { 7.86824160e+00f, 8.80516388e+02f, 5.39627832e+07f, 8.87651190e+19f, };
+
+__constant__ float m_weights_float_2[4] = 
+      { 2.39852428e+00f, 5.24459642e+01f, 6.45788782e+04f, 2.50998524e+12f, };
+
+__constant__ float m_weights_float_3[8] = 
+      { 1.74936958e+00f, 3.97965898e+00f, 1.84851460e+01f, 1.86488072e+02f, 5.97420570e+03f, 1.27041264e+06f, 
+        6.16419301e+09f, 5.23085003e+15f, };
+
+__constant__ float m_weights_float_4[16] = 
+      { 1.61385906e+00f, 1.99776729e+00f, 3.02023198e+00f, 5.47764184e+00f, 1.17966092e+01f, 3.03550485e+01f, 
+        9.58442179e+01f, 3.89387024e+02f, 2.17919325e+03f, 1.83920812e+04f, 2.63212061e+05f, 7.42729651e+06f,
+        5.01587565e+08f, 1.03961087e+11f, 9.10032891e+13f, 5.06865116e+17f, };
+
+__constant__ float m_weights_float_5[32] = 
+      { 1.58146596e+00f, 1.66914991e+00f, 1.85752319e+00f, 2.17566262e+00f, 2.67590138e+00f, 3.44773868e+00f,
+        4.64394654e+00f, 6.53020450e+00f, 9.58228502e+00f, 1.46836141e+01f, 2.35444955e+01f, 3.96352727e+01f,
+        7.03763521e+01f, 1.32588012e+02f, 2.66962565e+02f, 5.79374920e+02f, 1.36869193e+03f, 3.55943572e+03f,
+        1.03218668e+04f, 3.38662130e+04f, 1.27816626e+05f, 5.65408251e+05f, 2.99446204e+06f, 1.94497502e+07f,
+        1.59219301e+08f, 1.69428882e+09f, 2.42715618e+10f, 4.87031785e+11f, 1.43181966e+13f, 6.48947152e+14f,
+        4.80375775e+16f, 6.20009636e+18f, };
+
+__constant__ float m_weights_float_6[65] = 
+      { 1.57345777e+00f, 1.59489276e+00f, 1.63853652e+00f, 1.70598041e+00f, 1.79972439e+00f, 1.92332285e+00f,
+        2.08159737e+00f, 2.28093488e+00f, 2.52969785e+00f, 2.83878478e+00f, 3.22239575e+00f, 3.69908136e+00f,
+        4.29318827e+00f, 5.03686536e+00f, 5.97287114e+00f, 7.15853842e+00f, 8.67142780e+00f, 1.06174736e+01f,
+        1.31428500e+01f, 1.64514563e+01f, 2.08309945e+01f, 2.66923599e+01f, 3.46299351e+01f, 4.55151836e+01f,
+        6.06440809e+01f, 8.19729692e+01f, 1.12502047e+02f, 1.56909655e+02f, 2.22620435e+02f, 3.21638549e+02f,
+        4.73757451e+02f, 7.12299455e+02f, 1.09460965e+03f, 1.72169779e+03f, 2.77592491e+03f, 4.59523007e+03f,
+        7.82342759e+03f, 1.37235744e+04f, 2.48518896e+04f, 4.65553875e+04f, 9.04176678e+04f, 1.82484396e+05f,
+        3.83680026e+05f, 8.42627197e+05f, 1.93843257e+06f, 4.68511285e+06f, 1.19352867e+07f, 3.21564375e+07f,
+        9.19600893e+07f, 2.80222318e+08f, 9.13611083e+08f, 3.20091090e+09f, 1.21076526e+10f, 4.96902475e+10f,
+        2.22431575e+11f, 1.09212534e+12f, 5.91688298e+12f, 3.55974344e+13f, 2.39435365e+14f, 1.81355107e+15f,
+        1.55873671e+16f, 1.53271488e+17f, 1.73927478e+18f, 2.29884122e+19f, 3.57403070e+20f, };
+
+__constant__ float m_weights_float_7[129] = 
+      { 1.57146132e+00f, 1.57679017e+00f, 1.58749564e+00f, 1.60367396e+00f, 1.62547113e+00f, 1.65308501e+00f,
+        1.68676814e+00f, 1.72683132e+00f, 1.77364814e+00f, 1.82766042e+00f, 1.88938482e+00f, 1.95942057e+00f,
+        2.03845873e+00f, 2.12729290e+00f, 2.22683194e+00f, 2.33811466e+00f, 2.46232715e+00f, 2.60082286e+00f,
+        2.75514621e+00f, 2.92706011e+00f, 3.11857817e+00f, 3.33200254e+00f, 3.56996830e+00f, 3.83549565e+00f,
+        4.13205150e+00f, 4.46362211e+00f, 4.83479919e+00f, 5.25088196e+00f, 5.71799849e+00f, 6.24325042e+00f,
+        6.83488580e+00f, 7.50250620e+00f, 8.25731548e+00f, 9.11241941e+00f, 1.00831875e+01f, 1.11876913e+01f,
+        1.24472371e+01f, 1.38870139e+01f, 1.55368872e+01f, 1.74323700e+01f, 1.96158189e+01f, 2.21379089e+01f,
+        2.50594593e+01f, 2.84537038e+01f, 3.24091185e+01f, 3.70329629e+01f, 4.24557264e+01f, 4.88367348e+01f,
+        5.63712464e+01f, 6.52994709e+01f, 7.59180776e+01f, 8.85949425e+01f, 1.03788130e+02f, 1.22070426e+02f,
+        1.44161210e+02f, 1.70968019e+02f, 2.03641059e+02f, 2.43645006e+02f, 2.92854081e+02f, 3.53678602e+02f,
+        4.29234308e+02f, 5.23570184e+02f, 6.41976690e+02f, 7.91405208e+02f, 9.81042209e+02f, 1.22309999e+03f,
+        1.53391256e+03f, 1.93546401e+03f, 2.45753455e+03f, 3.14073373e+03f, 4.04081819e+03f, 5.23488160e+03f,
+        6.83029446e+03f, 8.97771323e+03f, 1.18901592e+04f, 1.58712239e+04f, 2.13571111e+04f, 2.89798371e+04f,
+        3.96630673e+04f, 5.47687519e+04f, 7.63235654e+04f, 1.07371915e+05f, 1.52531667e+05f, 2.18877843e+05f,
+        3.17362450e+05f, 4.65120153e+05f, 6.89253766e+05f, 1.03311989e+06f, 1.56688798e+06f, 2.40549203e+06f,
+        3.73952896e+06f, 5.88912115e+06f, 9.39904635e+06f, 1.52090328e+07f, 2.49628719e+07f, 4.15775926e+07f,
+        7.03070537e+07f, 1.20759856e+08f, 2.10788251e+08f, 3.74104720e+08f, 6.75449459e+08f, 1.24131674e+09f,
+        2.32331003e+09f, 4.43117602e+09f, 8.61744649e+09f, 1.70983691e+10f, 3.46357452e+10f, 7.16760712e+10f,
+        1.51634762e+11f, 3.28172932e+11f, 7.27110260e+11f, 1.65049955e+12f, 3.84133815e+12f, 9.17374427e+12f,
+        2.24990195e+13f, 5.67153509e+13f, 1.47074225e+14f, 3.92701252e+14f, 1.08063998e+15f, 3.06767147e+15f,
+        8.99238679e+15f, 2.72472254e+16f, 8.54294612e+16f, 2.77461372e+17f, 9.34529948e+17f, 3.26799612e+18f,
+        1.18791443e+19f, 4.49405341e+19f, 1.77170665e+20f, };
+
+__constant__ float m_weights_float_8[259] = 
+      { 1.57096255e+00f, 1.57229290e+00f, 1.57495658e+00f, 1.57895955e+00f, 1.58431079e+00f, 1.59102230e+00f,
+        1.59910918e+00f, 1.60858966e+00f, 1.61948515e+00f, 1.63182037e+00f, 1.64562338e+00f, 1.66092569e+00f,
+        1.67776241e+00f, 1.69617233e+00f, 1.71619809e+00f, 1.73788633e+00f, 1.76128784e+00f, 1.78645779e+00f,
+        1.81345587e+00f, 1.84234658e+00f, 1.87319943e+00f, 1.90608922e+00f, 1.94109632e+00f, 1.97830698e+00f,
+        2.01781368e+00f, 2.05971547e+00f, 2.10411838e+00f, 2.15113585e+00f, 2.20088916e+00f, 2.25350798e+00f,
+        2.30913084e+00f, 2.36790578e+00f, 2.42999091e+00f, 2.49555516e+00f, 2.56477893e+00f, 2.63785496e+00f,
+        2.71498915e+00f, 2.79640147e+00f, 2.88232702e+00f, 2.97301705e+00f, 3.06874019e+00f, 3.16978367e+00f,
+        3.27645477e+00f, 3.38908227e+00f, 3.50801806e+00f, 3.63363896e+00f, 3.76634859e+00f, 3.90657947e+00f,
+        4.05479525e+00f, 4.21149322e+00f, 4.37720695e+00f, 4.55250922e+00f, 4.73801517e+00f, 4.93438579e+00f,
+        5.14233166e+00f, 5.36261713e+00f, 5.59606472e+00f, 5.84356014e+00f, 6.10605759e+00f, 6.38458564e+00f,
+        6.68025373e+00f, 6.99425915e+00f, 7.32789480e+00f, 7.68255767e+00f, 8.05975815e+00f, 8.46113023e+00f,
+        8.88844279e+00f, 9.34361190e+00f, 9.82871448e+00f, 1.03460033e+01f, 1.08979234e+01f, 1.14871305e+01f,
+        1.21165112e+01f, 1.27892047e+01f, 1.35086281e+01f, 1.42785033e+01f, 1.51028871e+01f, 1.59862046e+01f,
+        1.69332867e+01f, 1.79494108e+01f, 1.90403465e+01f, 2.02124072e+01f, 2.14725057e+01f, 2.28282181e+01f,
+        2.42878539e+01f, 2.58605342e+01f, 2.75562800e+01f, 2.93861096e+01f, 3.13621485e+01f, 3.34977526e+01f,
+        3.58076454e+01f, 3.83080730e+01f, 4.10169773e+01f, 4.39541917e+01f, 4.71416602e+01f, 5.06036855e+01f,
+        5.43672075e+01f, 5.84621188e+01f, 6.29216205e+01f, 6.77826252e+01f, 7.30862125e+01f, 7.88781469e+01f,
+        8.52094636e+01f, 9.21371360e+01f, 9.97248336e+01f, 1.08043785e+02f, 1.17173764e+02f, 1.27204209e+02f,
+        1.38235512e+02f, 1.50380485e+02f, 1.63766039e+02f, 1.78535118e+02f, 1.94848913e+02f, 2.12889407e+02f,
+        2.32862309e+02f, 2.55000432e+02f, 2.79567594e+02f, 3.06863126e+02f, 3.37227087e+02f, 3.71046310e+02f,
+        4.08761417e+02f, 4.50874968e+02f, 4.97960949e+02f, 5.50675821e+02f, 6.09771424e+02f, 6.76110054e+02f,
+        7.50682104e+02f, 8.34626760e+02f, 9.29256285e+02f, 1.03608458e+03f, 1.15686082e+03f, 1.29360914e+03f,
+        1.44867552e+03f, 1.62478326e+03f, 1.82509876e+03f, 2.05330964e+03f, 2.31371761e+03f, 2.61134924e+03f,
+        2.95208799e+03f, 3.34283233e+03f, 3.79168493e+03f, 4.30817984e+03f, 4.90355562e+03f, 5.59108434e+03f,
+        6.38646863e+03f, 7.30832183e+03f, 8.37874981e+03f, 9.62405722e+03f, 1.10756067e+04f, 1.27708661e+04f,
+        1.47546879e+04f, 1.70808754e+04f, 1.98141031e+04f, 2.30322789e+04f, 2.68294532e+04f, 3.13194118e+04f,
+        3.66401221e+04f, 4.29592484e+04f, 5.04810088e+04f, 5.94547213e+04f, 7.01854788e+04f, 8.30475173e+04f,
+        9.85009981e+04f, 1.17113127e+05f, 1.39584798e+05f, 1.66784302e+05f, 1.99790063e+05f, 2.39944995e+05f,
+        2.88925794e+05f, 3.48831531e+05f, 4.22297220e+05f, 5.12639825e+05f, 6.24046488e+05f, 7.61817907e+05f,
+        9.32683930e+05f, 1.14521401e+06f, 1.41035265e+06f, 1.74212004e+06f, 2.15853172e+06f, 2.68280941e+06f,
+        3.34498056e+06f, 4.18399797e+06f, 5.25055801e+06f, 6.61086017e+06f, 8.35163942e+06f, 1.05869253e+07f,
+        1.34671524e+07f, 1.71914827e+07f, 2.20245345e+07f, 2.83191730e+07f, 3.65476782e+07f, 4.73445266e+07f,
+        6.15653406e+07f, 8.03684303e+07f, 1.05328028e+08f, 1.38592169e+08f, 1.83103699e+08f, 2.42910946e+08f,
+        3.23606239e+08f, 4.32947522e+08f, 5.81743297e+08f, 7.85117979e+08f, 1.06432920e+09f, 1.44938958e+09f,
+        1.98286647e+09f, 2.72541431e+09f, 3.76386796e+09f, 5.22313881e+09f, 7.28378581e+09f, 1.02080964e+10f,
+        1.43789932e+10f, 2.03583681e+10f, 2.89749983e+10f, 4.14577375e+10f, 5.96383768e+10f, 8.62622848e+10f,
+        1.25466705e+11f, 1.83521298e+11f, 2.69981221e+11f, 3.99492845e+11f, 5.94638056e+11f, 8.90440997e+11f,
+        1.34155194e+12f, 2.03376855e+12f, 3.10262796e+12f, 4.76359832e+12f, 7.36142036e+12f, 1.14512696e+13f,
+        1.79331419e+13f, 2.82758550e+13f, 4.48929705e+13f, 7.17780287e+13f, 1.15585510e+14f, 1.87483389e+14f,
+        3.06351036e+14f, 5.04340065e+14f, 8.36616340e+14f, 1.39855635e+15f, 2.35633575e+15f, 4.00176517e+15f,
+        6.85137513e+15f, 1.18269011e+16f, 2.05867353e+16f, 3.61396878e+16f, 6.39911218e+16f, 1.14301619e+17f,
+        2.05988138e+17f, 3.74584679e+17f, 6.87444303e+17f, 1.27340764e+18f, 2.38124192e+18f, 4.49583562e+18f,
+        8.57144202e+18f, 1.65044358e+19f, 3.21010035e+19f, 6.30778012e+19f, 1.25240403e+20f, 2.51300530e+20f,
+        5.09677626e+20f, };
+
+__constant__ float* m_weights_float[8] = {
+    m_weights_float_1,
+    m_weights_float_2,
+    m_weights_float_3,
+    m_weights_float_4,
+    m_weights_float_5,
+    m_weights_float_6,
+    m_weights_float_7,
+    m_weights_float_8
+};
+
+__constant__ double m_abscissas_double_1[6] = 
+      { 3.088287417976322866e+00, 1.489931846492091580e+02, 3.412289247883437102e+06, 2.069325766042617791e+18, 
+        2.087002407609475560e+50, 2.019766160717908151e+137, };
+
+__constant__ double m_abscissas_double_2[6] =
+      { 9.130487626376696748e-01, 1.415789294662811592e+01, 6.704215516223276482e+03, 9.641725327150499415e+10, 
+        2.508950760085778485e+30, 1.447263535710337145e+83, };
+
+__constant__ double m_abscissas_double_3[12] =
+      { 4.072976900657586902e-01, 1.682066707021148743e+00, 6.150897986386729515e+00, 4.003962351929400222e+01,
+        7.929200247931026321e+02, 1.029849713330979583e+05, 3.038623109252438574e+08, 1.565445474362494869e+14, 
+        4.042465098430219104e+23, 1.321706827429658179e+39, 4.991231782099557998e+64, 7.352943850359875966e+106, };
+
+__constant__ double m_abscissas_double_4[24] =
+      { 1.981352722514781726e-01, 6.401556735005260177e-01, 1.248928698253977663e+00, 2.266080840944321232e+00, 
+        4.296462696702327381e+00, 9.130290387099955696e+00, 2.311107653864279933e+01, 7.427706034324012430e+01,
+        3.267209207115258917e+02, 2.159485694311818716e+03, 2.415015262896413060e+04, 5.318194002756929158e+05,
+        2.800586857217043323e+07, 4.524065079794338780e+09, 3.085612573980677122e+12, 1.338826733015807478e+16,
+        6.254617176562341381e+20, 6.182098535814164754e+26, 3.077293649788458067e+34, 2.348957289370104303e+44, 
+        1.148543197899469758e+57, 2.255300070010069868e+73, 1.877919500569195394e+94, 1.367473887938624280e+121, };
+
+__constant__ double m_abscissas_double_5[49] = 
+      { 9.839678940067320339e-02, 3.006056176599550351e-01, 5.198579789949384900e-01, 7.703620832988877009e-01, 
+        1.071311369641311830e+00, 1.450569758088998445e+00, 1.950778549520360334e+00, 2.640031773695551468e+00,
+        3.631372373667412273e+00, 5.119915330903350570e+00, 7.456660981404883289e+00, 1.130226126889972624e+01,
+        1.796410692472772550e+01, 3.017810704601898222e+01, 5.403875800312370567e+01, 1.041077314477469548e+02,
+        2.180295201202628077e+02, 5.021556986259101646e+02, 1.288621310998222420e+03, 3.739216870800548324e+03,
+        1.247507297020191232e+04, 4.876399753226692124e+04, 2.281456582219130122e+05, 1.308777960064843017e+06,
+        9.460846634209664077e+06, 8.888831203637279622e+07, 1.124168828974344134e+09, 1.991276729532144470e+10,
+        5.167434691060984650e+11, 2.067218814203990888e+13, 1.350615033184100406e+15, 1.538540662836508188e+17,
+        3.290747290540350661e+19, 1.437291381884498816e+22, 1.409832445530347286e+25, 3.459135480277971441e+28,
+        2.398720582340954092e+32, 5.398806604617292960e+36, 4.613340002580628610e+41, 1.787685909667902457e+47,
+        3.841984370124338536e+53, 5.752797955708583700e+60, 7.771812038427286551e+68, 1.269673044204081626e+78,
+        3.495676773765731568e+88, 2.362519474971692445e+100, 6.002143893273651123e+113, 9.290716303464155539e+128,
+        1.514442238033847090e+146, };
+
+__constant__ double m_abscissas_double_6[98] = 
+      { 4.911510035029024930e-02, 1.480131496743607333e-01, 2.489388137406836857e-01, 3.533254236926684378e-01,
+        4.627335566122353259e-01, 5.789120681640963067e-01, 7.038702533860627799e-01, 8.399658591446505688e-01,
+        9.900150664244376147e-01, 1.157432570143699131e+00, 1.346412759185361763e+00, 1.562167113901335551e+00,
+        1.811238852782323380e+00, 2.101924419006550301e+00, 2.444843885584197934e+00, 2.853720746632915024e+00,
+        3.346458910955350787e+00, 3.946645821057838387e+00, 4.685673101596678529e+00, 5.605762230908151175e+00,
+        6.764332336830574204e+00, 8.240383175379985221e+00, 1.014394356129857730e+01, 1.263024714338892472e+01,
+        1.592130395780345258e+01, 2.033921861921857185e+01, 2.635846445760633752e+01, 3.468926333224152409e+01,
+        4.641291467019728963e+01, 6.320550793890424203e+01, 8.771497261808906374e+01, 1.242096926240411498e+02,
+        1.797186347845127557e+02, 2.660817283327900190e+02, 4.037273029575712841e+02, 6.288113066545908703e+02,
+        1.007079837507490594e+03, 1.661568229185114288e+03, 2.829651440786582598e+03, 4.984386266585669139e+03,
+        9.101546927647810893e+03, 1.726892655475049727e+04, 3.413099578778601190e+04, 7.045668977053092802e+04,
+        1.523404217761279128e+05, 3.460479782897947414e+05, 8.284724209233183002e+05, 2.097596146601193946e+06,
+        5.636950798861273236e+06, 1.614071410855607245e+07, 4.944730678915060360e+07, 1.627810516820991356e+08,
+        5.785332971632280838e+08, 2.230838540681955690e+09, 9.382391306064739643e+09, 4.328149544776551692e+10,
+        2.203072744049242904e+11, 1.245245067109136413e+12, 7.869000534957822375e+12, 5.599531432979422461e+13,
+        4.521486949902090877e+14, 4.176889516548293265e+15, 4.452867759650496656e+16, 5.529142853140498068e+17,
+        8.075732516562854275e+18, 1.402046916260468698e+20, 2.925791412832239850e+21, 7.426433029335410886e+22,
+        2.321996331245735364e+24, 9.064194250638442432e+25, 4.481279048819445609e+27, 2.849046304726990645e+29,
+        2.367381159183355975e+31, 2.615825578455121227e+33, 3.914764948263290808e+35, 8.092042448555929219e+37,
+        2.358921320940630332e+40, 9.915218648535332591e+42, 6.152851059342658764e+45, 5.780276340144515388e+48,
+        8.443751734186488626e+51, 1.973343350899766708e+55, 7.605247378556219980e+58, 4.992057104939510418e+62,
+        5.775863423903912316e+66, 1.221808201945355603e+71, 4.912917230387133816e+75, 3.913971813732202372e+80,
+        6.456388069905286787e+85, 2.311225068528010358e+91, 1.887458157719431339e+97, 3.708483165438453094e+103,
+        1.855198812283538635e+110, 2.509787873171705318e+117, 9.790423755591216617e+124, 1.179088807944050747e+133,
+        4.714631846722476620e+141, 6.762657785959713240e+150, };
+
+__constant__ double m_abscissas_double_7[196] = 
+      { 2.454715583629863651e-02, 7.372466873903346224e-02, 1.231525309416766543e-01, 1.730001377719248556e-01,
+        2.234406649596860001e-01, 2.746526549718518258e-01, 3.268216792980646669e-01, 3.801421009804789245e-01,
+        4.348189637215614948e-01, 4.910700365099428407e-01, 5.491280459480215441e-01, 6.092431324382654397e-01,
+        6.716855712021148069e-01, 7.367488049067938643e-01, 8.047528416336950644e-01, 8.760480802482050705e-01,
+        9.510196351823332253e-01, 1.030092244532470067e+00, 1.113735859588680765e+00, 1.202472030918058876e+00,
+        1.296881226496863751e+00, 1.397611241828373026e+00, 1.505386891360545205e+00, 1.621021205894798030e+00,
+        1.745428403369044572e+00, 1.879638952031029331e+00, 2.024817107609328524e+00, 2.182281382147884181e+00,
+        2.353528494823881355e+00, 2.540261468229626457e+00, 2.744422672171478111e+00, 2.968232787190606619e+00,
+        3.214236869520657666e+00, 3.485358957907730467e+00, 3.784966983117372821e+00, 4.116950138940295100e+00,
+        4.485811369388231710e+00, 4.896778246562001812e+00, 5.355936290826725948e+00, 5.870389762600956907e+00,
+        6.448456189131117605e+00, 7.099902452679558236e+00, 7.836232253282841261e+00, 8.671037293575230635e+00,
+        9.620427777985990363e+00, 1.070356198876799531e+01, 1.194330008139441022e+01, 1.336701421038499647e+01,
+        1.500759615914396343e+01, 1.690471548203528376e+01, 1.910639668731689597e+01, 2.167100443216577994e+01,
+        2.466975274695099197e+01, 2.818989025157845355e+01, 3.233876132429401745e+01, 3.724900758097245740e+01,
+        4.308526084907741997e+01, 5.005279647654703975e+01, 5.840877607253876528e+01, 6.847692821534239862e+01,
+        8.066681777060714848e+01, 9.549927270200249260e+01, 1.136401195769487885e+02, 1.359451944976603209e+02,
+        1.635207451879744447e+02, 1.978049687912586950e+02, 2.406787535889776661e+02, 2.946170292930555023e+02,
+        3.628969532147125333e+02, 4.498861782715596902e+02, 5.614447353133496106e+02, 7.054892470899271429e+02,
+        8.927907732799964116e+02, 1.138111424979478376e+03, 1.461835991563605367e+03, 1.892332623444716186e+03,
+        2.469396036186133479e+03, 3.249311569298824731e+03, 4.312367113170283012e+03, 5.774094754500139661e+03,
+        7.802247237500851845e+03, 1.064267530975806972e+04, 1.465915383535674990e+04, 2.039528541239754835e+04,
+        2.867170622421556265e+04, 4.074033762183453297e+04, 5.853182310596923393e+04, 8.505689265265206640e+04,
+        1.250649269847856615e+05, 1.861373943166749766e+05, 2.805255777452010927e+05, 4.282782486084761748e+05,
+        6.626340506127657304e+05, 1.039443239650339565e+06, 1.653857426112961316e+06, 2.670315650125279161e+06,
+        4.377212026624358795e+06, 7.288071713698413821e+06, 1.233172993400331694e+07, 2.121557285769933699e+07,
+        3.713086254861535383e+07, 6.614579377352135534e+07, 1.200055291694917110e+08, 2.218629410296880690e+08,
+        4.182282939928687703e+08, 8.043704132493714804e+08, 1.579392989425668114e+09, 3.168122415524104635e+09,
+        6.496606811549861323e+09, 1.362851988356444486e+10, 2.926863897008707708e+10, 6.439798665209493735e+10,
+        1.452755233772903022e+11, 3.362854459389246576e+11, 7.994202785433479271e+11, 1.953264233362291960e+12,
+        4.909581868242554569e+12, 1.270622730765015610e+13, 3.389070986742985764e+13, 9.325084030208844833e+13,
+        2.649489423834534140e+14, 7.781295184094957195e+14, 2.364715052527355639e+15, 7.444138031465958255e+15,
+        2.430217240684749635e+16, 8.237068641534357762e+16, 2.902117050664548840e+17, 1.064157679404037013e+18,
+        4.066277106061960017e+18, 1.621274233630359097e+19, 6.754156830915450013e+19, 2.944056841733781919e+20,
+        1.344640139549107817e+21, 6.444586158944723300e+21, 3.246218667554608934e+22, 1.721234579556653533e+23,
+        9.622533890240474391e+23, 5.681407260417956671e+24, 3.548890779995928184e+25, 2.349506425672269562e+26,
+        1.651618130605205643e+27, 1.235147426493113059e+28, 9.845947239792057550e+28, 8.383130781984610418e+29,
+        7.639649461399172445e+30, 7.467862732233885201e+31, 7.847691482004993660e+32, 8.886032557626454704e+33,
+        1.086734890678302436e+35, 1.438967777036538458e+36, 2.068168865475603521e+37, 3.234885320223912385e+38,
+        5.521233641542628514e+39, 1.031148231194663855e+41, 2.113272035816365982e+42, 4.766724345485077520e+43,
+        1.186961550990218287e+45, 3.273172169205847573e+46, 1.002821226769167753e+48, 3.424933903935156479e+49,
+        1.308436017026428736e+51, 5.611378330048420503e+52, 2.711424806327139291e+54, 1.481771793644066442e+56,
+        9.194282071042778804e+57, 6.503661455875355562e+59, 5.266329986868627303e+61, 4.902662807969347359e+63,
+        5.270511057289557050e+65, 6.572856511670583316e+67, 9.553956030013225387e+69, 1.626491911159411616e+72,
+        3.259410915500951223e+74, 7.728460318113614280e+76, 2.179881996905918059e+79, 7.354484388371505915e+81,
+        2.984831270803957746e+84, 1.465828267813438962e+87, 8.763355972629864261e+89, 6.417909665847831130e+92,
+        5.794958649229893510e+95, 6.494224472311908365e+98, 9.095000156016433698e+101, 1.603058498455299102e+105,
+        3.582099119119320529e+108, 1.022441227139854687e+112, 3.756872185015086057e+115, 1.791363463832849159e+119,
+        1.117641882039472124e+123, 9.202159565546528285e+126, 1.008716474827888568e+131, 1.485546487089301805e+135,
+        2.966961534830566097e+139, 8.114207284664369360e+143, 3.069178087507669739e+148, 1.622223681147791473e+153, };
+
+__constant__ double m_abscissas_double_8[391] = 
+      { 1.227227917054637830e-02, 3.682722894492590471e-02, 6.141337626871079991e-02, 8.605159708778207907e-02,
+        1.107628840017845446e-01, 1.355683934957785482e-01, 1.604894937454335489e-01, 1.855478131645089496e-01,
+        2.107652898670700524e-01, 2.361642222214626268e-01, 2.617673206785495261e-01, 2.875977610631342900e-01,
+        3.136792395249035647e-01, 3.400360293536632770e-01, 3.666930398731810193e-01, 3.936758776386451797e-01,
+        4.210109101746846268e-01, 4.487253325041450341e-01, 4.768472367324829462e-01, 5.054056849688209375e-01,
+        5.344307858825229079e-01, 5.639537752137267134e-01, 5.940071005777549000e-01, 6.246245109268716053e-01,
+        6.558411510586397969e-01, 6.876936615883514922e-01, 7.202202848338683401e-01, 7.534609770949572224e-01,
+        7.874575278460963461e-01, 8.222536864020499377e-01, 8.578952966595825808e-01, 8.944304405668593009e-01,
+        9.319095910247435485e-01, 9.703857749817920659e-01, 1.009914747547728584e+00, 1.050555178019083150e+00,
+        1.092368848786092579e+00, 1.135420868172514300e+00, 1.179779898350424466e+00, 1.225518399571142610e+00,
+        1.272712892062026473e+00, 1.321444237057985065e+00, 1.371797938567245953e+00, 1.423864467614384096e+00,
+        1.477739610861208115e+00, 1.533524845679288858e+00, 1.591327743938355098e+00, 1.651262406984310076e+00,
+        1.713449934511288211e+00, 1.778018930286256858e+00, 1.845106047964720870e+00, 1.914856580544951899e+00,
+        1.987425097349017093e+00, 2.062976132795275283e+00, 2.141684931642916785e+00, 2.223738255848994521e+00,
+        2.309335258687213796e+00, 2.398688432341103821e+00, 2.492024635808356095e+00, 2.589586210645122756e+00,
+        2.691632192846832444e+00, 2.798439630014497291e+00, 2.910305013902562652e+00, 3.027545839497364963e+00,
+        3.150502302946919722e+00, 3.279539151967394330e+00, 3.415047703805410611e+00, 3.557448047456550733e+00,
+        3.707191448649779817e+00, 3.864762978128342125e+00, 4.030684386016531344e+00, 4.205517247588613835e+00,
+        4.389866408585172458e+00, 4.584383761391930748e+00, 4.789772386950687695e+00, 5.006791101261363264e+00,
+        5.236259449815274050e+00, 5.479063198337523150e+00, 5.736160373884817415e+00, 6.008587916728619858e+00,
+        6.297469010648863048e+00, 6.604021167380929133e+00, 6.929565150124677837e+00, 7.275534831383860972e+00,
+        7.643488092123492064e+00, 8.035118882502459288e+00, 8.452270579478188130e+00, 8.896950793641785313e+00,
+        9.371347797016395173e+00, 9.877848765573446033e+00, 1.041906005527762037e+01, 1.099782975900831706e+01,
+        1.161727282423952258e+01, 1.228079904848924611e+01, 1.299214431196691048e+01, 1.375540545535625881e+01,
+        1.457507926620621316e+01, 1.545610610104852468e+01, 1.640391874338302925e+01, 1.742449718154208970e+01,
+        1.852443008688437526e+01, 1.971098388378266494e+01, 2.099218043080961648e+01, 2.237688448013982946e+01,
+        2.387490225270073820e+01, 2.549709266380430464e+01, 2.725549296232531555e+01, 2.916346081119624987e+01,
+        3.123583514423284962e+01, 3.348911849136805118e+01, 3.594168387985465099e+01, 3.861400990307230737e+01,
+        4.152894811329303023e+01, 4.471202755441533396e+01, 4.819180202224910174e+01, 5.200024654361558757e+01,
+        5.617321062537384494e+01, 6.075093706918782079e+01, 6.577865661168003966e+01, 7.130727037357721343e+01,
+        7.739413413465805794e+01, 8.410396085269633392e+01, 9.150986068496734448e+01, 9.969454113547704016e+01,
+        1.087516939426018897e+02, 1.187876000643037532e+02, 1.299229897614516371e+02, 1.422952015056372537e+02,
+        1.560606914665002671e+02, 1.713979549326432406e+02, 1.885109325154830073e+02, 2.076329877740125935e+02,
+        2.290315594654587370e+02, 2.530136115655676467e+02, 2.799320282398896912e+02, 3.101931299766730890e+02,
+        3.442655222107529892e+02, 3.826905303289378387e+02, 4.260945266207607701e+02, 4.752035175892902045e+02,
+        5.308604366239058864e+02, 5.940456805372995009e+02, 6.659015428338778262e+02, 7.477613367309153870e+02,
+        8.411841730471343023e+02, 9.479965698013741524e+02, 1.070342331375881840e+03, 1.210742457518582660e+03,
+        1.372167241552205820e+03, 1.558123212187692722e+03, 1.772758188662716282e+03, 2.020988485411862984e+03,
+        2.308653259329163157e+03, 2.642702189813684273e+03, 3.031424182869210212e+03, 3.484726676985756018e+03,
+        4.014477504733973505e+03, 4.634924264049394751e+03, 5.363209949773439749e+03, 6.220008412114342803e+03,
+        7.230309332853029956e+03, 8.424390216735217783e+03, 9.839022871538541787e+03, 1.151897463083113988e+04,
+        1.351888098874374202e+04, 1.590558745460066947e+04, 1.876108572764816176e+04, 2.218620462393366275e+04,
+        2.630526205054915357e+04, 3.127194401941711057e+04, 3.727675461256652923e+04, 4.455648280312273249e+04,
+        5.340626592018903930e+04, 6.419500580388918123e+04, 7.738512642386820060e+04, 9.355796993981725963e+04,
+        1.134465375820669470e+05, 1.379778272209741713e+05, 1.683277485807887053e+05, 2.059925746120735305e+05,
+        2.528822024503158254e+05, 3.114422718347725915e+05, 3.848145913435570736e+05, 4.770485864966822643e+05,
+        5.933809324724740854e+05, 7.406066190351666115e+05, 9.275730471470643372e+05, 1.165840260940180415e+06,
+        1.470566322118246135e+06, 1.861698899014921971e+06, 2.365584870298354495e+06, 3.017152695505764877e+06,
+        3.862882573599929249e+06, 4.964864305589750358e+06, 6.406362829959736606e+06, 8.299481847261302115e+06,
+        1.079575892642401854e+07, 1.410087327474604091e+07, 1.849514724418250100e+07, 2.436224419670805500e+07,
+        3.222951131863941234e+07, 4.282493882385925337e+07, 5.715793394339267637e+07, 7.663437932745451635e+07,
+        1.032212725498489699e+08, 1.396833991976194842e+08, 1.899251497664892740e+08, 2.594865396467505851e+08,
+        3.562664742464501497e+08, 4.915825413172413471e+08, 6.817316470116958142e+08, 9.502998105202541438e+08,
+        1.331598295343277538e+09, 1.875801976010459831e+09, 2.656673907709731487e+09, 3.783240215616365909e+09,
+        5.417531848500136979e+09, 7.801695369892847510e+09, 1.129965368955098833e+10, 1.646149161390821924e+10,
+        2.412353995736687694e+10, 3.556486895431927094e+10, 5.275345014093760519e+10, 7.873572108325378177e+10,
+        1.182569020317863604e+11, 1.787549442508363461e+11, 2.719633064979986142e+11, 4.165122153119897946e+11,
+        6.421781858205134197e+11, 9.968725497576275918e+11, 1.558212327122960399e+12, 2.452809984907093786e+12,
+        3.888656232828140210e+12, 6.209868990509424909e+12, 9.989924216297983665e+12, 1.619158001378611351e+13,
+        2.644324518669926559e+13, 4.352018847904374786e+13, 7.218884688202741709e+13, 1.206997640727349538e+14,
+        2.034483722445207402e+14, 3.457553102874402920e+14, 5.925248511957505706e+14, 1.024057793713038672e+15,
+        1.785174045941642162e+15, 3.139306988668494696e+15, 5.569856270174890128e+15, 9.971763353834460328e+15,
+        1.801687491114883092e+16, 3.285709858322565542e+16, 6.049018540910759710e+16, 1.124375283211369572e+17,
+        2.110445125952435305e+17, 4.000737007891229992e+17, 7.660849361564329309e+17, 1.482018770996176700e+18,
+        2.896945433910857945e+18, 5.722790165693470493e+18, 1.142689960439921462e+19, 2.306616559984106723e+19,
+        4.707857184616093863e+19, 9.717346347495342813e+19, 2.028735605622585444e+20, 4.284840254171000581e+20,
+        9.157027329021623836e+20, 1.980457834766411777e+21, 4.335604886702252004e+21, 9.609258559714223995e+21,
+        2.156604630608586997e+22, 4.902045909695270289e+22, 1.128749227121328467e+23, 2.633414623049930879e+23,
+        6.226335684490998543e+23, 1.492205279014148921e+24, 3.625768249717590109e+24, 8.933899764961444882e+24,
+        2.232786981682262383e+25, 5.661295336293986732e+25, 1.456616710298133142e+26, 3.803959852868488245e+26,
+        1.008531585603036490e+27, 2.715247425129423358e+27, 7.425071766766651967e+27, 2.062860712173225003e+28,
+        5.824055458799413312e+28, 1.671388836696436644e+29, 4.876830632023956392e+29, 1.447170071146107156e+30,
+        4.368562208925583783e+30, 1.341873806249251338e+31, 4.195251632754338682e+31, 1.335360134828214136e+32,
+        4.328681350715136340e+32, 1.429401866150319186e+33, 4.809736146227180696e+33, 1.649624114567602575e+34,
+        5.768677492419801469e+34, 2.057442854162761350e+35, 7.486423509917811063e+35, 2.780052791791155051e+36,
+        1.053908347660081874e+37, 4.080046334235754223e+37, 1.613553311592805373e+38, 6.520836332997615098e+38,
+        2.693848186257510992e+39, 1.138002408430710800e+40, 4.917748008813924613e+40, 2.174691073191358676e+41,
+        9.844523745430526502e+41, 4.563707467590116732e+42, 2.167352073708379137e+43, 1.054860193887170754e+44,
+        5.263588225566847365e+44, 2.693772458797916623e+45, 1.414506760560163074e+46, 7.624126763512016620e+46,
+        4.219828148762794411e+47, 2.399387665831793264e+48, 1.402139947254117434e+49, 8.424706325525422943e+49,
+        5.206918479942619318e+50, 3.311787866477716151e+51, 2.168683295509859155e+52, 1.462786368779206713e+53,
+        1.016761784575838363e+54, 7.286460995145043184e+54, 5.386194237448865407e+55, 4.108917480528740640e+56,
+        3.236445625945552728e+57, 2.633440652417619669e+58, 2.214702339357939268e+59, 1.926058995948268392e+60,
+        1.733067740414174932e+61, 1.614307160124426969e+62, 1.557464328486352138e+63, 1.557226155197192031e+64,
+        1.614473962707995344e+65, 1.736617406327386105e+66, 1.939201243451190521e+67, 2.249277732936622876e+68,
+        2.711593798719765599e+69, 3.399628732048687119e+70, 4.435389696730206291e+71, 6.025566076164003981e+72,
+        8.529161425383779849e+73, 1.258746322992988688e+75, 1.938112175186560210e+76, 3.115432363572610661e+77,
+        5.231797674434390018e+78, 9.184930207860680757e+79, 1.686929404780378772e+81, 3.243565624474232635e+82,
+        6.533812498930220075e+83, 1.379898823144620314e+85, 3.057650444842839916e+86, 7.114050545839171245e+87,
+        1.739275024442258674e+89, 4.471782915853177804e+90, 1.210036789494028144e+92, 3.448828044590862359e+93,
+        1.036226783750561565e+95, 3.284801914751206038e+96, 1.099514933602224638e+98, 3.889581731378242597e+99,
+        1.455434287901069991e+101, 5.765729934387419019e+102, 2.420349568745475582e+104, 1.077606625929777536e+106,
+        5.093346988695851845e+107, 2.558090824110323997e+109, 1.366512508719047964e+111, 7.771735800763526406e+112,
+        4.710398638793014918e+114, 3.045563885587013954e+116, 2.102762552861442993e+118, 1.551937536212596136e+120,
+        1.225676354426075970e+122, 1.036950946169703711e+124, 9.407885268970827717e+125, 9.163369107785093171e+127,
+        9.592531095671168926e+129, 1.080486293361823875e+132, 1.311034829557782450e+134, 1.715642975932639188e+136,
+        2.424231742707881878e+138, 3.703231223333127919e+140, 6.123225027409988902e+142, 1.097271040771196765e+145,
+        2.133693643241295977e+147, 4.508099184895777328e+149, 1.036252806686291189e+152, };
+
+__constant__ double* m_abscissas_double[8] = {
+    m_abscissas_double_1,
+    m_abscissas_double_2,
+    m_abscissas_double_3,
+    m_abscissas_double_4,
+    m_abscissas_double_5,
+    m_abscissas_double_6,
+    m_abscissas_double_7,
+    m_abscissas_double_8,
+};
+
+__constant__ double m_weights_double_1[6] =
+      { 7.868241604839621507e+00, 8.805163880733011116e+02, 5.396278323520705668e+07, 8.876511896968161317e+19,
+        2.432791879269225553e+52, 6.399713512080202911e+139, };
+
+__constant__ double m_weights_double_2[6] =
+      { 2.398524276302635218e+00, 5.244596423726681022e+01, 6.457887819598201760e+04, 2.509985242511374506e+12,
+        1.774029269327138701e+32, 2.781406115983097314e+85, };
+
+__constant__ double m_weights_double_3[12] =
+      { 1.749369583108386852e+00, 3.979658981934607813e+00, 1.848514598574449570e+01, 1.864880718932067988e+02,
+        5.974205695263265855e+03, 1.270412635144623341e+06, 6.164193014295984071e+09, 5.230850031811222530e+15,
+        2.226260929943369774e+25, 1.199931102042181592e+41, 7.470602144275146214e+66, 1.814465860528410676e+109, };
+
+__constant__ double m_weights_double_4[24] =
+      { 1.613859062188366173e+00, 1.997767291869673262e+00, 3.020231979908834220e+00, 5.477641843859057761e+00,
+        1.179660916492671672e+01, 3.035504848518598294e+01, 9.584421793794920860e+01, 3.893870238229992076e+02,
+        2.179193250357911344e+03, 1.839208123964132852e+04, 2.632120612599856167e+05, 7.427296507169468210e+06,
+        5.015875648341232356e+08, 1.039610867241544113e+11, 9.100328911818091977e+13, 5.068651163890231571e+17,
+        3.039966520714902616e+22, 3.857740194672007962e+28, 2.465542763666581087e+36, 2.416439449167799461e+46,
+        1.517091553926604149e+59, 3.825043412021411380e+75, 4.089582396821598640e+96, 3.823775894295564050e+123, };
+
+__constant__ double m_weights_double_5[49] =
+      { 1.581465959536694744e+00, 1.669149910438534746e+00, 1.857523188595005770e+00, 2.175662623626994120e+00,
+        2.675901375211020564e+00, 3.447738682498791744e+00, 4.643946540355464126e+00, 6.530204496574248616e+00,
+        9.582285015566804961e+00, 1.468361407515440960e+01, 2.354449548740987533e+01, 3.963527273305166705e+01,
+        7.037635206267538547e+01, 1.325880124784838868e+02, 2.669625649541569172e+02, 5.793749198508472676e+02,
+        1.368691928321303605e+03, 3.559435721533130554e+03, 1.032186677270763318e+04, 3.386621302858741487e+04,
+        1.278166259840246830e+05, 5.654082513926693098e+05, 2.994462044781721833e+06, 1.944975023421914947e+07,
+        1.592193007690560588e+08, 1.694288818617459913e+09, 2.427156182311303271e+10, 4.870317848199455490e+11,
+        1.431819656229181793e+13, 6.489471523099301256e+14, 4.803757752508989106e+16, 6.200096361305331541e+18,
+        1.502568562439914899e+21, 7.436061367189688251e+23, 8.264761218677928603e+26, 2.297735027897804345e+30,
+        1.805449779569534997e+34, 4.604472360199061931e+38, 4.458371212030626854e+43, 1.957638261114809309e+49,
+        4.767368137162500764e+55, 8.088820139476721285e+62, 1.238260897349286357e+71, 2.292272505278842062e+80,
+        7.151392373749193549e+90, 5.476714850156044431e+102, 1.576655618370700681e+116, 2.765448595957851958e+131,
+        5.108051255283132673e+148, };
+
+__constant__ double m_weights_double_6[98] =
+      { 1.573457773573108386e+00, 1.594892755038663787e+00, 1.638536515530234742e+00, 1.705980408212213620e+00,
+        1.799724394608737275e+00, 1.923322854425656307e+00, 2.081597373313268178e+00, 2.280934883790070511e+00,
+        2.529697852387704655e+00, 2.838784782552951185e+00, 3.222395745020980612e+00, 3.699081358854235112e+00,
+        4.293188274330526800e+00, 5.036865356322330076e+00, 5.972871140910932199e+00, 7.158538424311077564e+00,
+        8.671427800892076385e+00, 1.061747360297922326e+01, 1.314285002260235600e+01, 1.645145625668428040e+01,
+        2.083099449998189069e+01, 2.669235989791640190e+01, 3.462993514791378189e+01, 4.551518362653662579e+01,
+        6.064408087764392116e+01, 8.197296917485846798e+01, 1.125020468081652564e+02, 1.569096552844714123e+02,
+        2.226204347868638276e+02, 3.216385489504077755e+02, 4.737574505945461739e+02, 7.122994548146997637e+02,
+        1.094609652686376553e+03, 1.721697789176049576e+03, 2.775924909253835146e+03, 4.595230066268149347e+03,
+        7.823427586641573672e+03, 1.372357435269105405e+04, 2.485188961645119553e+04, 4.655538745425972783e+04,
+        9.041766782135686884e+04, 1.824843964862728392e+05, 3.836800264094614027e+05, 8.426271970245168026e+05,
+        1.938432574158782634e+06, 4.685112849356485528e+06, 1.193528667218607927e+07, 3.215643752247989316e+07,
+        9.196008928386600386e+07, 2.802223178457559964e+08, 9.136110825267458886e+08, 3.200910900783148591e+09,
+        1.210765264234723689e+10, 4.969024745093101808e+10, 2.224315751863855216e+11, 1.092125344449313660e+12,
+        5.916882980019919359e+12, 3.559743438494577249e+13, 2.394353652945465191e+14, 1.813551073517501917e+15,
+        1.558736706166165738e+16, 1.532714875555114333e+17, 1.739274776190789212e+18, 2.298841216802216313e+19,
+        3.574030698837762664e+20, 6.604899705451419080e+21, 1.467155879591820659e+23, 3.964094964398509381e+24,
+        1.319342840595348793e+26, 5.482251971340400742e+27, 2.885137894723827518e+29, 1.952539840765392110e+31,
+        1.727051489032222797e+33, 2.031343507095439396e+35, 3.236074146972599980e+37, 7.120487412983497200e+39,
+        2.209552707411017265e+42, 9.886282647791384648e+44, 6.530514048788273529e+47, 6.530706672481546528e+50,
+        1.015518807431281951e+54, 2.526366773162394510e+57, 1.036450519906790297e+61, 7.241966032627135861e+64,
+        8.919402520769714938e+68, 2.008463619152992905e+73, 8.596914764830260020e+77, 7.290599546829495220e+82,
+        1.280199563216419112e+88, 4.878349285603201150e+93, 4.240828248064127940e+99, 8.869771764721598720e+105,
+        4.723342575741417669e+112, 6.802035963326188581e+119, 2.824531180990009549e+127, 3.621049216745982252e+135,
+        1.541270150334942520e+144, 2.353376995174362785e+153, };
+
+__constant__ double m_weights_double_7[196] =
+      { 1.571461316550783294e+00, 1.576790166316938345e+00, 1.587495640370383316e+00, 1.603673956341370210e+00,
+        1.625471125457493943e+00, 1.653085011915939302e+00, 1.686768142525911236e+00, 1.726831323537516202e+00,
+        1.773648138667236602e+00, 1.827660421478661448e+00, 1.889384817044018196e+00, 1.959420572855037091e+00,
+        2.038458728047908923e+00, 2.127292904083847225e+00, 2.226831940199076941e+00, 2.338114664555130296e+00,
+        2.462327148722991304e+00, 2.600822860927085164e+00, 2.755146214814554359e+00, 2.927060108424483555e+00,
+        3.118578166240921951e+00, 3.332002540339506630e+00, 3.569968300410740276e+00, 3.835495653996447262e+00,
+        4.132051496512934885e+00, 4.463622106699067881e+00, 4.834799191008006557e+00, 5.250881957765679608e+00,
+        5.717998490875333124e+00, 6.243250421598568105e+00, 6.834885801226541839e+00, 7.502506202789340802e+00,
+        8.257315484493544201e+00, 9.112419405864642634e+00, 1.008318749543997758e+01, 1.118769134993865202e+01,
+        1.244723705914106881e+01, 1.388701390605507587e+01, 1.553688715915900190e+01, 1.743237000680942831e+01,
+        1.961581894823993424e+01, 2.213790886354273806e+01, 2.505945934677137610e+01, 2.845370377742137561e+01,
+        3.240911845969524834e+01, 3.703296289480230161e+01, 4.245572644746267911e+01, 4.883673480337985582e+01,
+        5.637124640586975420e+01, 6.529947092752610340e+01, 7.591807755694122837e+01, 8.859494252391663822e+01,
+        1.037881295005788124e+02, 1.220704263969226746e+02, 1.441612098131200535e+02, 1.709680191245773511e+02,
+        2.036410593843575570e+02, 2.436450058708723643e+02, 2.928540812182076105e+02, 3.536786019152253392e+02,
+        4.292343083967296939e+02, 5.235701840488733027e+02, 6.419766898003024575e+02, 7.914052083668759283e+02,
+        9.810422089081931637e+02, 1.223099994999740393e+03, 1.533912555427112127e+03, 1.935464013605830339e+03,
+        2.457534549912886852e+03, 3.140733731623635519e+03, 4.040818188564651898e+03, 5.234881599712225681e+03,
+        6.830294457607329226e+03, 8.977713228649887143e+03, 1.189015920967326839e+04, 1.587122387044346962e+04,
+        2.135711106445789331e+04, 2.897983705189681437e+04, 3.966306726795547950e+04, 5.476875193750000787e+04,
+        7.632356539388055680e+04, 1.073719149754976951e+05, 1.525316674555574152e+05, 2.188778434744216586e+05,
+        3.173624496019295608e+05, 4.651201525869328462e+05, 6.892537656280580572e+05, 1.033119885120019982e+06,
+        1.566887981043252499e+06, 2.405492027026531795e+06, 3.739528964815910340e+06, 5.889121154895580032e+06,
+        9.399046351922342030e+06, 1.520903276129653518e+07, 2.496287187293576168e+07, 4.157759259963074840e+07,
+        7.030705366950267312e+07, 1.207598558452493366e+08, 2.107882509464846833e+08, 3.741047199023457864e+08,
+        6.754494594987415572e+08, 1.241316740415880537e+09, 2.323310032649552862e+09, 4.431176019026625759e+09,
+        8.617446487400900130e+09, 1.709836906604031513e+10, 3.463574521880171339e+10, 7.167607123799270726e+10,
+        1.516347620910054079e+11, 3.281729323238950526e+11, 7.271102600298280790e+11, 1.650499552378780378e+12,
+        3.841338149508803917e+12, 9.173744267785176575e+12, 2.249901946357519979e+13, 5.671535089900611731e+13,
+        1.470742250307697019e+14, 3.927012518464311775e+14, 1.080639977391212820e+15, 3.067671466720475189e+15,
+        8.992386789198328428e+15, 2.724722536524592111e+16, 8.542946122263389258e+16, 2.774613718725574755e+17,
+        9.345299479382029121e+17, 3.267996122987731882e+18, 1.187914433455468315e+19, 4.494053408418564214e+19,
+        1.771706652195486743e+20, 7.288102552885931527e+20, 3.132512430816625349e+21, 1.408743767951073110e+22,
+        6.638294268236060414e+22, 3.282543608403565013e+23, 1.705920098038394064e+24, 9.332259385148524285e+24,
+        5.382727175874888312e+25, 3.278954235122093249e+26, 2.113191697957458099e+27, 1.443411041499643040e+28,
+        1.046864394654982423e+29, 8.077319226958905700e+29, 6.643146963432616277e+30, 5.835670121359986260e+31,
+        5.486890296790230798e+32, 5.533726968508261614e+33, 5.999734996418352834e+34, 7.009176119466122569e+35,
+        8.844061966424597499e+36, 1.208226860869605961e+38, 1.791648514311063338e+39, 2.891313916713205762e+40,
+        5.091457860211527298e+41, 9.810630588402496553e+42, 2.074441239147378860e+44, 4.827650116937700540e+45,
+        1.240287939111549029e+47, 3.528782858644784616e+48, 1.115449490471696659e+50, 3.930510643328196314e+51,
+        1.549243712957852337e+53, 6.854998238041301002e+54, 3.417479961583207704e+56, 1.926905498641079990e+58,
+        1.233580963004919450e+60, 9.002819902898076915e+61, 7.521415141253441645e+63, 7.224277554900578993e+65,
+        8.012832830535078610e+67, 1.030999620286380369e+70, 1.546174957076748679e+72, 2.715803772613248694e+74,
+        5.615089920571746438e+76, 1.373667859345343337e+79, 3.997541020769625126e+81, 1.391500589339800087e+84,
+        5.826693844912022892e+86, 2.952274820929549096e+89, 1.821023061478466282e+92, 1.375973022137941526e+95,
+        1.281852367543412945e+98, 1.482130127201990503e+101, 2.141574273792435314e+104, 3.894495540947112380e+107,
+        8.978646362580102961e+110, 2.644131589807244050e+114, 1.002403539841913834e+118, 4.931412804903905259e+121,
+        3.174401112435865044e+125, 2.696624001761892390e+129, 3.049799322320447166e+133, 4.634041526818687785e+137,
+        9.548983134803106512e+141, 2.694404866192089829e+146, 1.051502720036395325e+151, 5.734170640626244955e+155, };
+
+__constant__ double m_weights_double_8[391] =
+      { 1.570962550997832611e+00, 1.572292902367211961e+00, 1.574956581912666755e+00, 1.578959553636163985e+00,
+        1.584310789563614305e+00, 1.591022301117035107e+00, 1.599109181186160337e+00, 1.608589657109067468e+00,
+        1.619485154826419743e+00, 1.631820374530739318e+00, 1.645623378191125679e+00, 1.660925689395424109e+00,
+        1.677762406016463717e+00, 1.696172326277082973e+00, 1.716198088860732467e+00, 1.737886327791014562e+00,
+        1.761287842885152410e+00, 1.786457786673686420e+00, 1.813455868772335587e+00, 1.842346578792652542e+00,
+        1.873199428986627521e+00, 1.906089217937612619e+00, 1.941096316736779451e+00, 1.978306979221816566e+00,
+        2.017813678003844337e+00, 2.059715468170813895e+00, 2.104118380732327493e+00, 2.151135848063375554e+00,
+        2.200889163814591418e+00, 2.253507979986114202e+00, 2.309130844113053375e+00, 2.367905779785113334e+00,
+        2.429990914023652954e+00, 2.495555155369085590e+00, 2.564778926893134514e+00, 2.637854958747451684e+00,
+        2.714989145296268067e+00, 2.796401472360280536e+00, 2.882327020626578700e+00, 2.973017051860293803e+00,
+        3.068740185193628238e+00, 3.169783671473487386e+00, 3.276454774427328601e+00, 3.389082268266156098e+00,
+        3.508018062292869136e+00, 3.633638964133530274e+00, 3.766348594369884204e+00, 3.906579466636309289e+00,
+        4.054795248667541120e+00, 4.211493221360917802e+00, 4.377206954666462219e+00, 4.552509221059946388e+00,
+        4.738015169510782826e+00, 4.934385785253587887e+00, 5.142331663338191074e+00, 5.362617126899976224e+00,
+        5.596064724397100194e+00, 5.843560143744373307e+00, 6.106057585381734693e+00, 6.384585640900671436e+00,
+        6.680253728973824449e+00, 6.994259146058412709e+00, 7.327894795748901060e+00, 7.682557667824588764e+00,
+        8.059758146071137270e+00, 8.461130232962342889e+00, 8.888442789395671080e+00, 9.343611899025485155e+00,
+        9.828714479494622022e+00, 1.034600327721380625e+01, 1.089792339849122916e+01, 1.148713054801325790e+01,
+        1.211651116619788555e+01, 1.278920468010096321e+01, 1.350862810871281096e+01, 1.427850329305334421e+01,
+        1.510288705493181327e+01, 1.598620462612703196e+01, 1.693328673269081128e+01, 1.794941076780000506e+01,
+        1.904034654190823159e+01, 2.021240716182964334e+01, 2.147250566192247370e+01, 2.282821809199713505e+01,
+        2.428785385941680425e+01, 2.586053422878117785e+01, 2.755628000354674426e+01, 2.938610955221109564e+01,
+        3.136214849990951329e+01, 3.349775258749912582e+01, 3.580764540799625468e+01, 3.830807296872530167e+01,
+        4.101697730155473447e+01, 4.395419165876113623e+01, 4.714166019494196927e+01, 5.060368545366659226e+01,
+        5.436720746019445252e+01, 5.846211877912138439e+01, 6.292162054058128784e+01, 6.778262518512416663e+01,
+        7.308621254265223015e+01, 7.887814686488147292e+01, 8.520946359734658334e+01, 9.213713603387774717e+01,
+        9.972483357670754649e+01, 1.080437851679046426e+02, 1.171737636088621692e+02, 1.272042089988687372e+02,
+        1.382355124664102373e+02, 1.503804848151483311e+02, 1.637660387526102742e+02, 1.785351181233383403e+02,
+        1.948489131607280604e+02, 2.128894073598352670e+02, 2.328623093447990790e+02, 2.550004322843281994e+02,
+        2.795675942672445782e+02, 3.068631259124280934e+02, 3.372270867451200874e+02, 3.710463099965576255e+02,
+        4.087614170466174911e+02, 4.508749684194593670e+02, 4.979609488959773491e+02, 5.506758209385785877e+02,
+        6.097714244663179092e+02, 6.761100535726473685e+02, 7.506821038741422446e+02, 8.346267600518081192e+02,
+        9.292562845315541998e+02, 1.036084578498234728e+03, 1.156860819661897657e+03, 1.293609142453808600e+03,
+        1.448675521854205144e+03, 1.624783259532197615e+03, 1.825098759915318560e+03, 2.053309635972617554e+03,
+        2.313717614494777200e+03, 2.611349236640186999e+03, 2.952087994093624299e+03, 3.342832332560548180e+03,
+        3.791684927756595099e+03, 4.308179838716318955e+03, 4.903555624570201673e+03, 5.591084343634811452e+03,
+        6.386468625571246341e+03, 7.308321829412979440e+03, 8.378749812799703561e+03, 9.624057218749638059e+03,
+        1.107560666191146008e+04, 1.277086605445904388e+04, 1.475468792019489452e+04, 1.708087537417066343e+04,
+        1.981410309695485051e+04, 2.303227888204754908e+04, 2.682945317928632535e+04, 3.131941178398428200e+04,
+        3.664012209706997997e+04, 4.295924836668690170e+04, 5.048100882639843572e+04, 5.945472133180055290e+04,
+        7.018547875172689579e+04, 8.304751726175694003e+04, 9.850099805053575446e+04, 1.171131266261766060e+05,
+        1.395847982160589845e+05, 1.667843016393077556e+05, 1.997900626520524686e+05, 2.399449946032992187e+05,
+        2.889257939838013232e+05, 3.488315309194304548e+05, 4.222972201496778447e+05, 5.126398246369253619e+05,
+        6.240464876221989792e+05, 7.618179073233615941e+05, 9.326839300224119257e+05, 1.145214007774297539e+06,
+        1.410352646274233119e+06, 1.742120041875863385e+06, 2.158531716934287014e+06, 2.682809410126426731e+06,
+        3.344980563595418861e+06, 4.183997972337706048e+06, 5.250558008165501752e+06, 6.610860174141680988e+06,
+        8.351639423967558693e+06, 1.058692532393929900e+07, 1.346715235106239409e+07, 1.719148271024263021e+07,
+        2.202453449027701694e+07, 2.831917301724337797e+07, 3.654767820268344932e+07, 4.734452657230626106e+07,
+        6.156534063509513873e+07, 8.036843026897869248e+07, 1.053280284359690289e+08, 1.385921689084126286e+08,
+        1.831036985925683524e+08, 2.429109457458640820e+08, 3.236062393759667463e+08, 4.329475218599986663e+08,
+        5.817432967962929479e+08, 7.851179789388191786e+08, 1.064329197627075307e+09, 1.449389582912945485e+09,
+        1.982866469377991849e+09, 2.725414314698094324e+09, 3.763867964111621444e+09, 5.223138814950990937e+09,
+        7.283785810644397704e+09, 1.020809642381158743e+10, 1.437899318470510521e+10, 2.035836812543633578e+10,
+        2.897499827080027444e+10, 4.145773751645494878e+10, 5.963837683872426287e+10, 8.626228483915530800e+10,
+        1.254667045389825180e+11, 1.835212982264913186e+11, 2.699812207400151604e+11, 3.994928452151922954e+11,
+        5.946380558701434550e+11, 8.904409967424091107e+11, 1.341551941677775838e+12, 2.033768550332151892e+12,
+        3.102627959875753214e+12, 4.763598321705862063e+12, 7.361420360560813584e+12, 1.145126961456557423e+13,
+        1.793314186996273926e+13, 2.827585501285792232e+13, 4.489297053678444669e+13, 7.177802872658499571e+13,
+        1.155855098545820625e+14, 1.874833886367883093e+14, 3.063510356402174454e+14, 5.043400653005970242e+14,
+        8.366163396892429890e+14, 1.398556351640947289e+15, 2.356335749516164682e+15, 4.001765167382637456e+15,
+        6.851375128404941445e+15, 1.182690111761543990e+16, 2.058673527013806443e+16, 3.613968784314904633e+16,
+        6.399112184394213551e+16, 1.143016185628376923e+17, 2.059881383915666443e+17, 3.745846788353680914e+17,
+        6.874443034683149068e+17, 1.273407643613485314e+18, 2.381241916829895366e+18, 4.495835617307108399e+18,
+        8.571442024901952701e+18, 1.650443584181656965e+19, 3.210100352421317851e+19, 6.307780124442703091e+19,
+        1.252404031157661279e+20, 2.513005295649985394e+20, 5.096776255690838436e+20, 1.045019200016673046e+21,
+        2.166476479260878466e+21, 4.542138145678395463e+21, 9.632082324449137128e+21, 2.066386536688254528e+22,
+        4.485529785554428251e+22, 9.853879573610977508e+22, 2.191158874464374408e+23, 4.932835964390971668e+23,
+        1.124501529971774363e+24, 2.596269136156756008e+24, 6.072292938313625501e+24, 1.438989066308003836e+25,
+        3.455841956406570469e+25, 8.412655191713576490e+25, 2.076289061650816510e+26, 5.196515024640220322e+26,
+        1.319173194089644043e+27, 3.397455895980380794e+27, 8.879057454438503591e+27, 2.355272361492064126e+28,
+        6.342762007722624824e+28, 1.734531093990859705e+29, 4.817893170606830871e+29, 1.359597346490148232e+30,
+        3.898969689906500392e+30, 1.136542986529989936e+31, 3.368450043991780017e+31, 1.015304084709817260e+32,
+        3.113144376221918237e+32, 9.713072739730140403e+32, 3.084517643581725946e+33, 9.972682139820497284e+33,
+        3.283625052288491586e+34, 1.101378785390827536e+35, 3.764333367592714297e+35, 1.311403465938242926e+36,
+        4.658135710682813672e+36, 1.687517347470511392e+37, 6.237053685018323490e+37, 2.352571314427744869e+38,
+        9.058938240219699936e+38, 3.562249097611136071e+39, 1.430959291578558210e+40, 5.873974584984375049e+40,
+        2.464828549811283787e+41, 1.057649203090855628e+42, 4.642475639281078035e+42, 2.085287118272421779e+43,
+        9.588439985186632177e+43, 4.514982011246092280e+44, 2.177974048341973204e+45, 1.076720976822900458e+46,
+        5.457267432929085589e+46, 2.836869270455781134e+47, 1.513103201392011626e+48, 8.283974667225617075e+48,
+        4.657239491995971344e+49, 2.689796370712836937e+50, 1.596597846911970388e+51, 9.744154538256586629e+51,
+        6.117238394843313065e+52, 3.952049650585241827e+53, 2.628701592074258213e+54, 1.800990196502679393e+55,
+        1.271554462563068383e+56, 9.255880104477760711e+56, 6.949737920133919393e+57, 5.385167200769965621e+58,
+        4.308493668102978774e+59, 3.560951557542178371e+60, 3.041888528384649992e+61, 2.687094441930837189e+62,
+        2.455920538900000855e+63, 2.323648254168641537e+64, 2.277129741584892331e+65, 2.312633552913224734e+66,
+        2.435407592981291129e+67, 2.660910388822465246e+68, 3.018105943423533920e+69, 3.555823489510192503e+70,
+        4.354188877793849013e+71, 5.544975795511813315e+72, 7.348276481909886336e+73, 1.013998025722423261e+75,
+        1.457911462244607943e+76, 2.185488876819505295e+77, 3.418022153286623008e+78, 5.580843920601835728e+79,
+        9.519586502799733908e+80, 1.697573578247197786e+82, 3.166906670990180014e+83, 6.185099106418675430e+84,
+        1.265541134386934377e+86, 2.714828965877756899e+87, 6.110386802964494082e+88, 1.444054086171083239e+90,
+        3.586083726638388165e+91, 9.365231868063239600e+92, 2.574080116205122449e+94, 7.452134689862302719e+95,
+        2.274309903836169819e+97, 7.323011134121164749e+98, 2.489816421737932462e+100, 8.946533386359281588e+101,
+        3.400401372391165979e+103, 1.368288186208928217e+105, 5.834277489829591931e+106, 2.638486937672383424e+108,
+        1.266728882767139521e+110, 6.462225178314182803e+111, 3.506432320607573604e+113, 2.025608933943268165e+115,
+        1.247041677084784707e+117, 8.189865188405279038e+118, 5.743610894406099965e+120, 4.305808934084489763e+122,
+        3.454156966079496755e+124, 2.968316601530352737e+126, 2.735456242372183592e+128, 2.706317176690077847e+130,
+        2.877679916342060385e+132, 3.292412878268106390e+134, 4.057840961953725969e+136, 5.393783049105737324e+138,
+        7.741523901672235406e+140, 1.201209962310668456e+143, 2.017456079556807301e+145, 3.672176623483062526e+147,
+        7.253163798058577630e+149, 1.556591535302570570e+152, 3.634399832790394885e+154, };
+
+__constant__ double* m_weights_double[8] = {
+    m_weights_double_1,
+    m_weights_double_2,
+    m_weights_double_3,
+    m_weights_double_4,
+    m_weights_double_5,
+    m_weights_double_6,
+    m_weights_double_7,
+    m_weights_double_8
+};
+__constant__ boost::math::size_t float_coefficients_size[8] = {4, 4, 8, 16, 32, 65, 129, 259};
+
+__constant__ boost::math::size_t double_coefficients_size[8] = {6, 6, 12, 24, 49, 98, 196, 391};
+
+template<typename T>
+struct coefficients_selector;
+
+template<>
+struct coefficients_selector<float>
+{
+    __device__ static const auto abscissas() { return m_abscissas_float; }
+    __device__ static const auto weights() { return m_weights_float; }
+    __device__ static const auto size() { return float_coefficients_size; }
+};
+
+template<>
+struct coefficients_selector<double>
+{
+    __device__ static const auto abscissas() { return m_abscissas_double; }
+    __device__ static const auto weights() { return m_weights_double; }
+    __device__ static const auto size() { return double_coefficients_size; }
+};
+
+template <class F, class Real, class Policy = boost::math::policies::policy<> >
+__device__ auto sinh_sinh_integrate_impl(const F& f, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+{
+    BOOST_MATH_STD_USING
+    using boost::math::constants::half;
+    using boost::math::constants::half_pi;
+    using boost::math::size_t;
+
+    constexpr auto function = "boost::math::quadrature::sinh_sinh<%1%>::integrate";
+
+    using K = decltype(f(static_cast<Real>(0)));
+    static_assert(!boost::math::is_integral<K>::value,
+                  "The return type cannot be integral, it must be either a real or complex floating point type.");
+
+    K y_max = f(boost::math::tools::max_value<Real>());
+    
+    if(abs(y_max) > boost::math::tools::epsilon<Real>())
+    {
+        return static_cast<K>(policies::raise_domain_error(function,
+           "The function you are trying to integrate does not go to zero at infinity, and instead evaluates to %1%", y_max, Policy()));
+    }
+
+    K y_min = f(-boost::math::tools::max_value<Real>());
+    
+    if(abs(y_min) > boost::math::tools::epsilon<Real>())
+    {
+        return static_cast<K>(policies::raise_domain_error(function,
+           "The function you are trying to integrate does not go to zero at -infinity, and instead evaluates to %1%", y_max, Policy()));
+    }
+
+    // Get the party started with two estimates of the integral:
+    const auto m_abscissas = coefficients_selector<Real>::abscissas();
+    const auto m_weights = coefficients_selector<Real>::weights();
+    const auto m_size = coefficients_selector<Real>::size();
+
+    K I0 = f(0)*half_pi<Real>();
+    Real L1_I0 = abs(I0);
+    for(size_t i = 0; i < m_size[0]; ++i)
+    {
+        Real x = m_abscissas[0][i];
+        K yp = f(x);
+        K ym = f(-x);
+        I0 += (yp + ym)*m_weights[0][i];
+        L1_I0 += (abs(yp)+abs(ym))*m_weights[0][i];
+    }
+
+    K I1 = I0;
+    Real L1_I1 = L1_I0;
+    for (size_t i = 0; i < m_size[1]; ++i)
+    {
+        Real x= m_abscissas[1][i];
+        K yp = f(x);
+        K ym = f(-x);
+        I1 += (yp + ym)*m_weights[1][i];
+        L1_I1 += (abs(yp) + abs(ym))*m_weights[1][i];
+    }
+
+    I1 *= half<Real>();
+    L1_I1 *= half<Real>();
+    Real err = abs(I0 - I1);
+
+    size_t i = 2;
+    for(; i <= 8U; ++i)
+    {
+        I0 = I1;
+        L1_I0 = L1_I1;
+
+        I1 = half<Real>()*I0;
+        L1_I1 = half<Real>()*L1_I0;
+        Real h = static_cast<Real>(1) / static_cast<Real>(1 << i);
+        K sum = 0;
+        Real absum = 0;
+
+        Real abterm1 = 1;
+        Real eps = boost::math::tools::epsilon<Real>()*L1_I1;
+
+        auto abscissa_row = m_abscissas[i];
+        auto weight_row = m_weights[i];
+
+        for(size_t j = 0; j < m_size[i]; ++j)
+        {
+            Real x = abscissa_row[j];
+            K yp = f(x);
+            K ym = f(-x);
+            sum += (yp + ym)*weight_row[j];
+            Real abterm0 = (abs(yp) + abs(ym))*weight_row[j];
+            absum += abterm0;
+
+            // We require two consecutive terms to be < eps in case we hit a zero of f.
+            if (x > static_cast<Real>(100) && abterm0 < eps && abterm1 < eps)
+            {
+                break;
+            }
+            abterm1 = abterm0;
+        }
+
+        I1 += sum*h;
+        L1_I1 += absum*h;
+        err = abs(I0 - I1);
+
+        if (!(boost::math::isfinite)(L1_I1))
+        {
+            constexpr auto err_msg = "The sinh_sinh quadrature evaluated your function at a singular point, leading to the value %1%.\n"
+               "sinh_sinh quadrature cannot handle singularities in the domain.\n"
+               "If you are sure your function has no singularities, please submit a bug against boost.math\n";
+            return static_cast<K>(policies::raise_evaluation_error(function, err_msg, I1, Policy()));
+        }
+        if (err <= tolerance*L1_I1)
+        {
+            break;
+        }
+    }
+
+    if (error)
+    {
+        *error = err;
+    }
+
+    if (L1)
+    {
+        *L1 = L1_I1;
+    }
+
+    if (levels)
+    {
+       *levels = i;
+    }
+
+    return I1;
+}
+
+} // Namespace detail
+} // Namespace quadrature
+} // Namespace math
+} // Namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
+#endif // BOOST_MATH_QUADRATURE_DETAIL_SINH_SINH_DETAIL_HPP
diff --git a/include/boost/math/quadrature/exp_sinh.hpp b/include/boost/math/quadrature/exp_sinh.hpp
index f28493737e..d3148e0c0a 100644
--- a/include/boost/math/quadrature/exp_sinh.hpp
+++ b/include/boost/math/quadrature/exp_sinh.hpp
@@ -15,11 +15,15 @@
 #ifndef BOOST_MATH_QUADRATURE_EXP_SINH_HPP
 #define BOOST_MATH_QUADRATURE_EXP_SINH_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/quadrature/detail/exp_sinh_detail.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <limits>
 #include <memory>
 #include <string>
-#include <boost/math/quadrature/detail/exp_sinh_detail.hpp>
 
 namespace boost{ namespace math{ namespace quadrature {
 
@@ -98,4 +102,79 @@ auto exp_sinh<Real, Policy>::integrate(const F& f, Real tolerance, Real* error,
 
 
 }}}
-#endif
+
+#endif // BOOST_MATH_HAS_NVRTC
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/constants/constants.hpp>
+
+namespace boost { 
+namespace math { 
+namespace quadrature {
+
+template <class F, class Real, class Policy = policies::policy<> >
+__device__ auto exp_sinh_integrate(const F& f, Real a, Real b, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+{
+    BOOST_MATH_STD_USING
+
+    using K = decltype(f(a));
+    static_assert(!boost::math::is_integral<K>::value,
+                  "The return type cannot be integral, it must be either a real or complex floating point type.");
+
+    constexpr auto function = "boost::math::quadrature::exp_sinh<%1%>::integrate";
+
+    // Neither limit may be a NaN:
+    if((boost::math::isnan)(a) || (boost::math::isnan)(b))
+    {
+       return static_cast<K>(policies::raise_domain_error(function, "NaN supplied as one limit of integration - sorry I don't know what to do", a, Policy()));
+    }
+    // Right limit is infinite:
+    if ((boost::math::isfinite)(a) && (b >= boost::math::tools::max_value<Real>()))
+    {
+        // If a = 0, don't use an additional level of indirection:
+        if (a == static_cast<Real>(0))
+        {
+            return detail::exp_sinh_integrate_impl(f, tolerance, error, L1, levels);
+        }
+        const auto u = [&](Real t)->K { return f(t + a); };
+        return detail::exp_sinh_integrate_impl(u, tolerance, error, L1, levels);
+    }
+
+    if ((boost::math::isfinite)(b) && a <= -boost::math::tools::max_value<Real>())
+    {
+        const auto u = [&](Real t)->K { return f(b-t);};
+        return detail::exp_sinh_integrate_impl(u, tolerance, error, L1, levels);
+    }
+
+    // Infinite limits:
+    if ((a <= -boost::math::tools::max_value<Real>()) && (b >= boost::math::tools::max_value<Real>()))
+    {
+        return static_cast<K>(policies::raise_domain_error(function, "Use sinh_sinh quadrature for integration over the whole real line; exp_sinh is for half infinite integrals.", a, Policy()));
+    }
+    // If we get to here then both ends must necessarily be finite:
+    return static_cast<K>(policies::raise_domain_error(function, "Use tanh_sinh quadrature for integration over finite domains; exp_sinh is for half infinite integrals.", a, Policy()));
+}
+
+template <class F, class Real, class Policy = policies::policy<> >
+__device__ auto exp_sinh_integrate(const F& f, Real tolerance, Real* error, Real* L1, boost::math::size_t* levels)
+{
+    BOOST_MATH_STD_USING
+    constexpr auto function = "boost::math::quadrature::exp_sinh<%1%>::integrate";
+    if (abs(tolerance) > 1) {
+        return policies::raise_domain_error(function, "The tolerance provided (%1%) is unusually large; did you confuse it with a domain bound?", tolerance, Policy());
+    }
+    return detail::exp_sinh_integrate_impl(f, tolerance, error, L1, levels);
+}
+
+} // namespace quadrature
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
+#endif // BOOST_MATH_QUADRATURE_EXP_SINH_HPP
diff --git a/include/boost/math/quadrature/sinh_sinh.hpp b/include/boost/math/quadrature/sinh_sinh.hpp
index ed958eb8d2..7aabcb4376 100644
--- a/include/boost/math/quadrature/sinh_sinh.hpp
+++ b/include/boost/math/quadrature/sinh_sinh.hpp
@@ -1,4 +1,5 @@
 // Copyright Nick Thompson, 2017
+// Copyright Matt Borland, 2024
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -15,10 +16,17 @@
 #ifndef BOOST_MATH_QUADRATURE_SINH_SINH_HPP
 #define BOOST_MATH_QUADRATURE_SINH_SINH_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/quadrature/detail/sinh_sinh_detail.hpp>
+#include <boost/math/policies/error_handling.hpp>
+
+#ifndef BOOST_MATH_HAS_NVRTC
+
 #include <cmath>
 #include <limits>
 #include <memory>
-#include <boost/math/quadrature/detail/sinh_sinh_detail.hpp>
 
 namespace boost{ namespace math{ namespace quadrature {
 
@@ -40,4 +48,25 @@ class sinh_sinh
 };
 
 }}}
-#endif
+
+#endif // BOOST_MATH_HAS_NVRTC
+
+#ifdef BOOST_MATH_ENABLE_CUDA
+
+namespace boost {
+namespace math {
+namespace quadrature {
+
+template <class F, class Real, class Policy = boost::math::policies::policy<> >
+__device__ auto sinh_sinh_integrate(const F& f, Real tol = boost::math::tools::root_epsilon<Real>(), Real* error = nullptr, Real* L1 = nullptr, boost::math::size_t* levels = nullptr)
+{
+    return detail::sinh_sinh_integrate_impl(f, tol, error, L1, levels);
+}
+
+} // namespace quadrature
+} // namespace math
+} // namespace boost
+
+#endif // BOOST_MATH_ENABLE_CUDA
+
+#endif // BOOST_MATH_QUADRATURE_SINH_SINH_HPP
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 2eb7810081..b3e1992c63 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -9,6 +9,12 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
+# Quad
+run test_exp_sinh_quad_float.cu ;
+run test_exp_sinh_quad_double.cu ;
+run test_sinh_sinh_quad_float.cu ;
+run test_sinh_sinh_quad_double.cu ;
+
 # Distributions
 run test_arcsine_cdf_double.cu ;
 run test_arcsine_cdf_float.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 0786564d7c..46dd0e257f 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -9,6 +9,12 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
+# Quad
+run test_exp_sinh_quad_nvrtc_float.cpp ;
+run test_exp_sinh_quad_nvrtc_double.cpp ;
+run test_sinh_sinh_quad_nvrtc_float.cpp ;
+run test_sinh_sinh_quad_nvrtc_double.cpp ;
+
 # Distributions
 run test_arcsine_cdf_nvrtc_double.cpp ;
 run test_arcsine_cdf_nvrtc_float.cpp ;
diff --git a/test/test_exp_sinh_quad_double.cu b/test/test_exp_sinh_quad_double.cu
new file mode 100644
index 0000000000..59f6d8a12f
--- /dev/null
+++ b/test/test_exp_sinh_quad_double.cu
@@ -0,0 +1,133 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/quadrature/exp_sinh.hpp>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/tools/precision.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+__host__ __device__ float_type func(float_type x)
+{
+    BOOST_MATH_STD_USING
+    return 1/(1+x*x);
+}
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::exp_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = M_PI * (static_cast<float_type>(i) / numElements);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid = (numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::quadrature::exp_sinh<float_type> integrator;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(integrator.integrate(func, tol, &error, &L1));
+    }
+    double t = w.elapsed();
+    // check the results
+    int failed_count = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+        if (eps > 10)
+        {
+            std::cerr   << std::setprecision(std::numeric_limits<float_type>::digits10)
+                        << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i]
+                        << "\n  Host: " << results[i]
+                        << "\n   Eps: " << eps << "\n";
+            failed_count++;
+        }
+        if (failed_count > 100)
+        {
+            break;
+        }
+    }
+
+    if (failed_count != 0)
+    {
+        std::cout << "Test FAILED" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_exp_sinh_quad_float.cu b/test/test_exp_sinh_quad_float.cu
new file mode 100644
index 0000000000..1472dbcde8
--- /dev/null
+++ b/test/test_exp_sinh_quad_float.cu
@@ -0,0 +1,133 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/quadrature/exp_sinh.hpp>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/tools/precision.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+__host__ __device__ float_type func(float_type x)
+{
+    BOOST_MATH_STD_USING
+    return 1/(1+x*x);
+}
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::exp_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = M_PI * (static_cast<float_type>(i) / numElements);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid = (numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::quadrature::exp_sinh<float_type> integrator;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(integrator.integrate(func, tol, &error, &L1));
+    }
+    double t = w.elapsed();
+    // check the results
+    int failed_count = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+        if (eps > 10)
+        {
+            std::cerr   << std::setprecision(std::numeric_limits<float_type>::digits10)
+                        << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i]
+                        << "\n  Host: " << results[i]
+                        << "\n   Eps: " << eps << "\n";
+            failed_count++;
+        }
+        if (failed_count > 100)
+        {
+            break;
+        }
+    }
+
+    if (failed_count != 0)
+    {
+        std::cout << "Test FAILED" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_exp_sinh_quad_nvrtc_double.cpp b/test/test_exp_sinh_quad_nvrtc_double.cpp
new file mode 100644
index 0000000000..bfd5080928
--- /dev/null
+++ b/test/test_exp_sinh_quad_nvrtc_double.cpp
@@ -0,0 +1,206 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/quadrature/exp_sinh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/quadrature/exp_sinh.hpp>
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+extern "C" __global__ 
+void test_expm1_kernel(const float_type*, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::exp_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+)";
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expm1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expm1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expm1_kernel"), "Failed to get kernel function");
+
+        int numElements = 50000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        float_type tol = boost::math::tools::root_epsilon<float_type>();
+        float_type error;
+        float_type L1;
+        boost::math::quadrature::exp_sinh<float_type> integrator;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = integrator.integrate(func, tol, &error, &L1);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_exp_sinh_quad_nvrtc_float.cpp b/test/test_exp_sinh_quad_nvrtc_float.cpp
new file mode 100644
index 0000000000..b472e5597c
--- /dev/null
+++ b/test/test_exp_sinh_quad_nvrtc_float.cpp
@@ -0,0 +1,206 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/quadrature/exp_sinh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/quadrature/exp_sinh.hpp>
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+extern "C" __global__ 
+void test_expm1_kernel(const float_type*, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::exp_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+)";
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expm1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expm1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expm1_kernel"), "Failed to get kernel function");
+
+        int numElements = 50000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        float_type tol = boost::math::tools::root_epsilon<float_type>();
+        float_type error;
+        float_type L1;
+        boost::math::quadrature::exp_sinh<float_type> integrator;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = integrator.integrate(func, tol, &error, &L1);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sinh_sinh_quad_double.cu b/test/test_sinh_sinh_quad_double.cu
new file mode 100644
index 0000000000..bf7490fa4b
--- /dev/null
+++ b/test/test_sinh_sinh_quad_double.cu
@@ -0,0 +1,133 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/quadrature/sinh_sinh.hpp>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/tools/precision.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+__host__ __device__ float_type func(float_type x)
+{
+    BOOST_MATH_STD_USING
+    return 1/(1+x*x);
+}
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::sinh_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = M_PI * (static_cast<float_type>(i) / numElements);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid = (numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::quadrature::sinh_sinh<float_type> integrator;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(integrator.integrate(func, tol, &error, &L1));
+    }
+    double t = w.elapsed();
+    // check the results
+    int failed_count = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+        if (eps > 10)
+        {
+            std::cerr   << std::setprecision(std::numeric_limits<float_type>::digits10)
+                        << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i]
+                        << "\n  Host: " << results[i]
+                        << "\n   Eps: " << eps << "\n";
+            failed_count++;
+        }
+        if (failed_count > 100)
+        {
+            break;
+        }
+    }
+
+    if (failed_count != 0)
+    {
+        std::cout << "Test FAILED" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sinh_sinh_quad_float.cu b/test/test_sinh_sinh_quad_float.cu
new file mode 100644
index 0000000000..b84e316af9
--- /dev/null
+++ b/test/test_sinh_sinh_quad_float.cu
@@ -0,0 +1,133 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/quadrature/sinh_sinh.hpp>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/tools/precision.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+__host__ __device__ float_type func(float_type x)
+{
+    BOOST_MATH_STD_USING
+    return 1/(1+x*x);
+}
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::sinh_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = M_PI * (static_cast<float_type>(i) / numElements);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 512;
+    int blocksPerGrid = (numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::quadrature::sinh_sinh<float_type> integrator;
+    for(int i = 0; i < numElements; ++i)
+    {
+       results.push_back(integrator.integrate(func, tol, &error, &L1));
+    }
+    double t = w.elapsed();
+    // check the results
+    int failed_count = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+        if (eps > 10)
+        {
+            std::cerr   << std::setprecision(std::numeric_limits<float_type>::digits10)
+                        << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i]
+                        << "\n  Host: " << results[i]
+                        << "\n   Eps: " << eps << "\n";
+            failed_count++;
+        }
+        if (failed_count > 100)
+        {
+            break;
+        }
+    }
+
+    if (failed_count != 0)
+    {
+        std::cout << "Test FAILED" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sinh_sinh_quad_nvrtc_double.cpp b/test/test_sinh_sinh_quad_nvrtc_double.cpp
new file mode 100644
index 0000000000..5342e97785
--- /dev/null
+++ b/test/test_sinh_sinh_quad_nvrtc_double.cpp
@@ -0,0 +1,206 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/quadrature/sinh_sinh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <boost/math/quadrature/sinh_sinh.hpp>
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+extern "C" __global__ 
+void test_sinh_sinh_kernel(const float_type*, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::sinh_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+)";
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sinh_sinh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sinh_sinh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sinh_sinh_kernel"), "Failed to get kernel function");
+
+        int numElements = 50000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        float_type tol = boost::math::tools::root_epsilon<float_type>();
+        float_type error;
+        float_type L1;
+        boost::math::quadrature::sinh_sinh<float_type> integrator;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = integrator.integrate(func, tol, &error, &L1);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sinh_sinh_quad_nvrtc_float.cpp b/test/test_sinh_sinh_quad_nvrtc_float.cpp
new file mode 100644
index 0000000000..37a8c12525
--- /dev/null
+++ b/test/test_sinh_sinh_quad_nvrtc_float.cpp
@@ -0,0 +1,206 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/quadrature/sinh_sinh.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+#include <cuda.h>
+#include <cuda_runtime.h>
+#include <nvrtc.h>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <boost/math/quadrature/sinh_sinh.hpp>
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+extern "C" __global__ 
+void test_sinh_sinh_kernel(const float_type*, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    float_type tol = boost::math::tools::root_epsilon<float_type>();
+    float_type error;
+    float_type L1;
+    boost::math::size_t levels;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::quadrature::sinh_sinh_integrate(func, tol, &error, &L1, &levels);
+    }
+}
+)";
+
+__host__ __device__ float_type func(float_type x)
+{
+    return 1/(1+x*x);
+}
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sinh_sinh_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sinh_sinh_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sinh_sinh_kernel"), "Failed to get kernel function");
+
+        int numElements = 50000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        float_type tol = boost::math::tools::root_epsilon<float_type>();
+        float_type error;
+        float_type L1;
+        boost::math::quadrature::sinh_sinh<float_type> integrator;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            auto res = integrator.integrate(func, tol, &error, &L1);
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From ff72eaad44ffddfa25b01815a7bb1730b3cb81e7 Mon Sep 17 00:00:00 2001
From: Lucas Colley <lucas.colley8@gmail.com>
Date: Mon, 16 Sep 2024 13:55:10 +0100
Subject: [PATCH 380/399] cmake: directly define project version (#1199)

Co-authored-by: Peter Dimov <pdimov@gmail.com>
---
 CMakeLists.txt               |  2 +-
 test/CMakeLists.txt          |  2 ++
 test/check_cmake_version.cpp | 27 +++++++++++++++++++++++++++
 3 files changed, 30 insertions(+), 1 deletion(-)
 create mode 100644 test/check_cmake_version.cpp

diff --git a/CMakeLists.txt b/CMakeLists.txt
index d05c44a9e8..4c4fc1ddc8 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -5,7 +5,7 @@
 
 cmake_minimum_required(VERSION 3.5...3.16)
 
-project(boost_math VERSION "${BOOST_SUPERPROJECT_VERSION}" LANGUAGES CXX)
+project(boost_math VERSION 1.87.0 LANGUAGES CXX)
 
 add_library(boost_math INTERFACE)
 
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index fef1189f1d..95d7849f6b 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -6,6 +6,8 @@ include(BoostTestJamfile OPTIONAL RESULT_VARIABLE HAVE_BOOST_TEST)
 
 if(HAVE_BOOST_TEST)
 
+    boost_test(SOURCES check_cmake_version.cpp ARGUMENTS ${PROJECT_VERSION} LINK_LIBRARIES Boost::core Boost::config)    
+
     if (BOOST_MATH_ENABLE_CUDA)
 
         message(STATUS "Building boost.math with CUDA")
diff --git a/test/check_cmake_version.cpp b/test/check_cmake_version.cpp
new file mode 100644
index 0000000000..2fd4648368
--- /dev/null
+++ b/test/check_cmake_version.cpp
@@ -0,0 +1,27 @@
+// Check whether the version in CMakeLists.txt is up to date
+//
+// Copyright 2018 Peter Dimov
+//
+// Distributed under the Boost Software License, Version 1.0.
+//
+// See accompanying file LICENSE_1_0.txt or copy at
+// http://www.boost.org/LICENSE_1_0.txt
+
+#include <boost/core/lightweight_test.hpp>
+#include <boost/version.hpp>
+#include <cstdio>
+
+int main( int ac, char const* av[] )
+{
+    BOOST_TEST_EQ( ac, 2 );
+
+    if( ac >= 2 )
+    {
+        char version[ 64 ];
+        std::sprintf( version, "%d.%d.%d", BOOST_VERSION / 100000, BOOST_VERSION / 100 % 1000, BOOST_VERSION % 100 );
+
+        BOOST_TEST_CSTR_EQ( av[1], version );
+    }
+
+    return boost::report_errors();
+}

From 1324401c92f793fcd23b6a4a49f81ad49326e0db Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 16 Sep 2024 14:04:07 -0400
Subject: [PATCH 381/399] Add GPU support to airy functions

Add SYCL testing of ariy functions

Add CUDA testing of airy functions

Add NVRTC testing of airy functions

Add GPU support to ellint rc

Add GPU support to ellint rd

Add GPU support to ellint rf

Add GPU support to ellint rg

Add GPU support to ellint rj

Add GPU support to ellint d

Add GPU support to ellint_1

Markup forward and add ellint_3 return type def for NVRTC platform

Add CUDA testing of ellint 1

NVRTC fixes

Add NVRTC testing of ellint_1

Add GPU support to ellint_2

Add CUDA testing of ellint_2

Fix NVRTC errors

Add NVRTC testing of ellint_2

Add GPU support to atanh

Add GPU support to ellint_3

Add NVRTC testing of ellint_3

Add CUDA testing of ellint_3

Replace use of static const char*

Add SYCL testing of ellint_1

Add SYCL testing of ellint 2 with slight tolerance bump

Remove recursion from ellint_rj

Add ellint_d CUDA testing

Add NVRTC testing of ellint_d

Add SYCL testing of ellint_d

Remove SYCL ellint_3 support

Update docs

Add GPU support to jacobi zeta

Add CUDA testing of jacobi zeta

Add NVRTC testing of jacobi zeta

Add SYCL testing of jacobi zeta

Add GPU support to heuman_lambda

Add NVRTC testing of heuman lambda

Add CUDA testing of heuman_lambda

Add SYCL testing of heuman lambda

Add markers to docs

Add marker for CUDA only functions in the docs
---
 doc/overview/gpu.qbk                          |   5 +-
 doc/sf/ellint_carlson.qbk                     |  40 ++--
 doc/sf/ellint_legendre.qbk                    |  72 +++----
 include/boost/math/special_functions/airy.hpp |  52 ++---
 .../boost/math/special_functions/atanh.hpp    |  10 +-
 .../boost/math/special_functions/ellint_1.hpp |  65 +++---
 .../boost/math/special_functions/ellint_2.hpp |  69 ++++---
 .../boost/math/special_functions/ellint_3.hpp |  22 +-
 .../boost/math/special_functions/ellint_d.hpp |  21 +-
 .../math/special_functions/ellint_rc.hpp      |  12 +-
 .../math/special_functions/ellint_rd.hpp      |  33 +--
 .../math/special_functions/ellint_rf.hpp      |  23 ++-
 .../math/special_functions/ellint_rg.hpp      |  23 +--
 .../math/special_functions/ellint_rj.hpp      | 116 +++++++----
 .../math/special_functions/heuman_lambda.hpp  |  22 +-
 .../math/special_functions/jacobi_zeta.hpp    |  10 +-
 .../boost/math/special_functions/math_fwd.hpp | 154 +++++++-------
 include/boost/math/tools/workaround.hpp       |   2 +-
 test/cuda_jamfile                             |  22 ++
 test/nvrtc_jamfile                            |  23 +++
 test/sycl_jamfile                             |   8 +
 test/test_airy.cpp                            |  12 ++
 test/test_airy_ai_double.cu                   | 100 +++++++++
 test/test_airy_ai_float.cu                    | 100 +++++++++
 test/test_airy_ai_nvrtc_double.cpp            | 190 ++++++++++++++++++
 test/test_airy_ai_nvrtc_float.cpp             | 190 ++++++++++++++++++
 test/test_airy_ai_prime_double.cu             | 100 +++++++++
 test/test_airy_ai_prime_float.cu              | 100 +++++++++
 test/test_airy_ai_prime_nvrtc_double.cpp      | 190 ++++++++++++++++++
 test/test_airy_ai_prime_nvrtc_float.cpp       | 190 ++++++++++++++++++
 test/test_airy_bi_double.cu                   | 100 +++++++++
 test/test_airy_bi_float.cu                    | 100 +++++++++
 test/test_airy_bi_nvrtc_double.cpp            | 190 ++++++++++++++++++
 test/test_airy_bi_nvrtc_float.cpp             | 190 ++++++++++++++++++
 test/test_airy_bi_prime_double.cu             | 100 +++++++++
 test/test_airy_bi_prime_float.cu              | 100 +++++++++
 test/test_airy_bi_prime_nvrtc_double.cpp      | 190 ++++++++++++++++++
 test/test_airy_bi_prime_nvrtc_float.cpp       | 190 ++++++++++++++++++
 test/test_ellint_1.cpp                        |   3 +
 test/test_ellint_1.hpp                        |   6 +
 test/test_ellint_1_double.cu                  | 106 ++++++++++
 test/test_ellint_1_float.cu                   | 100 +++++++++
 test/test_ellint_1_nvrtc_double.cpp           | 190 ++++++++++++++++++
 test/test_ellint_1_nvrtc_float.cpp            | 190 ++++++++++++++++++
 test/test_ellint_2.cpp                        |   7 +
 test/test_ellint_2.hpp                        |   9 +
 test/test_ellint_2_double.cu                  | 100 +++++++++
 test/test_ellint_2_float.cu                   | 100 +++++++++
 test/test_ellint_2_nvrtc_double.cpp           | 190 ++++++++++++++++++
 test/test_ellint_2_nvrtc_float.cpp            | 190 ++++++++++++++++++
 test/test_ellint_3_double.cu                  | 104 ++++++++++
 test/test_ellint_3_float.cu                   | 104 ++++++++++
 test/test_ellint_3_nvrtc_double.cpp           | 190 ++++++++++++++++++
 test/test_ellint_3_nvrtc_float.cpp            | 190 ++++++++++++++++++
 test/test_ellint_d.cpp                        |   3 +
 test/test_ellint_d.hpp                        |   8 +
 test/test_ellint_d_double.cu                  | 104 ++++++++++
 test/test_ellint_d_float.cu                   | 104 ++++++++++
 test/test_ellint_d_nvrtc_double.cpp           | 190 ++++++++++++++++++
 test/test_ellint_d_nvrtc_float.cpp            | 190 ++++++++++++++++++
 test/test_heuman_lambda.cpp                   |   3 +
 test/test_heuman_lambda.hpp                   |   6 +
 test/test_heuman_lambda_double.cu             | 120 +++++++++++
 test/test_heuman_lambda_float.cu              | 120 +++++++++++
 test/test_heumann_lambda_nvrtc_double.cpp     | 190 ++++++++++++++++++
 test/test_heumann_lambda_nvrtc_float.cpp      | 190 ++++++++++++++++++
 test/test_jacobi_zeta.cpp                     |   3 +
 test/test_jacobi_zeta.hpp                     |   6 +
 test/test_jacobi_zeta_double.cu               | 120 +++++++++++
 test/test_jacobi_zeta_float.cu                | 120 +++++++++++
 test/test_jacobi_zeta_nvrtc_double.cpp        | 190 ++++++++++++++++++
 test/test_jacobi_zeta_nvrtc_float.cpp         | 190 ++++++++++++++++++
 72 files changed, 6436 insertions(+), 336 deletions(-)
 create mode 100644 test/test_airy_ai_double.cu
 create mode 100644 test/test_airy_ai_float.cu
 create mode 100644 test/test_airy_ai_nvrtc_double.cpp
 create mode 100644 test/test_airy_ai_nvrtc_float.cpp
 create mode 100644 test/test_airy_ai_prime_double.cu
 create mode 100644 test/test_airy_ai_prime_float.cu
 create mode 100644 test/test_airy_ai_prime_nvrtc_double.cpp
 create mode 100644 test/test_airy_ai_prime_nvrtc_float.cpp
 create mode 100644 test/test_airy_bi_double.cu
 create mode 100644 test/test_airy_bi_float.cu
 create mode 100644 test/test_airy_bi_nvrtc_double.cpp
 create mode 100644 test/test_airy_bi_nvrtc_float.cpp
 create mode 100644 test/test_airy_bi_prime_double.cu
 create mode 100644 test/test_airy_bi_prime_float.cu
 create mode 100644 test/test_airy_bi_prime_nvrtc_double.cpp
 create mode 100644 test/test_airy_bi_prime_nvrtc_float.cpp
 create mode 100644 test/test_ellint_1_double.cu
 create mode 100644 test/test_ellint_1_float.cu
 create mode 100644 test/test_ellint_1_nvrtc_double.cpp
 create mode 100644 test/test_ellint_1_nvrtc_float.cpp
 create mode 100644 test/test_ellint_2_double.cu
 create mode 100644 test/test_ellint_2_float.cu
 create mode 100644 test/test_ellint_2_nvrtc_double.cpp
 create mode 100644 test/test_ellint_2_nvrtc_float.cpp
 create mode 100644 test/test_ellint_3_double.cu
 create mode 100644 test/test_ellint_3_float.cu
 create mode 100644 test/test_ellint_3_nvrtc_double.cpp
 create mode 100644 test/test_ellint_3_nvrtc_float.cpp
 create mode 100644 test/test_ellint_d_double.cu
 create mode 100644 test/test_ellint_d_float.cu
 create mode 100644 test/test_ellint_d_nvrtc_double.cpp
 create mode 100644 test/test_ellint_d_nvrtc_float.cpp
 create mode 100644 test/test_heuman_lambda_double.cu
 create mode 100644 test/test_heuman_lambda_float.cu
 create mode 100644 test/test_heumann_lambda_nvrtc_double.cpp
 create mode 100644 test/test_heumann_lambda_nvrtc_float.cpp
 create mode 100644 test/test_jacobi_zeta_double.cu
 create mode 100644 test/test_jacobi_zeta_float.cu
 create mode 100644 test/test_jacobi_zeta_nvrtc_double.cpp
 create mode 100644 test/test_jacobi_zeta_nvrtc_float.cpp

diff --git a/doc/overview/gpu.qbk b/doc/overview/gpu.qbk
index b97b059a60..7fb27e645e 100644
--- a/doc/overview/gpu.qbk
+++ b/doc/overview/gpu.qbk
@@ -3,8 +3,9 @@
 [h4 GPU Support]
 
 Selected functions, distributions, tools, etc. support running on both host and devices.
-These functions will have the annotation `BOOST_MATH_GPU_ENABLED` next to their individual documentation.
-We test using CUDA (both NVCC and NVRTC) as well as SYCL to provide a wide range of support.
+These functions will have the annotation `BOOST_MATH_GPU_ENABLED` or `BOOST_MATH_CUDA_ENABLED` next to their individual documentation.
+Functions marked with `BOOST_MATH_GPU_ENABLED` are tested using CUDA (both NVCC and NVRTC) as well as SYCL to provide a wide range of support.
+Functions marked with `BOOST_MATH_CUDA_ENABLED` are few, but due to its restrictions SYCL is unsupported.
 
 [h4 Policies]
 
diff --git a/doc/sf/ellint_carlson.qbk b/doc/sf/ellint_carlson.qbk
index ca39cd6bef..db45697463 100644
--- a/doc/sf/ellint_carlson.qbk
+++ b/doc/sf/ellint_carlson.qbk
@@ -17,10 +17,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z)
 
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z, const ``__Policy``&)
 
   }} // namespaces
 
@@ -32,10 +32,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z)
 
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z, const ``__Policy``&)
 
   }} // namespaces
 
@@ -47,10 +47,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2, class T3, class T4>
-  ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p)
 
   template <class T1, class T2, class T3, class T4, class ``__Policy``>
-  ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p, const ``__Policy``&)
 
   }} // namespaces
 
@@ -62,10 +62,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_rc(T1 x, T2 y)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rc(T1 x, T2 y)
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_rc(T1 x, T2 y, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rc(T1 x, T2 y, const ``__Policy``&)
 
   }} // namespaces
 
@@ -76,10 +76,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z)
 
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z, const ``__Policy``&)
 
   }} // namespaces
 
@@ -98,10 +98,10 @@ when the arguments are of different types: otherwise the return is the same type
 as the arguments.
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z)
   
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rf(T1 x, T2 y, T3 z, const ``__Policy``&)
   
 Returns Carlson's Elliptic Integral ['R[sub F]]:
 
@@ -113,10 +113,10 @@ one may be zero.  Otherwise returns the result of __domain_error.
 [optional_policy]
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z)
   
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rd(T1 x, T2 y, T3 z, const ``__Policy``&)
   
 Returns Carlson's elliptic integral R[sub D]:
 
@@ -128,10 +128,10 @@ zero, and that z >= 0.  Otherwise returns the result of __domain_error.
 [optional_policy]
 
   template <class T1, class T2, class T3, class T4>
-  ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p)
 
   template <class T1, class T2, class T3, class T4, class ``__Policy``>
-  ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rj(T1 x, T2 y, T3 z, T4 p, const ``__Policy``&)
 
 Returns Carlson's elliptic integral R[sub J]:
   
@@ -149,10 +149,10 @@ using the relation:
 [equation ellint17]
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_rc(T1 x, T2 y)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rc(T1 x, T2 y)
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_rc(T1 x, T2 y, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rc(T1 x, T2 y, const ``__Policy``&)
 
 Returns Carlson's elliptic integral R[sub C]:
   
@@ -170,10 +170,10 @@ using the relation:
 [equation ellint18]
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z)
   
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z, const ``__Policy``&)
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_rg(T1 x, T2 y, T3 z, const ``__Policy``&)
   
 Returns Carlson's elliptic integral ['R[sub G]:]
 
diff --git a/doc/sf/ellint_legendre.qbk b/doc/sf/ellint_legendre.qbk
index c780a9b019..50b633af9f 100644
--- a/doc/sf/ellint_legendre.qbk
+++ b/doc/sf/ellint_legendre.qbk
@@ -17,16 +17,16 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_1(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T1 k, T2 phi);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_1(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T1 k, T2 phi, const ``__Policy``&);
 
   template <class T>
-  ``__sf_result`` ellint_1(T k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T k);
 
   template <class T, class ``__Policy``>
-  ``__sf_result`` ellint_1(T k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T k, const ``__Policy``&);
 
   }} // namespaces
   
@@ -42,10 +42,10 @@ when T1 and T2 are different types: when they are the same type then the result
 is the same type as the arguments.
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_1(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T1 k, T2 phi);
   
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_1(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T1 k, T2 phi, const ``__Policy``&);
   
 Returns the incomplete elliptic integral of the first kind ['F([phi], k)]:
 
@@ -56,10 +56,10 @@ Requires k[super 2]sin[super 2](phi) < 1, otherwise returns the result of __doma
 [optional_policy]
 
   template <class T>
-  ``__sf_result`` ellint_1(T k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T k);
   
   template <class T>
-  ``__sf_result`` ellint_1(T k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_1(T k, const ``__Policy``&);
   
 Returns the complete elliptic integral of the first kind ['K(k)]:
 
@@ -123,16 +123,16 @@ and
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_2(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T1 k, T2 phi);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_2(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T1 k, T2 phi, const ``__Policy``&);
 
   template <class T>
-  ``__sf_result`` ellint_2(T k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T k);
 
   template <class T, class ``__Policy``>
-  ``__sf_result`` ellint_2(T k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T k, const ``__Policy``&);
 
   }} // namespaces
   
@@ -148,10 +148,10 @@ when T1 and T2 are different types: when they are the same type then the result
 is the same type as the arguments.
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_2(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T1 k, T2 phi);
   
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_2(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T1 k, T2 phi, const ``__Policy``&);
   
 Returns the incomplete elliptic integral of the second kind ['E([phi], k)]:
 
@@ -162,10 +162,10 @@ Requires k[super 2]sin[super 2](phi) < 1, otherwise returns the result of __doma
 [optional_policy]
 
   template <class T>
-  ``__sf_result`` ellint_2(T k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T k);
   
   template <class T>
-  ``__sf_result`` ellint_2(T k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_2(T k, const ``__Policy``&);
   
 Returns the complete elliptic integral of the second kind ['E(k)]:
 
@@ -230,16 +230,16 @@ and
   namespace boost { namespace math {
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi);
 
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi, const ``__Policy``&);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi, const ``__Policy``&);
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_3(T1 k, T2 n);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_3(T1 k, T2 n, const ``__Policy``&);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, const ``__Policy``&);
 
   }} // namespaces
   
@@ -255,10 +255,10 @@ when the arguments are of different types: when they are the same type then the
 is the same type as the arguments.
 
   template <class T1, class T2, class T3>
-  ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi);
   
   template <class T1, class T2, class T3, class ``__Policy``>
-  ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi, const ``__Policy``&);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, T3 phi, const ``__Policy``&);
   
 Returns the incomplete elliptic integral of the third kind ['[Pi](n, [phi], k)]:
 
@@ -271,10 +271,10 @@ would be complex).
 [optional_policy]
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_3(T1 k, T2 n);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n);
   
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_3(T1 k, T2 n, const ``__Policy``&);
+  BOOST_MATH_CUDA_ENABLED ``__sf_result`` ellint_3(T1 k, T2 n, const ``__Policy``&);
   
 Returns the complete elliptic integral of the first kind ['[Pi](n, k)]:
 
@@ -355,16 +355,16 @@ and
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_d(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k, T2 phi);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_d(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k, T2 phi, const ``__Policy``&);
 
   template <class T1>
-  ``__sf_result`` ellint_d(T1 k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k);
 
   template <class T1, class ``__Policy``>
-  ``__sf_result`` ellint_d(T1 k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k, const ``__Policy``&);
 
   }} // namespaces
   
@@ -378,10 +378,10 @@ when the arguments are of different types: when they are the same type then the
 is the same type as the arguments.
 
   template <class T1, class T2>
-  ``__sf_result`` ellint_d(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k, T2 phi);
   
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` ellint_3(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_3(T1 k, T2 phi, const ``__Policy``&);
   
 Returns the incomplete elliptic integral:
 
@@ -394,10 +394,10 @@ would be complex).
 [optional_policy]
 
   template <class T1>
-  ``__sf_result`` ellint_d(T1 k);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k);
   
   template <class T1, class ``__Policy``>
-  ``__sf_result`` ellint_d(T1 k, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` ellint_d(T1 k, const ``__Policy``&);
   
 Returns the complete elliptic integral ['D(k) = D([pi]/2, k)]
 
@@ -463,10 +463,10 @@ using the relation:
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` jacobi_zeta(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` jacobi_zeta(T1 k, T2 phi);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` jacobi_zeta(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` jacobi_zeta(T1 k, T2 phi, const ``__Policy``&);
 
   }} // namespaces
   
@@ -543,10 +543,10 @@ is [@../../example/jacobi_zeta_example.cpp jacobi_zeta_example.cpp].
   namespace boost { namespace math {
 
   template <class T1, class T2>
-  ``__sf_result`` heuman_lambda(T1 k, T2 phi);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` heuman_lambda(T1 k, T2 phi);
 
   template <class T1, class T2, class ``__Policy``>
-  ``__sf_result`` heuman_lambda(T1 k, T2 phi, const ``__Policy``&);
+  BOOST_MATH_GPU_ENABLED ``__sf_result`` heuman_lambda(T1 k, T2 phi, const ``__Policy``&);
 
   }} // namespaces
   
diff --git a/include/boost/math/special_functions/airy.hpp b/include/boost/math/special_functions/airy.hpp
index 06eee92383..65114089a6 100644
--- a/include/boost/math/special_functions/airy.hpp
+++ b/include/boost/math/special_functions/airy.hpp
@@ -1,4 +1,5 @@
 // Copyright John Maddock 2012.
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -7,19 +8,24 @@
 #ifndef BOOST_MATH_AIRY_HPP
 #define BOOST_MATH_AIRY_HPP
 
-#include <limits>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/precision.hpp>
+#include <boost/math/tools/cstdint.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/bessel.hpp>
 #include <boost/math/special_functions/cbrt.hpp>
 #include <boost/math/special_functions/detail/airy_ai_bi_zero.hpp>
 #include <boost/math/tools/roots.hpp>
+#include <boost/math/policies/error_handling.hpp>
+#include <boost/math/constants/constants.hpp>
 
 namespace boost{ namespace math{
 
 namespace detail{
 
 template <class T, class Policy>
-T airy_ai_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_ai_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -57,7 +63,7 @@ T airy_ai_imp(T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T airy_bi_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_bi_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -90,7 +96,7 @@ T airy_bi_imp(T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T airy_ai_prime_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_ai_prime_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -125,7 +131,7 @@ T airy_ai_prime_imp(T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T airy_bi_prime_imp(T x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_bi_prime_imp(T x, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
@@ -156,7 +162,7 @@ T airy_bi_prime_imp(T x, const Policy& pol)
 }
 
 template <class T, class Policy>
-T airy_ai_zero_imp(int m, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_ai_zero_imp(int m, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names, needed for log, sqrt.
 
@@ -209,7 +215,7 @@ T airy_ai_zero_imp(int m, const Policy& pol)
 }
 
 template <class T, class Policy>
-T airy_bi_zero_imp(int m, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T airy_bi_zero_imp(int m, const Policy& pol)
 {
    BOOST_MATH_STD_USING // ADL of std names, needed for log, sqrt.
 
@@ -263,7 +269,7 @@ T airy_bi_zero_imp(int m, const Policy& pol)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type airy_ai(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_ai(T x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
@@ -279,13 +285,13 @@ inline typename tools::promote_args<T>::type airy_ai(T x, const Policy&)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type airy_ai(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_ai(T x)
 {
    return airy_ai(x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type airy_bi(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_bi(T x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
@@ -301,13 +307,13 @@ inline typename tools::promote_args<T>::type airy_bi(T x, const Policy&)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type airy_bi(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_bi(T x)
 {
    return airy_bi(x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type airy_ai_prime(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_ai_prime(T x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
@@ -323,13 +329,13 @@ inline typename tools::promote_args<T>::type airy_ai_prime(T x, const Policy&)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type airy_ai_prime(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_ai_prime(T x)
 {
    return airy_ai_prime(x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type airy_bi_prime(T x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_bi_prime(T x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename tools::promote_args<T>::type result_type;
@@ -345,13 +351,13 @@ inline typename tools::promote_args<T>::type airy_bi_prime(T x, const Policy&)
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type airy_bi_prime(T x)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type airy_bi_prime(T x)
 {
    return airy_bi_prime(x, policies::policy<>());
 }
 
 template <class T, class Policy>
-inline T airy_ai_zero(int m, const Policy& /*pol*/)
+BOOST_MATH_GPU_ENABLED inline T airy_ai_zero(int m, const Policy& /*pol*/)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename policies::evaluation<T, Policy>::type value_type;
@@ -371,13 +377,13 @@ inline T airy_ai_zero(int m, const Policy& /*pol*/)
 }
 
 template <class T>
-inline T airy_ai_zero(int m)
+BOOST_MATH_GPU_ENABLED inline T airy_ai_zero(int m)
 {
    return airy_ai_zero<T>(m, policies::policy<>());
 }
 
 template <class T, class OutputIterator, class Policy>
-inline OutputIterator airy_ai_zero(
+BOOST_MATH_GPU_ENABLED inline OutputIterator airy_ai_zero(
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it,
@@ -399,7 +405,7 @@ inline OutputIterator airy_ai_zero(
 }
 
 template <class T, class OutputIterator>
-inline OutputIterator airy_ai_zero(
+BOOST_MATH_GPU_ENABLED inline OutputIterator airy_ai_zero(
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it)
@@ -408,7 +414,7 @@ inline OutputIterator airy_ai_zero(
 }
 
 template <class T, class Policy>
-inline T airy_bi_zero(int m, const Policy& /*pol*/)
+BOOST_MATH_GPU_ENABLED inline T airy_bi_zero(int m, const Policy& /*pol*/)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename policies::evaluation<T, Policy>::type value_type;
@@ -428,13 +434,13 @@ inline T airy_bi_zero(int m, const Policy& /*pol*/)
 }
 
 template <typename T>
-inline T airy_bi_zero(int m)
+BOOST_MATH_GPU_ENABLED inline T airy_bi_zero(int m)
 {
    return airy_bi_zero<T>(m, policies::policy<>());
 }
 
 template <class T, class OutputIterator, class Policy>
-inline OutputIterator airy_bi_zero(
+BOOST_MATH_GPU_ENABLED inline OutputIterator airy_bi_zero(
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it,
@@ -456,7 +462,7 @@ inline OutputIterator airy_bi_zero(
 }
 
 template <class T, class OutputIterator>
-inline OutputIterator airy_bi_zero(
+BOOST_MATH_GPU_ENABLED inline OutputIterator airy_bi_zero(
                          int start_index,
                          unsigned number_of_zeros,
                          OutputIterator out_it)
diff --git a/include/boost/math/special_functions/atanh.hpp b/include/boost/math/special_functions/atanh.hpp
index 543fb5fce3..9d73e568c0 100644
--- a/include/boost/math/special_functions/atanh.hpp
+++ b/include/boost/math/special_functions/atanh.hpp
@@ -15,7 +15,7 @@
 #pragma once
 #endif
 
-#include <cmath>
+#include <boost/math/tools/config.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
@@ -33,10 +33,10 @@ namespace boost
         // This is the main fare
 
         template<typename T, typename Policy>
-        inline T    atanh_imp(const T x, const Policy& pol)
+        BOOST_MATH_GPU_ENABLED inline T    atanh_imp(const T x, const Policy& pol)
         {
             BOOST_MATH_STD_USING
-            static const char* function = "boost::math::atanh<%1%>(%1%)";
+            constexpr auto function = "boost::math::atanh<%1%>(%1%)";
 
             if(x < -1)
             {
@@ -87,7 +87,7 @@ namespace boost
        }
 
         template<typename T, typename Policy>
-        inline typename tools::promote_args<T>::type atanh(T x, const Policy&)
+        BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type atanh(T x, const Policy&)
         {
             typedef typename tools::promote_args<T>::type result_type;
             typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -102,7 +102,7 @@ namespace boost
               "boost::math::atanh<%1%>(%1%)");
         }
         template<typename T>
-        inline typename tools::promote_args<T>::type atanh(T x)
+        BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type atanh(T x)
         {
            return boost::math::atanh(x, policies::policy<>());
         }
diff --git a/include/boost/math/special_functions/ellint_1.hpp b/include/boost/math/special_functions/ellint_1.hpp
index f7fbbce40c..96c7c9e9b9 100644
--- a/include/boost/math/special_functions/ellint_1.hpp
+++ b/include/boost/math/special_functions/ellint_1.hpp
@@ -20,6 +20,7 @@
 #endif
 
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/constants/constants.hpp>
@@ -33,28 +34,28 @@
 namespace boost { namespace math {
 
 template <class T1, class T2, class Policy>
-typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol);
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol);
 
 namespace detail{
 
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 0> const&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 0> const&);
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 1> const&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 1> const&);
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 2> const&);
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, T one_minus_k2);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, T one_minus_k2);
 
 // Elliptic integral (Legendre form) of the first kind
 template <typename T, typename Policy>
-T ellint_f_imp(T phi, T k, const Policy& pol, T one_minus_k2)
+BOOST_MATH_GPU_ENABLED T ellint_f_imp(T phi, T k, const Policy& pol, T one_minus_k2)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
     using namespace boost::math::constants;
 
-    static const char* function = "boost::math::ellint_f<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::ellint_f<%1%>(%1%,%1%)";
     BOOST_MATH_INSTRUMENT_VARIABLE(phi);
     BOOST_MATH_INSTRUMENT_VARIABLE(k);
     BOOST_MATH_INSTRUMENT_VARIABLE(function);
@@ -151,19 +152,19 @@ T ellint_f_imp(T phi, T k, const Policy& pol, T one_minus_k2)
 }
 
 template <typename T, typename Policy>
-inline T ellint_f_imp(T phi, T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T ellint_f_imp(T phi, T k, const Policy& pol)
 {
    return ellint_f_imp(phi, k, pol, T(1 - k * k));
 }
 
 // Complete elliptic integral (Legendre form) of the first kind
 template <typename T, typename Policy>
-T ellint_k_imp(T k, const Policy& pol, T one_minus_k2)
+BOOST_MATH_GPU_ENABLED T ellint_k_imp(T k, const Policy& pol, T one_minus_k2)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
 
-    static const char* function = "boost::math::ellint_k<%1%>(%1%)";
+    constexpr auto function = "boost::math::ellint_k<%1%>(%1%)";
 
     if (abs(k) > 1)
     {
@@ -181,7 +182,7 @@ T ellint_k_imp(T k, const Policy& pol, T one_minus_k2)
     return value;
 }
 template <typename T, typename Policy>
-inline T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&)
+BOOST_MATH_GPU_ENABLED inline T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 2> const&)
 {
    return ellint_k_imp(k, pol, T(1 - k * k));
 }
@@ -203,9 +204,9 @@ inline T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 2> con
 // archived in the code below), but was found to have slightly higher error rates.
 //
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 0> const&)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 0> const&)
 {
-   using std::abs;
+   BOOST_MATH_STD_USING
    using namespace boost::math::tools;
 
    T m = k * k;
@@ -456,7 +457,7 @@ BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_cons
       // This handles all cases where m > 0.9, 
       // including all error handling:
       //
-      return ellint_k_imp(k, pol, std::integral_constant<int, 2>());
+      return ellint_k_imp(k, pol, boost::math::integral_constant<int, 2>());
 #if 0
    else
    {
@@ -476,9 +477,9 @@ BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_cons
    }
 }
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_constant<int, 1> const&)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, boost::math::integral_constant<int, 1> const&)
 {
-   using std::abs;
+   BOOST_MATH_STD_USING
    using namespace boost::math::tools;
 
    T m = k * k;
@@ -757,44 +758,37 @@ BOOST_MATH_FORCEINLINE T ellint_k_imp(T k, const Policy& pol, std::integral_cons
       // All cases where m > 0.9
       // including all error handling:
       //
-      return ellint_k_imp(k, pol, std::integral_constant<int, 2>());
+      return ellint_k_imp(k, pol, boost::math::integral_constant<int, 2>());
    }
 }
 
 template <typename T, typename Policy>
-typename tools::promote_args<T>::type ellint_1(T k, const Policy& pol, const std::true_type&)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type ellint_1(T k, const Policy& pol, const boost::math::true_type&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
-   typedef std::integral_constant<int, 
+   typedef boost::math::integral_constant<int, 
 #if defined(__clang_major__) && (__clang_major__ == 7)
       2
 #else
-      std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 54) ? 0 :
-      std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 64) ? 1 : 2
+      boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 54) ? 0 :
+      boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 64) ? 1 : 2
 #endif
    > precision_tag_type;
    return policies::checked_narrowing_cast<result_type, Policy>(detail::ellint_k_imp(static_cast<value_type>(k), pol, precision_tag_type()), "boost::math::ellint_1<%1%>(%1%)");
 }
 
 template <class T1, class T2>
-typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const std::false_type&)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const boost::math::false_type&)
 {
    return boost::math::ellint_1(k, phi, policies::policy<>());
 }
 
-}
-
-// Complete elliptic integral (Legendre form) of the first kind
-template <typename T>
-typename tools::promote_args<T>::type ellint_1(T k)
-{
-   return ellint_1(k, policies::policy<>());
-}
+} // namespace detail
 
 // Elliptic integral (Legendre form) of the first kind
 template <class T1, class T2, class Policy>
-typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -802,12 +796,19 @@ typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi, const Policy&
 }
 
 template <class T1, class T2>
-typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_1(T1 k, T2 phi)
 {
    typedef typename policies::is_policy<T2>::type tag_type;
    return detail::ellint_1(k, phi, tag_type());
 }
 
+// Complete elliptic integral (Legendre form) of the first kind
+template <typename T>
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type ellint_1(T k)
+{
+   return ellint_1(k, policies::policy<>());
+}
+
 }} // namespaces
 
 #endif // BOOST_MATH_ELLINT_1_HPP
diff --git a/include/boost/math/special_functions/ellint_2.hpp b/include/boost/math/special_functions/ellint_2.hpp
index 5e2552ceca..0cc1fa0944 100644
--- a/include/boost/math/special_functions/ellint_2.hpp
+++ b/include/boost/math/special_functions/ellint_2.hpp
@@ -19,6 +19,9 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/special_functions/ellint_rd.hpp>
@@ -34,20 +37,20 @@
 namespace boost { namespace math {
 
 template <class T1, class T2, class Policy>
-typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol);
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol);
 
 namespace detail{
 
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 0>&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const boost::math::integral_constant<int, 0>&);
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 1>&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const boost::math::integral_constant<int, 1>&);
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const std::integral_constant<int, 2>&);
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, const boost::math::integral_constant<int, 2>&);
 
 // Elliptic integral (Legendre form) of the second kind
 template <typename T, typename Policy>
-T ellint_e_imp(T phi, T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_e_imp(T phi, T k, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
@@ -72,9 +75,9 @@ T ellint_e_imp(T phi, T k, const Policy& pol)
     }
     else if(phi > 1 / tools::epsilon<T>())
     {
-       typedef std::integral_constant<int,
-          std::is_floating_point<T>::value&& std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 54) ? 0 :
-          std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 64) ? 1 : 2
+       typedef boost::math::integral_constant<int,
+          boost::math::is_floating_point<T>::value&& boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 54) ? 0 :
+          boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 64) ? 1 : 2
        > precision_tag_type;
        // Phi is so large that phi%pi is necessarily zero (or garbage),
        // just return the second part of the duplication formula:
@@ -139,9 +142,9 @@ T ellint_e_imp(T phi, T k, const Policy& pol)
        }
        if (m != 0)
        {
-          typedef std::integral_constant<int,
-             std::is_floating_point<T>::value&& std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 54) ? 0 :
-             std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 64) ? 1 : 2
+          typedef boost::math::integral_constant<int,
+             boost::math::is_floating_point<T>::value&& boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 54) ? 0 :
+             boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 64) ? 1 : 2
           > precision_tag_type;
           result += m * ellint_e_imp(k, pol, precision_tag_type());
        }
@@ -151,7 +154,7 @@ T ellint_e_imp(T phi, T k, const Policy& pol)
 
 // Complete elliptic integral (Legendre form) of the second kind
 template <typename T, typename Policy>
-T ellint_e_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&)
+BOOST_MATH_GPU_ENABLED T ellint_e_imp(T k, const Policy& pol, boost::math::integral_constant<int, 2> const&)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
@@ -189,9 +192,9 @@ T ellint_e_imp(T k, const Policy& pol, std::integral_constant<int, 2> const&)
 // existing routines.
 //
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, std::integral_constant<int, 0> const&)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, boost::math::integral_constant<int, 0> const&)
 {
-   using std::abs;
+   BOOST_MATH_STD_USING
    using namespace boost::math::tools;
 
    T m = k * k;
@@ -424,13 +427,13 @@ BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, std::integral_cons
       // All cases where m > 0.9
       // including all error handling:
       //
-      return ellint_e_imp(k, pol, std::integral_constant<int, 2>());
+      return ellint_e_imp(k, pol, boost::math::integral_constant<int, 2>());
    }
 }
 template <typename T, typename Policy>
-BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, std::integral_constant<int, 1> const&)
+BOOST_MATH_GPU_ENABLED BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, boost::math::integral_constant<int, 1> const&)
 {
-   using std::abs;
+   BOOST_MATH_STD_USING
    using namespace boost::math::tools;
 
    T m = k * k;
@@ -697,54 +700,56 @@ BOOST_MATH_FORCEINLINE T ellint_e_imp(T k, const Policy& pol, std::integral_cons
       // All cases where m > 0.9
       // including all error handling:
       //
-      return ellint_e_imp(k, pol, std::integral_constant<int, 2>());
+      return ellint_e_imp(k, pol, boost::math::integral_constant<int, 2>());
    }
 }
 
 template <typename T, typename Policy>
-typename tools::promote_args<T>::type ellint_2(T k, const Policy& pol, const std::true_type&)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type ellint_2(T k, const Policy& pol, const boost::math::true_type&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
-   typedef std::integral_constant<int,
-      std::is_floating_point<T>::value&& std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 54) ? 0 :
-      std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 64) ? 1 : 2
+   typedef boost::math::integral_constant<int,
+      boost::math::is_floating_point<T>::value&& boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 54) ? 0 :
+      boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 64) ? 1 : 2
    > precision_tag_type;
    return policies::checked_narrowing_cast<result_type, Policy>(detail::ellint_e_imp(static_cast<value_type>(k), pol, precision_tag_type()), "boost::math::ellint_2<%1%>(%1%)");
 }
 
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const std::false_type&)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const boost::math::false_type&)
 {
    return boost::math::ellint_2(k, phi, policies::policy<>());
 }
 
 } // detail
 
-// Complete elliptic integral (Legendre form) of the second kind
-template <typename T>
-typename tools::promote_args<T>::type ellint_2(T k)
-{
-   return ellint_2(k, policies::policy<>());
-}
-
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi)
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi)
 {
    typedef typename policies::is_policy<T2>::type tag_type;
    return detail::ellint_2(k, phi, tag_type());
 }
 
 template <class T1, class T2, class Policy>
-typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_2(T1 k, T2 phi, const Policy& pol)  // LCOV_EXCL_LINE gcc misses this but sees the function body, strange!
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
    return policies::checked_narrowing_cast<result_type, Policy>(detail::ellint_e_imp(static_cast<value_type>(phi), static_cast<value_type>(k), pol), "boost::math::ellint_2<%1%>(%1%,%1%)");
 }
 
+
+// Complete elliptic integral (Legendre form) of the second kind
+template <typename T>
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T>::type ellint_2(T k)
+{
+   return ellint_2(k, policies::policy<>());
+}
+
+
 }} // namespaces
 
 #endif // BOOST_MATH_ELLINT_2_HPP
diff --git a/include/boost/math/special_functions/ellint_3.hpp b/include/boost/math/special_functions/ellint_3.hpp
index 33acc545dc..b8df7e2645 100644
--- a/include/boost/math/special_functions/ellint_3.hpp
+++ b/include/boost/math/special_functions/ellint_3.hpp
@@ -18,6 +18,8 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/special_functions/ellint_rj.hpp>
@@ -38,16 +40,16 @@ namespace boost { namespace math {
 namespace detail{
 
 template <typename T, typename Policy>
-T ellint_pi_imp(T v, T k, T vc, const Policy& pol);
+BOOST_MATH_CUDA_ENABLED T ellint_pi_imp(T v, T k, T vc, const Policy& pol);
 
 // Elliptic integral (Legendre form) of the third kind
 template <typename T, typename Policy>
-T ellint_pi_imp(T v, T phi, T k, T vc, const Policy& pol)
+BOOST_MATH_CUDA_ENABLED T ellint_pi_imp(T v, T phi, T k, T vc, const Policy& pol)
 {
    // Note vc = 1-v presumably without cancellation error.
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::ellint_3<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ellint_3<%1%>(%1%,%1%,%1%)";
 
 
    T sphi = sin(fabs(phi));
@@ -270,13 +272,13 @@ T ellint_pi_imp(T v, T phi, T k, T vc, const Policy& pol)
 
 // Complete elliptic integral (Legendre form) of the third kind
 template <typename T, typename Policy>
-T ellint_pi_imp(T v, T k, T vc, const Policy& pol)
+BOOST_MATH_CUDA_ENABLED T ellint_pi_imp(T v, T k, T vc, const Policy& pol)
 {
     // Note arg vc = 1-v, possibly without cancellation errors
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
 
-    static const char* function = "boost::math::ellint_pi<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::ellint_pi<%1%>(%1%,%1%)";
 
     if (abs(k) >= 1)
     {
@@ -318,13 +320,13 @@ T ellint_pi_imp(T v, T k, T vc, const Policy& pol)
 }
 
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi, const std::false_type&)
+BOOST_MATH_CUDA_ENABLED inline typename tools::promote_args<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi, const boost::math::false_type&)
 {
    return boost::math::ellint_3(k, v, phi, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type ellint_3(T1 k, T2 v, const Policy& pol, const std::true_type&)
+BOOST_MATH_CUDA_ENABLED inline typename tools::promote_args<T1, T2>::type ellint_3(T1 k, T2 v, const Policy& pol, const boost::math::true_type&)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -339,7 +341,7 @@ inline typename tools::promote_args<T1, T2>::type ellint_3(T1 k, T2 v, const Pol
 } // namespace detail
 
 template <class T1, class T2, class T3, class Policy>
-inline typename tools::promote_args<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi, const Policy&)
+BOOST_MATH_CUDA_ENABLED inline typename tools::promote_args<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi, const Policy&)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -354,14 +356,14 @@ inline typename tools::promote_args<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 ph
 }
 
 template <class T1, class T2, class T3>
-typename detail::ellint_3_result<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi)
+BOOST_MATH_CUDA_ENABLED typename detail::ellint_3_result<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi)
 {
    typedef typename policies::is_policy<T3>::type tag_type;
    return detail::ellint_3(k, v, phi, tag_type());
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type ellint_3(T1 k, T2 v)
+BOOST_MATH_CUDA_ENABLED inline typename tools::promote_args<T1, T2>::type ellint_3(T1 k, T2 v)
 {
    return ellint_3(k, v, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/ellint_d.hpp b/include/boost/math/special_functions/ellint_d.hpp
index da1e87ba3e..f5a8491f5a 100644
--- a/include/boost/math/special_functions/ellint_d.hpp
+++ b/include/boost/math/special_functions/ellint_d.hpp
@@ -1,5 +1,6 @@
 //  Copyright (c) 2006 Xiaogang Zhang
 //  Copyright (c) 2006 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -18,6 +19,8 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
 #include <boost/math/special_functions/ellint_rd.hpp>
@@ -33,16 +36,16 @@
 namespace boost { namespace math {
 
 template <class T1, class T2, class Policy>
-typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const Policy& pol);
+BOOST_MATH_GPU_ENABLED typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const Policy& pol);
 
 namespace detail{
 
 template <typename T, typename Policy>
-T ellint_d_imp(T k, const Policy& pol);
+BOOST_MATH_GPU_ENABLED T ellint_d_imp(T k, const Policy& pol);
 
 // Elliptic integral (Legendre form) of the second kind
 template <typename T, typename Policy>
-T ellint_d_imp(T phi, T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_d_imp(T phi, T k, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
@@ -113,7 +116,7 @@ T ellint_d_imp(T phi, T k, const Policy& pol)
 
 // Complete elliptic integral (Legendre form) of the second kind
 template <typename T, typename Policy>
-T ellint_d_imp(T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_d_imp(T k, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
@@ -135,7 +138,7 @@ T ellint_d_imp(T k, const Policy& pol)
 }
 
 template <typename T, typename Policy>
-inline typename tools::promote_args<T>::type ellint_d(T k, const Policy& pol, const std::true_type&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type ellint_d(T k, const Policy& pol, const boost::math::true_type&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -144,7 +147,7 @@ inline typename tools::promote_args<T>::type ellint_d(T k, const Policy& pol, co
 
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const boost::math::false_type&)
 {
    return boost::math::ellint_d(k, phi, policies::policy<>());
 }
@@ -153,21 +156,21 @@ inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const s
 
 // Complete elliptic integral (Legendre form) of the second kind
 template <typename T>
-inline typename tools::promote_args<T>::type ellint_d(T k)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type ellint_d(T k)
 {
    return ellint_d(k, policies::policy<>());
 }
 
 // Elliptic integral (Legendre form) of the second kind
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi)
 {
    typedef typename policies::is_policy<T2>::type tag_type;
    return detail::ellint_d(k, phi, tag_type());
 }
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type ellint_d(T1 k, T2 phi, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
diff --git a/include/boost/math/special_functions/ellint_rc.hpp b/include/boost/math/special_functions/ellint_rc.hpp
index 2f9a1f8cfb..ae3c6375e5 100644
--- a/include/boost/math/special_functions/ellint_rc.hpp
+++ b/include/boost/math/special_functions/ellint_rc.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2006 Xiaogang Zhang, 2015 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -18,12 +19,11 @@
 #pragma once
 #endif
 
-#include <boost/math/policies/error_handling.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/log1p.hpp>
 #include <boost/math/constants/constants.hpp>
-#include <iostream>
 
 // Carlson's degenerate elliptic integral
 // R_C(x, y) = R_F(x, y, y) = 0.5 * \int_{0}^{\infty} (t+x)^{-1/2} (t+y)^{-1} dt
@@ -32,11 +32,11 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T ellint_rc_imp(T x, T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_rc_imp(T x, T y, const Policy& pol)
 {
     BOOST_MATH_STD_USING
 
-    static const char* function = "boost::math::ellint_rc<%1%>(%1%,%1%)";
+    constexpr auto function = "boost::math::ellint_rc<%1%>(%1%,%1%)";
 
     if(x < 0)
     {
@@ -88,7 +88,7 @@ T ellint_rc_imp(T x, T y, const Policy& pol)
 } // namespace detail
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type 
    ellint_rc(T1 x, T2 y, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
@@ -100,7 +100,7 @@ inline typename tools::promote_args<T1, T2>::type
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type 
    ellint_rc(T1 x, T2 y)
 {
    return ellint_rc(x, y, policies::policy<>());
diff --git a/include/boost/math/special_functions/ellint_rd.hpp b/include/boost/math/special_functions/ellint_rd.hpp
index 2a79e54ca2..f2a33adc46 100644
--- a/include/boost/math/special_functions/ellint_rd.hpp
+++ b/include/boost/math/special_functions/ellint_rd.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2006 Xiaogang Zhang, 2015 John Maddock.
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -16,10 +17,10 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rc.hpp>
-#include <boost/math/special_functions/pow.hpp>
-#include <boost/math/tools/config.hpp>
 #include <boost/math/policies/error_handling.hpp>
 
 // Carlson's elliptic integral of the second kind
@@ -29,12 +30,11 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T ellint_rd_imp(T x, T y, T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_rd_imp(T x, T y, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   using std::swap;
 
-   static const char* function = "boost::math::ellint_rd<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ellint_rd<%1%>(%1%,%1%,%1%)";
 
    if(x < 0)
    {
@@ -55,9 +55,11 @@ T ellint_rd_imp(T x, T y, T z, const Policy& pol)
    //
    // Special cases from http://dlmf.nist.gov/19.20#iv
    //
-   using std::swap;
+
    if(x == z)
-      swap(x, y);
+   {
+      BOOST_MATH_GPU_SAFE_SWAP(x, y);
+   }
    if(y == z)
    {
       if(x == y)
@@ -70,19 +72,21 @@ T ellint_rd_imp(T x, T y, T z, const Policy& pol)
       }
       else
       {
-         if((std::max)(x, y) / (std::min)(x, y) > T(1.3))
+         if(BOOST_MATH_GPU_SAFE_MAX(x, y) / BOOST_MATH_GPU_SAFE_MIN(x, y) > T(1.3))
             return 3 * (ellint_rc_imp(x, y, pol) - sqrt(x) / y) / (2 * (y - x));
          // Otherwise fall through to avoid cancellation in the above (RC(x,y) -> 1/x^0.5 as x -> y)
       }
    }
    if(x == y)
    {
-      if((std::max)(x, z) / (std::min)(x, z) > T(1.3))
+      if(BOOST_MATH_GPU_SAFE_MAX(x, z) / BOOST_MATH_GPU_SAFE_MIN(x, z) > T(1.3))
          return 3 * (ellint_rc_imp(z, x, pol) - 1 / sqrt(z)) / (z - x);
       // Otherwise fall through to avoid cancellation in the above (RC(x,y) -> 1/x^0.5 as x -> y)
    }
    if(y == 0)
-      swap(x, y);
+   {
+      BOOST_MATH_GPU_SAFE_SWAP(x, y);
+   }
    if(x == 0)
    {
       //
@@ -102,7 +106,8 @@ T ellint_rd_imp(T x, T y, T z, const Policy& pol)
          xn = (xn + yn) / 2;
          yn = t;
          sum_pow *= 2;
-         sum += sum_pow * boost::math::pow<2>(xn - yn);
+         const auto temp = (xn - yn);
+         sum += sum_pow * temp * temp;
       }
       T RF = constants::pi<T>() / (xn + yn);
       //
@@ -128,7 +133,7 @@ T ellint_rd_imp(T x, T y, T z, const Policy& pol)
    T An = (x + y + 3 * z) / 5;
    T A0 = An;
    // This has an extra 1.2 fudge factor which is really only needed when x, y and z are close in magnitude:
-   T Q = pow(tools::epsilon<T>() / 4, -T(1) / 8) * (std::max)((std::max)(An - x, An - y), An - z) * 1.2f;
+   T Q = pow(tools::epsilon<T>() / 4, -T(1) / 8) * BOOST_MATH_GPU_SAFE_MAX(BOOST_MATH_GPU_SAFE_MAX(An - x, An - y), An - z) * 1.2f;
    BOOST_MATH_INSTRUMENT_VARIABLE(Q);
    T lambda, rx, ry, rz;
    unsigned k = 0;
@@ -177,7 +182,7 @@ T ellint_rd_imp(T x, T y, T z, const Policy& pol)
 } // namespace detail
 
 template <class T1, class T2, class T3, class Policy>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rd(T1 x, T2 y, T3 z, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
@@ -190,7 +195,7 @@ inline typename tools::promote_args<T1, T2, T3>::type
 }
 
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rd(T1 x, T2 y, T3 z)
 {
    return ellint_rd(x, y, z, policies::policy<>());
diff --git a/include/boost/math/special_functions/ellint_rf.hpp b/include/boost/math/special_functions/ellint_rf.hpp
index c781ac0353..eb1c2b6e71 100644
--- a/include/boost/math/special_functions/ellint_rf.hpp
+++ b/include/boost/math/special_functions/ellint_rf.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2006 Xiaogang Zhang, 2015 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -17,8 +18,9 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/ellint_rc.hpp>
@@ -30,21 +32,20 @@
 namespace boost { namespace math { namespace detail{
 
    template <typename T, typename Policy>
-   T ellint_rf_imp(T x, T y, T z, const Policy& pol)
+   BOOST_MATH_GPU_ENABLED T ellint_rf_imp(T x, T y, T z, const Policy& pol)
    {
       BOOST_MATH_STD_USING
       using namespace boost::math;
-      using std::swap;
 
-      static const char* function = "boost::math::ellint_rf<%1%>(%1%,%1%,%1%)";
+      constexpr auto function = "boost::math::ellint_rf<%1%>(%1%,%1%,%1%)";
 
       if(x < 0 || y < 0 || z < 0)
       {
-         return policies::raise_domain_error<T>(function, "domain error, all arguments must be non-negative, only sensible result is %1%.", std::numeric_limits<T>::quiet_NaN(), pol);
+         return policies::raise_domain_error<T>(function, "domain error, all arguments must be non-negative, only sensible result is %1%.", boost::math::numeric_limits<T>::quiet_NaN(), pol);
       }
       if(x + y == 0 || y + z == 0 || z + x == 0)
       {
-         return policies::raise_domain_error<T>(function, "domain error, at most one argument can be zero, only sensible result is %1%.", std::numeric_limits<T>::quiet_NaN(), pol);
+         return policies::raise_domain_error<T>(function, "domain error, at most one argument can be zero, only sensible result is %1%.", boost::math::numeric_limits<T>::quiet_NaN(), pol);
       }
       //
       // Special cases from http://dlmf.nist.gov/19.20#i
@@ -80,9 +81,9 @@ namespace boost { namespace math { namespace detail{
             return ellint_rc_imp(x, y, pol);
       }
       if(x == 0)
-         swap(x, z);
+         BOOST_MATH_GPU_SAFE_SWAP(x, z);
       else if(y == 0)
-         swap(y, z);
+         BOOST_MATH_GPU_SAFE_SWAP(y, z);
       if(z == 0)
       {
          //
@@ -105,7 +106,7 @@ namespace boost { namespace math { namespace detail{
       T zn = z;
       T An = (x + y + z) / 3;
       T A0 = An;
-      T Q = pow(3 * boost::math::tools::epsilon<T>(), T(-1) / 8) * (std::max)((std::max)(fabs(An - xn), fabs(An - yn)), fabs(An - zn));
+      T Q = pow(3 * boost::math::tools::epsilon<T>(), T(-1) / 8) * BOOST_MATH_GPU_SAFE_MAX(BOOST_MATH_GPU_SAFE_MAX(fabs(An - xn), fabs(An - yn)), fabs(An - zn));
       T fn = 1;
 
 
@@ -143,7 +144,7 @@ namespace boost { namespace math { namespace detail{
 } // namespace detail
 
 template <class T1, class T2, class T3, class Policy>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rf(T1 x, T2 y, T3 z, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
@@ -156,7 +157,7 @@ inline typename tools::promote_args<T1, T2, T3>::type
 }
 
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rf(T1 x, T2 y, T3 z)
 {
    return ellint_rf(x, y, z, policies::policy<>());
diff --git a/include/boost/math/special_functions/ellint_rg.hpp b/include/boost/math/special_functions/ellint_rg.hpp
index 051c104bca..8a7f706ac0 100644
--- a/include/boost/math/special_functions/ellint_rg.hpp
+++ b/include/boost/math/special_functions/ellint_rg.hpp
@@ -10,8 +10,8 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/ellint_rd.hpp>
@@ -21,27 +21,26 @@
 namespace boost { namespace math { namespace detail{
 
    template <typename T, typename Policy>
-   T ellint_rg_imp(T x, T y, T z, const Policy& pol)
+   BOOST_MATH_GPU_ENABLED T ellint_rg_imp(T x, T y, T z, const Policy& pol)
    {
       BOOST_MATH_STD_USING
-      static const char* function = "boost::math::ellint_rf<%1%>(%1%,%1%,%1%)";
+      constexpr auto function = "boost::math::ellint_rf<%1%>(%1%,%1%,%1%)";
 
       if(x < 0 || y < 0 || z < 0)
       {
-         return policies::raise_domain_error<T>(function, "domain error, all arguments must be non-negative, only sensible result is %1%.", std::numeric_limits<T>::quiet_NaN(), pol);
+         return policies::raise_domain_error<T>(function, "domain error, all arguments must be non-negative, only sensible result is %1%.", boost::math::numeric_limits<T>::quiet_NaN(), pol);
       }
       //
       // Function is symmetric in x, y and z, but we require
       // (x - z)(y - z) >= 0 to avoid cancellation error in the result
       // which implies (for example) x >= z >= y
       //
-      using std::swap;
       if(x < y)
-         swap(x, y);
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
       if(x < z)
-         swap(x, z);
+         BOOST_MATH_GPU_SAFE_SWAP(x, z);
       if(y > z)
-         swap(y, z);
+         BOOST_MATH_GPU_SAFE_SWAP(y, z);
       
       BOOST_MATH_ASSERT(x >= z);
       BOOST_MATH_ASSERT(z >= y);
@@ -64,7 +63,7 @@ namespace boost { namespace math { namespace detail{
          else
          {
             // x = z, y != 0
-            swap(x, y);
+            BOOST_MATH_GPU_SAFE_SWAP(x, y);
             return (x == 0) ? T(sqrt(z) / 2) : T((z * ellint_rc_imp(x, z, pol) + sqrt(x)) / 2);
          }
       }
@@ -75,7 +74,7 @@ namespace boost { namespace math { namespace detail{
       }
       else if(y == 0)
       {
-         swap(y, z);
+         BOOST_MATH_GPU_SAFE_SWAP(y, z);
          //
          // Special handling for common case, from
          // Numerical Computation of Real or Complex Elliptic Integrals, eq.46
@@ -106,7 +105,7 @@ namespace boost { namespace math { namespace detail{
 } // namespace detail
 
 template <class T1, class T2, class T3, class Policy>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rg(T1 x, T2 y, T3 z, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2, T3>::type result_type;
@@ -119,7 +118,7 @@ inline typename tools::promote_args<T1, T2, T3>::type
 }
 
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    ellint_rg(T1 x, T2 y, T3 z)
 {
    return ellint_rg(x, y, z, policies::policy<>());
diff --git a/include/boost/math/special_functions/ellint_rj.hpp b/include/boost/math/special_functions/ellint_rj.hpp
index f19eac2843..76e1a14eb4 100644
--- a/include/boost/math/special_functions/ellint_rj.hpp
+++ b/include/boost/math/special_functions/ellint_rj.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2006 Xiaogang Zhang, 2015 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -18,8 +19,9 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/policies/error_handling.hpp>
 #include <boost/math/special_functions/ellint_rc.hpp>
 #include <boost/math/special_functions/ellint_rf.hpp>
@@ -32,7 +34,7 @@
 namespace boost { namespace math { namespace detail{
 
 template <typename T, typename Policy>
-T ellint_rc1p_imp(T y, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_rc1p_imp(T y, const Policy& pol)
 {
    using namespace boost::math;
    // Calculate RC(1, 1 + x)
@@ -70,11 +72,11 @@ T ellint_rc1p_imp(T y, const Policy& pol)
 }
 
 template <typename T, typename Policy>
-T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T ellint_rj_imp_final(T x, T y, T z, T p, const Policy& pol)
 {
    BOOST_MATH_STD_USING
 
-   static const char* function = "boost::math::ellint_rj<%1%>(%1%,%1%,%1%)";
+   constexpr auto function = "boost::math::ellint_rj<%1%>(%1%,%1%,%1%)";
 
    if(x < 0)
    {
@@ -94,37 +96,7 @@ T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
    }
    if(x + y == 0 || y + z == 0 || z + x == 0)
    {
-      return policies::raise_domain_error<T>(function, "At most one argument can be zero, only possible result is %1%.", std::numeric_limits<T>::quiet_NaN(), pol);
-   }
-
-   // for p < 0, the integral is singular, return Cauchy principal value
-   if(p < 0)
-   {
-      //
-      // We must ensure that x < y < z.
-      // Since the integral is symmetrical in x, y and z
-      // we can just permute the values:
-      //
-      if(x > y)
-         std::swap(x, y);
-      if(y > z)
-         std::swap(y, z);
-      if(x > y)
-         std::swap(x, y);
-
-      BOOST_MATH_ASSERT(x <= y);
-      BOOST_MATH_ASSERT(y <= z);
-
-      T q = -p;
-      p = (z * (x + y + q) - x * y) / (z + q);
-
-      BOOST_MATH_ASSERT(p >= 0);
-
-      T value = (p - z) * ellint_rj_imp(x, y, z, p, pol);
-      value -= 3 * ellint_rf_imp(x, y, z, pol);
-      value += 3 * sqrt((x * y * z) / (x * y + p * q)) * ellint_rc_imp(T(x * y + p * q), T(p * q), pol);
-      value /= (z + q);
-      return value;
+      return policies::raise_domain_error<T>(function, "At most one argument can be zero, only possible result is %1%.", boost::math::numeric_limits<T>::quiet_NaN(), pol);
    }
 
    //
@@ -148,13 +120,12 @@ T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
       else
       {
          // x = y only, permute so y = z:
-         using std::swap;
-         swap(x, z);
+         BOOST_MATH_GPU_SAFE_SWAP(x, z);
          if(y == p)
          {
             return ellint_rd_imp(x, y, y, pol);
          }
-         else if((std::max)(y, p) / (std::min)(y, p) > T(1.2))
+         else if(BOOST_MATH_GPU_SAFE_MAX(y, p) / BOOST_MATH_GPU_SAFE_MIN(y, p) > T(1.2))
          {
             return 3 * (ellint_rc_imp(x, y, pol) - ellint_rc_imp(x, p, pol)) / (p - y);
          }
@@ -168,7 +139,7 @@ T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
          // y = z = p:
          return ellint_rd_imp(x, y, y, pol);
       }
-      else if((std::max)(y, p) / (std::min)(y, p) > T(1.2))
+      else if(BOOST_MATH_GPU_SAFE_MAX(y, p) / BOOST_MATH_GPU_SAFE_MIN(y, p) > T(1.2))
       {
          // y = z:
          return 3 * (ellint_rc_imp(x, y, pol) - ellint_rc_imp(x, p, pol)) / (p - y);
@@ -187,7 +158,7 @@ T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
    T An = (x + y + z + 2 * p) / 5;
    T A0 = An;
    T delta = (p - x) * (p - y) * (p - z);
-   T Q = pow(tools::epsilon<T>() / 5, -T(1) / 8) * (std::max)((std::max)(fabs(An - x), fabs(An - y)), (std::max)(fabs(An - z), fabs(An - p)));
+   T Q = pow(tools::epsilon<T>() / 5, -T(1) / 8) * BOOST_MATH_GPU_SAFE_MAX(BOOST_MATH_GPU_SAFE_MAX(fabs(An - x), fabs(An - y)), BOOST_MATH_GPU_SAFE_MAX(fabs(An - z), fabs(An - p)));
 
    unsigned n;
    T lambda;
@@ -260,10 +231,71 @@ T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
    return result;
 }
 
+template <typename T, typename Policy>
+BOOST_MATH_GPU_ENABLED T ellint_rj_imp(T x, T y, T z, T p, const Policy& pol)
+{
+   BOOST_MATH_STD_USING
+   
+   constexpr auto function = "boost::math::ellint_rj<%1%>(%1%,%1%,%1%)";
+
+   if(x < 0)
+   {
+      return policies::raise_domain_error<T>(function, "Argument x must be non-negative, but got x = %1%", x, pol);
+   }
+   if(y < 0)
+   {
+      return policies::raise_domain_error<T>(function, "Argument y must be non-negative, but got y = %1%", y, pol);
+   }
+   if(z < 0)
+   {
+      return policies::raise_domain_error<T>(function, "Argument z must be non-negative, but got z = %1%", z, pol);
+   }
+   if(p == 0)
+   {
+      return policies::raise_domain_error<T>(function, "Argument p must not be zero, but got p = %1%", p, pol);
+   }
+   if(x + y == 0 || y + z == 0 || z + x == 0)
+   {
+      return policies::raise_domain_error<T>(function, "At most one argument can be zero, only possible result is %1%.", boost::math::numeric_limits<T>::quiet_NaN(), pol);
+   }
+
+   // for p < 0, the integral is singular, return Cauchy principal value
+   if(p < 0)
+   {
+      //
+      // We must ensure that x < y < z.
+      // Since the integral is symmetrical in x, y and z
+      // we can just permute the values:
+      //
+      if(x > y)
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
+      if(y > z)
+         BOOST_MATH_GPU_SAFE_SWAP(y, z);
+      if(x > y)
+         BOOST_MATH_GPU_SAFE_SWAP(x, y);
+
+      BOOST_MATH_ASSERT(x <= y);
+      BOOST_MATH_ASSERT(y <= z);
+
+      T q = -p;
+      p = (z * (x + y + q) - x * y) / (z + q);
+
+      BOOST_MATH_ASSERT(p >= 0);
+
+      T value = (p - z) * ellint_rj_imp_final(x, y, z, p, pol);
+      value -= 3 * ellint_rf_imp(x, y, z, pol);
+      value += 3 * sqrt((x * y * z) / (x * y + p * q)) * ellint_rc_imp(T(x * y + p * q), T(p * q), pol);
+      value /= (z + q);
+      return value;
+   }
+
+   return ellint_rj_imp_final(x, y, z, p, pol);
+}
+
 } // namespace detail
 
 template <class T1, class T2, class T3, class T4, class Policy>
-inline typename tools::promote_args<T1, T2, T3, T4>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type 
    ellint_rj(T1 x, T2 y, T3 z, T4 p, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2, T3, T4>::type result_type;
@@ -278,7 +310,7 @@ inline typename tools::promote_args<T1, T2, T3, T4>::type
 }
 
 template <class T1, class T2, class T3, class T4>
-inline typename tools::promote_args<T1, T2, T3, T4>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3, T4>::type 
    ellint_rj(T1 x, T2 y, T3 z, T4 p)
 {
    return ellint_rj(x, y, z, p, policies::policy<>());
diff --git a/include/boost/math/special_functions/heuman_lambda.hpp b/include/boost/math/special_functions/heuman_lambda.hpp
index 0fbf4a9803..05002725f2 100644
--- a/include/boost/math/special_functions/heuman_lambda.hpp
+++ b/include/boost/math/special_functions/heuman_lambda.hpp
@@ -1,4 +1,5 @@
 //  Copyright (c) 2015 John Maddock
+//  Copyright (c) 2024 Matt Borland
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -10,6 +11,9 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+#include <boost/math/tools/type_traits.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_rj.hpp>
 #include <boost/math/special_functions/ellint_1.hpp>
@@ -26,13 +30,13 @@ namespace detail{
 
 // Elliptic integral - Jacobi Zeta
 template <typename T, typename Policy>
-T heuman_lambda_imp(T phi, T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T heuman_lambda_imp(T phi, T k, const Policy& pol)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
     using namespace boost::math::constants;
 
-    const char* function = "boost::math::heuman_lambda<%1%>(%1%, %1%)";
+    constexpr auto function = "boost::math::heuman_lambda<%1%>(%1%, %1%)";
 
     if(fabs(k) > 1)
        return policies::raise_domain_error<T>(function, "We require |k| <= 1 but got k = %1%", k, pol);
@@ -51,10 +55,10 @@ T heuman_lambda_imp(T phi, T k, const Policy& pol)
     }
     else
     {
-          typedef std::integral_constant<int,
-             std::is_floating_point<T>::value&& std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 54) ? 0 :
-             std::is_floating_point<T>::value && std::numeric_limits<T>::digits && (std::numeric_limits<T>::digits <= 64) ? 1 : 2
-          > precision_tag_type;
+       typedef boost::math::integral_constant<int,
+          boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 54) ? 0 :
+          boost::math::is_floating_point<T>::value && boost::math::numeric_limits<T>::digits && (boost::math::numeric_limits<T>::digits <= 64) ? 1 : 2
+       > precision_tag_type;
 
        T rkp = sqrt(kp);
        T ratio;
@@ -63,7 +67,9 @@ T heuman_lambda_imp(T phi, T k, const Policy& pol)
           return policies::raise_domain_error<T>(function, "When 1-k^2 == 1 then phi must be < Pi/2, but got phi = %1%", phi, pol);
        }
        else
+       {
           ratio = ellint_f_imp(phi, rkp, pol, k2) / ellint_k_imp(rkp, pol, k2);
+       }
        result = ratio + ellint_k_imp(k, pol, precision_tag_type()) * jacobi_zeta_imp(phi, rkp, pol, k2) / constants::half_pi<T>();
     }
     return result;
@@ -72,7 +78,7 @@ T heuman_lambda_imp(T phi, T k, const Policy& pol)
 } // detail
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type heuman_lambda(T1 k, T2 phi, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type heuman_lambda(T1 k, T2 phi, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -80,7 +86,7 @@ inline typename tools::promote_args<T1, T2>::type heuman_lambda(T1 k, T2 phi, co
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type heuman_lambda(T1 k, T2 phi)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type heuman_lambda(T1 k, T2 phi)
 {
    return boost::math::heuman_lambda(k, phi, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/jacobi_zeta.hpp b/include/boost/math/special_functions/jacobi_zeta.hpp
index c4ba7d23d2..8b6f80912d 100644
--- a/include/boost/math/special_functions/jacobi_zeta.hpp
+++ b/include/boost/math/special_functions/jacobi_zeta.hpp
@@ -11,6 +11,8 @@
 #pragma once
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/promotion.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/ellint_1.hpp>
 #include <boost/math/special_functions/ellint_rj.hpp>
@@ -27,7 +29,7 @@ namespace detail{
 
 // Elliptic integral - Jacobi Zeta
 template <typename T, typename Policy>
-T jacobi_zeta_imp(T phi, T k, const Policy& pol, T kp)
+BOOST_MATH_GPU_ENABLED T jacobi_zeta_imp(T phi, T k, const Policy& pol, T kp)
 {
     BOOST_MATH_STD_USING
     using namespace boost::math::tools;
@@ -55,14 +57,14 @@ T jacobi_zeta_imp(T phi, T k, const Policy& pol, T kp)
     return invert ? T(-result) : result;
 }
 template <typename T, typename Policy>
-inline T jacobi_zeta_imp(T phi, T k, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T jacobi_zeta_imp(T phi, T k, const Policy& pol)
 {
    return jacobi_zeta_imp(phi, k, pol, T(1 - k * k));
 }
 } // detail
 
 template <class T1, class T2, class Policy>
-inline typename tools::promote_args<T1, T2>::type jacobi_zeta(T1 k, T2 phi, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type jacobi_zeta(T1 k, T2 phi, const Policy& pol)
 {
    typedef typename tools::promote_args<T1, T2>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -70,7 +72,7 @@ inline typename tools::promote_args<T1, T2>::type jacobi_zeta(T1 k, T2 phi, cons
 }
 
 template <class T1, class T2>
-inline typename tools::promote_args<T1, T2>::type jacobi_zeta(T1 k, T2 phi)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2>::type jacobi_zeta(T1 k, T2 phi)
 {
    return boost::math::jacobi_zeta(k, phi, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 22c3889499..35f8dd1bb9 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -26,6 +26,8 @@
 
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/promotion.hpp> // for argument promotion.
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/policies/policy.hpp>
 
 #ifdef BOOST_MATH_HAS_NVRTC
 
@@ -36,6 +38,20 @@ template <class RT1, class RT2, class A>
 BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<RT1, RT2, A>::type
 beta(RT1 a, RT2 b, A arg);
 
+namespace detail{
+
+   template <class T, class U, class V>
+   struct ellint_3_result
+   {
+      using type = typename boost::math::conditional<
+         policies::is_policy<V>::value,
+         tools::promote_args_t<T, U>,
+         tools::promote_args_t<T, U, V>
+      >::type;
+   };
+
+   } // namespace detail
+
 } // namespace math
 } // namespace boost
 
@@ -329,90 +345,90 @@ namespace boost
 
    // Elliptic integrals:
    template <class T1, class T2, class T3>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
          ellint_rf(T1 x, T2 y, T3 z);
 
    template <class T1, class T2, class T3, class Policy>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
          ellint_rf(T1 x, T2 y, T3 z, const Policy& pol);
 
    template <class T1, class T2, class T3>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
          ellint_rd(T1 x, T2 y, T3 z);
 
    template <class T1, class T2, class T3, class Policy>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
          ellint_rd(T1 x, T2 y, T3 z, const Policy& pol);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          ellint_rc(T1 x, T2 y);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2>
          ellint_rc(T1 x, T2 y, const Policy& pol);
 
    template <class T1, class T2, class T3, class T4>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ellint_rj(T1 x, T2 y, T3 z, T4 p);
 
    template <class T1, class T2, class T3, class T4, class Policy>
-   tools::promote_args_t<T1, T2, T3, T4>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3, T4>
          ellint_rj(T1 x, T2 y, T3 z, T4 p, const Policy& pol);
 
    template <class T1, class T2, class T3>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
       ellint_rg(T1 x, T2 y, T3 z);
 
    template <class T1, class T2, class T3, class Policy>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
       ellint_rg(T1 x, T2 y, T3 z, const Policy& pol);
 
    template <typename T>
-   tools::promote_args_t<T> ellint_2(T k);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> ellint_2(T k);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi, const Policy& pol);
 
    template <typename T>
-   tools::promote_args_t<T> ellint_1(T k);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> ellint_1(T k);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi, const Policy& pol);
 
    template <typename T>
-   tools::promote_args_t<T> ellint_d(T k);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> ellint_d(T k);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi, const Policy& pol);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi, const Policy& pol);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi);
 
    template <class T1, class T2, class Policy>
-   tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi, const Policy& pol);
 
    namespace detail{
 
    template <class T, class U, class V>
    struct ellint_3_result
    {
-      using type = typename std::conditional<
+      using type = typename boost::math::conditional<
          policies::is_policy<V>::value,
          tools::promote_args_t<T, U>,
          tools::promote_args_t<T, U, V>
@@ -423,13 +439,13 @@ namespace boost
 
 
    template <class T1, class T2, class T3>
-   typename detail::ellint_3_result<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi);
+   BOOST_MATH_GPU_ENABLED typename detail::ellint_3_result<T1, T2, T3>::type ellint_3(T1 k, T2 v, T3 phi);
 
    template <class T1, class T2, class T3, class Policy>
-   tools::promote_args_t<T1, T2, T3> ellint_3(T1 k, T2 v, T3 phi, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3> ellint_3(T1 k, T2 v, T3 phi, const Policy& pol);
 
    template <class T1, class T2>
-   tools::promote_args_t<T1, T2> ellint_3(T1 k, T2 v);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2> ellint_3(T1 k, T2 v);
 
    // Factorial functions.
    // Note: not for integral types, at present.
@@ -648,10 +664,10 @@ namespace boost
    tools::promote_args_t<T> acosh(T x, const Policy&);
 
    template<typename T>
-   tools::promote_args_t<T> atanh(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> atanh(T x);
 
    template<typename T, class Policy>
-   tools::promote_args_t<T> atanh(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> atanh(T x, const Policy&);
 
    namespace detail{
 
@@ -816,58 +832,58 @@ namespace boost
    std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_2(T1 v, T2 x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> airy_ai(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_ai(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> airy_ai(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_ai(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> airy_bi(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_bi(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> airy_bi(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_bi(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> airy_ai_prime(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_ai_prime(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> airy_ai_prime(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_ai_prime(T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T> airy_bi_prime(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_bi_prime(T x, const Policy&);
 
    template <class T>
-   tools::promote_args_t<T> airy_bi_prime(T x);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_bi_prime(T x);
 
    template <class T>
-   T airy_ai_zero(int m);
+   BOOST_MATH_GPU_ENABLED T airy_ai_zero(int m);
    template <class T, class Policy>
-   T airy_ai_zero(int m, const Policy&);
+   BOOST_MATH_GPU_ENABLED T airy_ai_zero(int m, const Policy&);
 
    template <class OutputIterator>
-   OutputIterator airy_ai_zero(
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_ai_zero(
                      int start_index,
                      unsigned number_of_zeros,
                      OutputIterator out_it);
    template <class OutputIterator, class Policy>
-   OutputIterator airy_ai_zero(
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_ai_zero(
                      int start_index,
                      unsigned number_of_zeros,
                      OutputIterator out_it,
                      const Policy&);
 
    template <class T>
-   T airy_bi_zero(int m);
+   BOOST_MATH_GPU_ENABLED T airy_bi_zero(int m);
    template <class T, class Policy>
-   T airy_bi_zero(int m, const Policy&);
+   BOOST_MATH_GPU_ENABLED T airy_bi_zero(int m, const Policy&);
 
    template <class OutputIterator>
-   OutputIterator airy_bi_zero(
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_bi_zero(
                      int start_index,
                      unsigned number_of_zeros,
                      OutputIterator out_it);
    template <class OutputIterator, class Policy>
-   OutputIterator airy_bi_zero(
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_bi_zero(
                      int start_index,
                      unsigned number_of_zeros,
                      OutputIterator out_it,
@@ -1365,54 +1381,54 @@ namespace boost
       spherical_harmonic_i(unsigned n, int m, T1 theta, T2 phi, const Policy& pol);\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> \
    ellint_rf(T1 x, T2 y, T3 z){ return ::boost::math::ellint_rf(x, y, z, Policy()); }\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> \
    ellint_rd(T1 x, T2 y, T3 z){ return ::boost::math::ellint_rd(x, y, z, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> \
    ellint_rc(T1 x, T2 y){ return ::boost::math::ellint_rc(x, y, Policy()); }\
 \
    template <class T1, class T2, class T3, class T4>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3, T4> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3, T4> \
    ellint_rj(T1 x, T2 y, T3 z, T4 p){ return boost::math::ellint_rj(x, y, z, p, Policy()); }\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> \
    ellint_rg(T1 x, T2 y, T3 z){ return ::boost::math::ellint_rg(x, y, z, Policy()); }\
    \
    template <typename T>\
-   inline boost::math::tools::promote_args_t<T> ellint_2(T k){ return boost::math::ellint_2(k, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> ellint_2(T k){ return boost::math::ellint_2(k, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi){ return boost::math::ellint_2(k, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> ellint_2(T1 k, T2 phi){ return boost::math::ellint_2(k, phi, Policy()); }\
 \
    template <typename T>\
-   inline boost::math::tools::promote_args_t<T> ellint_d(T k){ return boost::math::ellint_d(k, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> ellint_d(T k){ return boost::math::ellint_d(k, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi){ return boost::math::ellint_d(k, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> ellint_d(T1 k, T2 phi){ return boost::math::ellint_d(k, phi, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi){ return boost::math::jacobi_zeta(k, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> jacobi_zeta(T1 k, T2 phi){ return boost::math::jacobi_zeta(k, phi, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi){ return boost::math::heuman_lambda(k, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> heuman_lambda(T1 k, T2 phi){ return boost::math::heuman_lambda(k, phi, Policy()); }\
 \
    template <typename T>\
-   inline boost::math::tools::promote_args_t<T> ellint_1(T k){ return boost::math::ellint_1(k, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> ellint_1(T k){ return boost::math::ellint_1(k, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi){ return boost::math::ellint_1(k, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> ellint_1(T1 k, T2 phi){ return boost::math::ellint_1(k, phi, Policy()); }\
 \
    template <class T1, class T2, class T3>\
-   inline boost::math::tools::promote_args_t<T1, T2, T3> ellint_3(T1 k, T2 v, T3 phi){ return boost::math::ellint_3(k, v, phi, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2, T3> ellint_3(T1 k, T2 v, T3 phi){ return boost::math::ellint_3(k, v, phi, Policy()); }\
 \
    template <class T1, class T2>\
-   inline boost::math::tools::promote_args_t<T1, T2> ellint_3(T1 k, T2 v){ return boost::math::ellint_3(k, v, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T1, T2> ellint_3(T1 k, T2 v){ return boost::math::ellint_3(k, v, Policy()); }\
 \
    using boost::math::max_factorial;\
    template <class RT>\
@@ -1515,7 +1531,7 @@ namespace boost
    inline boost::math::tools::promote_args_t<T> acosh(const T x){ return boost::math::acosh(x, Policy()); }\
 \
    template<typename T>\
-   inline boost::math::tools::promote_args_t<T> atanh(const T x){ return boost::math::atanh(x, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> atanh(const T x){ return boost::math::atanh(x, Policy()); }\
 \
    template <class T1, class T2>\
    inline typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type cyl_bessel_j(T1 v, T2 x)\
@@ -1769,33 +1785,33 @@ template <class OutputIterator, class T>\
    { return boost::math::jacobi_theta4m1tau(z, q, Policy()); }\
    \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> airy_ai(T x)\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> airy_ai(T x)\
    {  return boost::math::airy_ai(x, Policy());  }\
    \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> airy_bi(T x)\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> airy_bi(T x)\
    {  return boost::math::airy_bi(x, Policy());  }\
    \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> airy_ai_prime(T x)\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> airy_ai_prime(T x)\
    {  return boost::math::airy_ai_prime(x, Policy());  }\
    \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> airy_bi_prime(T x)\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> airy_bi_prime(T x)\
    {  return boost::math::airy_bi_prime(x, Policy());  }\
    \
    template <class T>\
-   inline T airy_ai_zero(int m)\
+   BOOST_MATH_GPU_ENABLED inline T airy_ai_zero(int m)\
    { return boost::math::airy_ai_zero<T>(m, Policy()); }\
    template <class T, class OutputIterator>\
-   OutputIterator airy_ai_zero(int start_index, unsigned number_of_zeros, OutputIterator out_it)\
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_ai_zero(int start_index, unsigned number_of_zeros, OutputIterator out_it)\
    { return boost::math::airy_ai_zero<T>(start_index, number_of_zeros, out_it, Policy()); }\
    \
    template <class T>\
-   inline T airy_bi_zero(int m)\
+   BOOST_MATH_GPU_ENABLED inline T airy_bi_zero(int m)\
    { return boost::math::airy_bi_zero<T>(m, Policy()); }\
    template <class T, class OutputIterator>\
-   OutputIterator airy_bi_zero(int start_index, unsigned number_of_zeros, OutputIterator out_it)\
+   BOOST_MATH_GPU_ENABLED OutputIterator airy_bi_zero(int start_index, unsigned number_of_zeros, OutputIterator out_it)\
    { return boost::math::airy_bi_zero<T>(start_index, number_of_zeros, out_it, Policy()); }\
    \
    template <class T>\
diff --git a/include/boost/math/tools/workaround.hpp b/include/boost/math/tools/workaround.hpp
index 9b15c4e930..7edd1c12aa 100644
--- a/include/boost/math/tools/workaround.hpp
+++ b/include/boost/math/tools/workaround.hpp
@@ -23,7 +23,7 @@ namespace boost{ namespace math{ namespace tools{
 // std::fmod(1185.0L, 1.5L);
 //
 template <class T>
-inline T fmod_workaround(T a, T b) BOOST_MATH_NOEXCEPT(T)
+BOOST_MATH_GPU_ENABLED inline T fmod_workaround(T a, T b) BOOST_MATH_NOEXCEPT(T)
 {
    BOOST_MATH_STD_USING
    return fmod(a, b);
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index b3e1992c63..0ba47dace3 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -244,6 +244,15 @@ run test_weibull_quan_double.cu ;
 run test_weibull_quan_float.cu ;
 
 # Special Functions
+run test_airy_ai_double.cu ;
+run test_airy_ai_float.cu ;
+run test_airy_ai_prime_double.cu ;
+run test_airy_ai_prime_float.cu ;
+run test_airy_bi_double.cu ;
+run test_airy_bi_float.cu ;
+run test_airy_bi_prime_double.cu ;
+run test_airy_bi_prime_float.cu ;
+
 run test_beta_double.cu ;
 run test_beta_float.cu ;
 run test_betac_double.cu ;
@@ -308,6 +317,19 @@ run test_cos_pi_float.cu ;
 run test_digamma_double.cu ;
 run test_digamma_float.cu ;
 
+run test_ellint_1_double.cu ;
+run test_ellint_1_float.cu ;
+run test_ellint_2_double.cu ;
+run test_ellint_2_float.cu ;
+run test_ellint_3_double.cu ;
+run test_ellint_3_float.cu ;
+run test_ellint_d_double.cu ;
+run test_ellint_d_float.cu ;
+run test_jacobi_zeta_double.cu ;
+run test_jacobi_zeta_float.cu ;
+run test_heuman_lambda_double.cu ;
+run test_heuman_lambda_float.cu ;
+
 run test_erf_double.cu ;
 run test_erf_float.cu ;
 run test_erf_inv_double.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index 46dd0e257f..eb5da37c83 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -9,6 +9,9 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
+run test_heumann_lambda_nvrtc_double.cpp ;
+run test_heumann_lambda_nvrtc_float.cpp ;
+
 # Quad
 run test_exp_sinh_quad_nvrtc_float.cpp ;
 run test_exp_sinh_quad_nvrtc_double.cpp ;
@@ -241,6 +244,15 @@ run test_weibull_quan_nvrtc_double.cpp ;
 run test_weibull_quan_nvrtc_float.cpp ;
 
 # Special Functions
+run test_airy_ai_nvrtc_double.cpp ;
+run test_airy_ai_nvrtc_float.cpp ;
+run test_airy_ai_prime_nvrtc_double.cpp ;
+run test_airy_ai_prime_nvrtc_float.cpp ;
+run test_airy_bi_nvrtc_double.cpp ;
+run test_airy_bi_nvrtc_float.cpp ;
+run test_airy_bi_prime_nvrtc_double.cpp ;
+run test_airy_bi_prime_nvrtc_float.cpp ;
+
 run test_beta_nvrtc_double.cpp ;
 run test_beta_nvrtc_float.cpp ;
 run test_betac_nvrtc_double.cpp ;
@@ -313,6 +325,17 @@ run test_erf_inv_nvrtc_float.cpp ;
 run test_erfc_inv_nvrtc_double.cpp ;
 run test_erfc_inv_nvrtc_float.cpp ;
 
+run test_ellint_1_nvrtc_double.cpp ;
+run test_ellint_1_nvrtc_float.cpp ;
+run test_ellint_2_nvrtc_double.cpp ;
+run test_ellint_2_nvrtc_float.cpp ;
+run test_ellint_3_nvrtc_double.cpp ;
+run test_ellint_3_nvrtc_float.cpp ;
+run test_ellint_d_nvrtc_double.cpp ;
+run test_ellint_d_nvrtc_float.cpp ;
+run test_jacobi_zeta_nvrtc_double.cpp ;
+run test_jacobi_zeta_nvrtc_float.cpp ;
+
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
 
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index 1626031082..ff6d84fde5 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -46,6 +46,8 @@ run test_weibull.cpp ;
 # Special Functions
 run pow_test.cpp ;
 
+run test_airy.cpp ;
+
 run test_beta_simple.cpp ;
 run test_beta.cpp ;
 run test_ibeta.cpp ;
@@ -59,6 +61,12 @@ run test_bessel_y.cpp ;
 
 run test_cbrt.cpp ;
 
+run test_ellint_1.cpp ;
+run test_ellint_2.cpp ;
+run test_ellint_d.cpp ;
+run test_jacobi_zeta.cpp ;
+run test_heuman_lambda.cpp ;
+
 run test_sign.cpp ;
 
 run test_round.cpp ;
diff --git a/test/test_airy.cpp b/test/test_airy.cpp
index d42fbb4ca3..548d4de159 100644
--- a/test/test_airy.cpp
+++ b/test/test_airy.cpp
@@ -3,14 +3,21 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
 
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/airy.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #include <boost/array.hpp>
 #include <iostream>
 #include <iomanip>
@@ -50,6 +57,11 @@ void test_airy(T, const char* name)
    T tol = boost::math::tools::epsilon<T>() * 800;
    if ((std::numeric_limits<T>::digits > 100) || (std::numeric_limits<T>::digits == 0))
       tol *= 2;
+
+   #ifdef SYCL_LANGUAGE_VERSION
+   tol *= 5;
+   #endif
+
    for(unsigned i = 0; i < data.size(); ++i)
    {
       BOOST_CHECK_CLOSE_FRACTION(data[i][1], boost::math::airy_ai(data[i][0]), tol);
diff --git a/test/test_airy_ai_double.cu b/test/test_airy_ai_double.cu
new file mode 100644
index 0000000000..fad46bd9d5
--- /dev/null
+++ b/test/test_airy_ai_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_ai(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_ai_float.cu b/test/test_airy_ai_float.cu
new file mode 100644
index 0000000000..b9149aec39
--- /dev/null
+++ b/test/test_airy_ai_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_ai(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_ai_nvrtc_double.cpp b/test/test_airy_ai_nvrtc_double.cpp
new file mode 100644
index 0000000000..1b918cfef2
--- /dev/null
+++ b/test/test_airy_ai_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_ai_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_ai_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_ai_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_ai_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_ai(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_ai_nvrtc_float.cpp b/test/test_airy_ai_nvrtc_float.cpp
new file mode 100644
index 0000000000..6957306426
--- /dev/null
+++ b/test/test_airy_ai_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_ai_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_ai_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_ai_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_ai_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_ai(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_ai_prime_double.cu b/test/test_airy_ai_prime_double.cu
new file mode 100644
index 0000000000..1a6bcd7104
--- /dev/null
+++ b/test/test_airy_ai_prime_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai_prime(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_ai_prime(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_ai_prime_float.cu b/test/test_airy_ai_prime_float.cu
new file mode 100644
index 0000000000..df690c2b10
--- /dev/null
+++ b/test/test_airy_ai_prime_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai_prime(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_ai_prime(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_ai_prime_nvrtc_double.cpp b/test/test_airy_ai_prime_nvrtc_double.cpp
new file mode 100644
index 0000000000..1012571761
--- /dev/null
+++ b/test/test_airy_ai_prime_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_ai_prime_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai_prime(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_ai_prime_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_ai_prime_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_ai_prime_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_ai_prime(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_ai_prime_nvrtc_float.cpp b/test/test_airy_ai_prime_nvrtc_float.cpp
new file mode 100644
index 0000000000..c96e044497
--- /dev/null
+++ b/test/test_airy_ai_prime_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_ai_prime_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_ai_prime(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_ai_prime_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_ai_prime_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_ai_prime_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_ai_prime(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_bi_double.cu b/test/test_airy_bi_double.cu
new file mode 100644
index 0000000000..60001a3fe5
--- /dev/null
+++ b/test/test_airy_bi_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_bi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_bi_float.cu b/test/test_airy_bi_float.cu
new file mode 100644
index 0000000000..ed729bfe78
--- /dev/null
+++ b/test/test_airy_bi_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_bi(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_bi_nvrtc_double.cpp b/test/test_airy_bi_nvrtc_double.cpp
new file mode 100644
index 0000000000..f69e239163
--- /dev/null
+++ b/test/test_airy_bi_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_bi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_bi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_bi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_bi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_bi(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_bi_nvrtc_float.cpp b/test/test_airy_bi_nvrtc_float.cpp
new file mode 100644
index 0000000000..c28a5f5eb0
--- /dev/null
+++ b/test/test_airy_bi_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_bi_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_bi_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_bi_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_bi_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_bi(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_bi_prime_double.cu b/test/test_airy_bi_prime_double.cu
new file mode 100644
index 0000000000..a73e43f254
--- /dev/null
+++ b/test/test_airy_bi_prime_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi_prime(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_bi_prime(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_bi_prime_float.cu b/test/test_airy_bi_prime_float.cu
new file mode 100644
index 0000000000..36874bccc7
--- /dev/null
+++ b/test/test_airy_bi_prime_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi_prime(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::airy_bi_prime(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_airy_bi_prime_nvrtc_double.cpp b/test/test_airy_bi_prime_nvrtc_double.cpp
new file mode 100644
index 0000000000..802f63a292
--- /dev/null
+++ b/test/test_airy_bi_prime_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_bi_prime_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi_prime(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_bi_prime_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_bi_prime_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_bi_prime_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_bi_prime(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_airy_bi_prime_nvrtc_float.cpp b/test/test_airy_bi_prime_nvrtc_float.cpp
new file mode 100644
index 0000000000..e96aa48b97
--- /dev/null
+++ b/test/test_airy_bi_prime_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/airy.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/airy.hpp>
+extern "C" __global__ 
+void test_airy_bi_prime_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::airy_bi_prime(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_airy_bi_prime_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_airy_bi_prime_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_airy_bi_prime_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1000.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::airy_bi_prime(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_1.cpp b/test/test_ellint_1.cpp
index b5cb2a359e..db82132a5a 100644
--- a/test/test_ellint_1.cpp
+++ b/test/test_ellint_1.cpp
@@ -6,7 +6,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_ellint_1.hpp"
 
 //
diff --git a/test/test_ellint_1.hpp b/test/test_ellint_1.hpp
index 635bcf2293..786841302c 100644
--- a/test/test_ellint_1.hpp
+++ b/test/test_ellint_1.hpp
@@ -9,11 +9,15 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/ellint_1.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
 
@@ -139,11 +143,13 @@ void test_spots(T, const char* type_name)
     //
     // Test error handling:
     //
+    #ifndef BOOST_MATH_NO_EXCEPTIONS
     BOOST_CHECK_GE(boost::math::ellint_1(T(1)), boost::math::tools::max_value<T>());
     BOOST_CHECK_GE(boost::math::ellint_1(T(-1)), boost::math::tools::max_value<T>());
     BOOST_CHECK_THROW(boost::math::ellint_1(T(1.0001)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::ellint_1(T(-1.0001)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::ellint_1(T(2.2), T(0.5)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::ellint_1(T(-2.2), T(0.5)), std::domain_error);
+    #endif
 }
 
diff --git a/test/test_ellint_1_double.cu b/test/test_ellint_1_double.cu
new file mode 100644
index 0000000000..eb9bfb162d
--- /dev/null
+++ b/test/test_ellint_1_double.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = dist(rng);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                return EXIT_FAILURE;
+            }
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_1_float.cu b/test/test_ellint_1_float.cu
new file mode 100644
index 0000000000..8de959d225
--- /dev/null
+++ b/test/test_ellint_1_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_1(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_1(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_1_nvrtc_double.cpp b/test/test_ellint_1_nvrtc_double.cpp
new file mode 100644
index 0000000000..fac5da55f0
--- /dev/null
+++ b/test/test_ellint_1_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_1.hpp>
+extern "C" __global__ 
+void test_ellint_1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_1_nvrtc_float.cpp b/test/test_ellint_1_nvrtc_float.cpp
new file mode 100644
index 0000000000..fac5da55f0
--- /dev/null
+++ b/test/test_ellint_1_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_1.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_1.hpp>
+extern "C" __global__ 
+void test_ellint_1_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_1(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_1(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_2.cpp b/test/test_ellint_2.cpp
index ca3e994d4d..0da012c133 100644
--- a/test/test_ellint_2.cpp
+++ b/test/test_ellint_2.cpp
@@ -6,7 +6,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_ellint_2.hpp"
 
 //
@@ -72,7 +75,11 @@ void expected_results()
       ".*",                          // platform
       largest_type,                  // test type(s)
       ".*",      // test data group
+      #ifdef SYCL_LANGUAGE_VERSION
+      ".*", 20, 6);  // test function
+      #else
       ".*", 15, 6);  // test function
+      #endif
    add_expected_result(
       ".*",                          // compiler
       ".*",                          // stdlib
diff --git a/test/test_ellint_2.hpp b/test/test_ellint_2.hpp
index e38f94d984..29a73c9961 100644
--- a/test/test_ellint_2.hpp
+++ b/test/test_ellint_2.hpp
@@ -9,11 +9,18 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/ellint_2.hpp>
+#include <boost/math/constants/constants.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
 
@@ -157,10 +164,12 @@ void test_spots(T, const char* type_name)
     //
     // Test error handling:
     //
+    #ifndef BOOST_MATH_NO_EXCEPTIONS
     BOOST_CHECK_EQUAL(boost::math::ellint_2(T(1)), T(1));
     BOOST_CHECK_EQUAL(boost::math::ellint_2(T(-1)), T(1));
     BOOST_CHECK_THROW(boost::math::ellint_2(T(1.5)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::ellint_2(T(-1.5)), std::domain_error);
     BOOST_CHECK_THROW(boost::math::ellint_2(T(1.5), T(1.5)), std::domain_error);
+    #endif
 }
 
diff --git a/test/test_ellint_2_double.cu b/test/test_ellint_2_double.cu
new file mode 100644
index 0000000000..2e1073576e
--- /dev/null
+++ b/test/test_ellint_2_double.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_2(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_2(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_2_float.cu b/test/test_ellint_2_float.cu
new file mode 100644
index 0000000000..a55a6d1ad4
--- /dev/null
+++ b/test/test_ellint_2_float.cu
@@ -0,0 +1,100 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_2(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_2(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_2_nvrtc_double.cpp b/test/test_ellint_2_nvrtc_double.cpp
new file mode 100644
index 0000000000..dd2eef1547
--- /dev/null
+++ b/test/test_ellint_2_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_2.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_2.hpp>
+extern "C" __global__ 
+void test_ellint_2_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_2(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_2(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_2_nvrtc_float.cpp b/test/test_ellint_2_nvrtc_float.cpp
new file mode 100644
index 0000000000..dd2eef1547
--- /dev/null
+++ b/test/test_ellint_2_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_2.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_2.hpp>
+extern "C" __global__ 
+void test_ellint_2_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_2(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_2(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_3_double.cu b/test/test_ellint_3_double.cu
new file mode 100644
index 0000000000..979e01ff18
--- /dev/null
+++ b/test/test_ellint_3_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_3(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_3_float.cu b/test/test_ellint_3_float.cu
new file mode 100644
index 0000000000..979e01ff18
--- /dev/null
+++ b/test/test_ellint_3_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_3(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_3_nvrtc_double.cpp b/test/test_ellint_3_nvrtc_double.cpp
new file mode 100644
index 0000000000..dacab66192
--- /dev/null
+++ b/test/test_ellint_3_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_3.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_3.hpp>
+extern "C" __global__ 
+void test_ellint_3_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_3_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_3_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_3_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_3(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_3_nvrtc_float.cpp b/test/test_ellint_3_nvrtc_float.cpp
new file mode 100644
index 0000000000..72b2ec71e7
--- /dev/null
+++ b/test/test_ellint_3_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_3.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_3.hpp>
+extern "C" __global__ 
+void test_ellint_3_kernel(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_3_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_3_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_3_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_3(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_d.cpp b/test/test_ellint_d.cpp
index 5e76a49fb6..420bc0c022 100644
--- a/test/test_ellint_d.cpp
+++ b/test/test_ellint_d.cpp
@@ -4,7 +4,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_ellint_d.hpp"
 
 //
diff --git a/test/test_ellint_d.hpp b/test/test_ellint_d.hpp
index de53936f1f..c33a4d942a 100644
--- a/test/test_ellint_d.hpp
+++ b/test/test_ellint_d.hpp
@@ -8,11 +8,17 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/ellint_d.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
 
@@ -117,6 +123,7 @@ void test_spots(T, const char* type_name)
 
     do_test_ellint_d1<T>(ellint_d_data, type_name, "Elliptic Integral D: Random Data");
 
+    #ifdef BOOST_MATH_NO_EXCEPTIONS
     BOOST_MATH_CHECK_THROW(boost::math::ellint_d(T(1)), std::domain_error);
     BOOST_MATH_CHECK_THROW(boost::math::ellint_d(T(-1)), std::domain_error);
     BOOST_MATH_CHECK_THROW(boost::math::ellint_d(T(1.5)), std::domain_error);
@@ -126,5 +133,6 @@ void test_spots(T, const char* type_name)
        BOOST_CHECK_EQUAL(boost::math::ellint_d(T(0.5), std::numeric_limits<T>::infinity()), std::numeric_limits<T>::infinity());
     }
     BOOST_MATH_CHECK_THROW(boost::math::ellint_d(T(1.5), T(1.0)), std::domain_error);
+    #endif
 }
 
diff --git a/test/test_ellint_d_double.cu b/test/test_ellint_d_double.cu
new file mode 100644
index 0000000000..979e01ff18
--- /dev/null
+++ b/test/test_ellint_d_double.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_3(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_d_float.cu b/test/test_ellint_d_float.cu
new file mode 100644
index 0000000000..50882aa76a
--- /dev/null
+++ b/test/test_ellint_d_float.cu
@@ -0,0 +1,104 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_3(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::ellint_3(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (boost::math::epsilon_difference(output_vector[i], results[i]) > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+            return EXIT_FAILURE;
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_ellint_d_nvrtc_double.cpp b/test/test_ellint_d_nvrtc_double.cpp
new file mode 100644
index 0000000000..cb65a2e731
--- /dev/null
+++ b/test/test_ellint_d_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_d.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_d.hpp>
+extern "C" __global__ 
+void test_ellint_d_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_d(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_d_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_d_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_d_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_d(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_ellint_d_nvrtc_float.cpp b/test/test_ellint_d_nvrtc_float.cpp
new file mode 100644
index 0000000000..727d9dcd17
--- /dev/null
+++ b/test/test_ellint_d_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/ellint_d.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/ellint_d.hpp>
+extern "C" __global__ 
+void test_ellint_d_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::ellint_d(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_ellint_d_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_ellint_d_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_ellint_d_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::ellint_d(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_heuman_lambda.cpp b/test/test_heuman_lambda.cpp
index 83709c635b..cdcf39aa68 100644
--- a/test/test_heuman_lambda.cpp
+++ b/test/test_heuman_lambda.cpp
@@ -4,7 +4,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_heuman_lambda.hpp"
 
 //
diff --git a/test/test_heuman_lambda.hpp b/test/test_heuman_lambda.hpp
index 23720b2d02..6081dac482 100644
--- a/test/test_heuman_lambda.hpp
+++ b/test/test_heuman_lambda.hpp
@@ -8,11 +8,17 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/heuman_lambda.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
diff --git a/test/test_heuman_lambda_double.cu b/test/test_heuman_lambda_double.cu
new file mode 100644
index 0000000000..361dbe8051
--- /dev/null
+++ b/test/test_heuman_lambda_double.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::heuman_lambda(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::heuman_lambda(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 200)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_heuman_lambda_float.cu b/test/test_heuman_lambda_float.cu
new file mode 100644
index 0000000000..361dbe8051
--- /dev/null
+++ b/test/test_heuman_lambda_float.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::heuman_lambda(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::heuman_lambda(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 200)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_heumann_lambda_nvrtc_double.cpp b/test/test_heumann_lambda_nvrtc_double.cpp
new file mode 100644
index 0000000000..38c762fd51
--- /dev/null
+++ b/test/test_heumann_lambda_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/heuman_lambda.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/heuman_lambda.hpp>
+extern "C" __global__ 
+void test_heuman_lambda_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::heuman_lambda(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_heuman_lambda_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_heuman_lambda_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_heuman_lambda_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::heuman_lambda(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_heumann_lambda_nvrtc_float.cpp b/test/test_heumann_lambda_nvrtc_float.cpp
new file mode 100644
index 0000000000..5139b9d6f6
--- /dev/null
+++ b/test/test_heumann_lambda_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/heuman_lambda.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/heuman_lambda.hpp>
+extern "C" __global__ 
+void test_heuman_lambda_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::heuman_lambda(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_heuman_lambda_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_heuman_lambda_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_heuman_lambda_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::heuman_lambda(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_jacobi_zeta.cpp b/test/test_jacobi_zeta.cpp
index 77f33efb1e..c64f99580e 100644
--- a/test/test_jacobi_zeta.cpp
+++ b/test/test_jacobi_zeta.cpp
@@ -4,7 +4,10 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
 #include "test_jacobi_zeta.hpp"
 
 //
diff --git a/test/test_jacobi_zeta.hpp b/test/test_jacobi_zeta.hpp
index 1aa72feb0d..a39d3ba709 100644
--- a/test/test_jacobi_zeta.hpp
+++ b/test/test_jacobi_zeta.hpp
@@ -8,11 +8,17 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/jacobi_zeta.hpp>
 #include <boost/math/constants/constants.hpp>
 //#include <boost/math/special_functions/next.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_jacobi_zeta_double.cu b/test/test_jacobi_zeta_double.cu
new file mode 100644
index 0000000000..8594da140b
--- /dev/null
+++ b/test/test_jacobi_zeta_double.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::jacobi_zeta(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::jacobi_zeta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 200)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_jacobi_zeta_float.cu b/test/test_jacobi_zeta_float.cu
new file mode 100644
index 0000000000..7b473455ad
--- /dev/null
+++ b/test/test_jacobi_zeta_float.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::jacobi_zeta(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::jacobi_zeta(input_vector1[i], input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 200)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_jacobi_zeta_nvrtc_double.cpp b/test/test_jacobi_zeta_nvrtc_double.cpp
new file mode 100644
index 0000000000..ded2e66571
--- /dev/null
+++ b/test/test_jacobi_zeta_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/jacobi_zeta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/jacobi_zeta.hpp>
+extern "C" __global__ 
+void test_jacobi_zeta_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::jacobi_zeta(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_jacobi_zeta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_jacobi_zeta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_jacobi_zeta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::jacobi_zeta(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_jacobi_zeta_nvrtc_float.cpp b/test/test_jacobi_zeta_nvrtc_float.cpp
new file mode 100644
index 0000000000..de52da118d
--- /dev/null
+++ b/test/test_jacobi_zeta_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/jacobi_zeta.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/jacobi_zeta.hpp>
+extern "C" __global__ 
+void test_jacobi_zeta_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::jacobi_zeta(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_jacobi_zeta_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_jacobi_zeta_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_jacobi_zeta_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::jacobi_zeta(h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From f985ba209eedcb29893305f1c82ea4bbb23ecdfa Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 16 Sep 2024 15:12:40 -0400
Subject: [PATCH 382/399] Fix windows cases of overflow error

---
 test/test_ellint_1.cpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/test/test_ellint_1.cpp b/test/test_ellint_1.cpp
index db82132a5a..9366e4545a 100644
--- a/test/test_ellint_1.cpp
+++ b/test/test_ellint_1.cpp
@@ -10,6 +10,10 @@
 #include <pch_light.hpp>
 #endif
 
+#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#endif
+
 #include "test_ellint_1.hpp"
 
 //

From dbb547b5ac051b698331af342511a005e9b9505c Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Mon, 16 Sep 2024 16:33:48 -0400
Subject: [PATCH 383/399] Fix CUDA only macro for NVRTC

---
 include/boost/math/tools/config.hpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 6d7af4d2be..99bc4ee27e 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -789,6 +789,7 @@ BOOST_MATH_GPU_ENABLED constexpr T gpu_safe_max(const T& a, const T& b) { return
 #define BOOST_MATH_HAS_GPU_SUPPORT
 
 #define BOOST_MATH_GPU_ENABLED __host__ __device__
+#define BOOST_MATH_CUDA_ENABLED __host__ __device__
 
 #define BOOST_MATH_STATIC static
 #define BOOST_MATH_STATIC_LOCAL_VARIABLE

From bbb8eee1d6dc837b0c09637b1bf62e3c9245b63a Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Tue, 17 Sep 2024 15:23:54 -0400
Subject: [PATCH 384/399] Add GPU support to expint

Add SYCL testing of expint

Add markers to forward decls

Add CUDA testing of expint

Fix static variable usage under NVRTC

Add NVRTC testing

Add configurable definition of complex

Add function aliases

Add GPU support to gegenbauer polynomials

Add SYCL testing of gegenbauer

Add NVCC testing of gegenbauer

Add NVRTC testing of gegenbauer

Add GPU support for hankel

Add SYCL testing of hankel

Add NVCC testing of cyl_hankel_1

Add comprehensive NVCC testing

Add NVRTC testing of cyl and sph hankel

Update docs

Fix writing cuda::std::complex<T> to stdout

Add GPU support to hermite

Add SYCL testing of hermite

Add CUDA testing of hermite

Add NVRTC testing of hermite

Add markers to hermite docs
---
 doc/sf/airy.qbk                               |  32 +--
 doc/sf/expint.qbk                             |  16 +-
 doc/sf/gegenbauer.qbk                         |   6 +-
 doc/sf/hankel.qbk                             |  51 ++++-
 doc/sf/hermite.qbk                            |  12 +-
 .../boost/math/special_functions/bessel.hpp   |  44 ----
 .../boost/math/special_functions/expint.hpp   | 177 +++++++++-------
 .../math/special_functions/gegenbauer.hpp     |  21 +-
 .../boost/math/special_functions/hankel.hpp   |  62 +++---
 .../boost/math/special_functions/hermite.hpp  |  14 +-
 .../boost/math/special_functions/math_fwd.hpp |  93 ++++++--
 include/boost/math/tools/complex.hpp          |  86 +++++++-
 include/boost/math/tools/config.hpp           |   1 +
 test/cuda_jamfile                             |  17 ++
 test/nvrtc_jamfile                            |  22 +-
 test/sycl_jamfile                             |   8 +
 test/test_cyl_hankel_1_double.cu              | 119 +++++++++++
 test/test_cyl_hankel_1_float.cu               | 119 +++++++++++
 test/test_cyl_hankel_1_nvrtc_double.cpp       | 199 ++++++++++++++++++
 test/test_cyl_hankel_1_nvrtc_float.cpp        | 199 ++++++++++++++++++
 test/test_cyl_hankel_2_double.cu              | 119 +++++++++++
 test/test_cyl_hankel_2_float.cu               | 119 +++++++++++
 test/test_cyl_hankel_2_nvrtc_double.cpp       | 199 ++++++++++++++++++
 test/test_cyl_hankel_2_nvrtc_float.cpp        | 199 ++++++++++++++++++
 test/test_expint.cpp                          |  11 +
 test/test_expint.hpp                          |   8 +-
 test/test_expint_double.cu                    | 106 ++++++++++
 test/test_expint_float.cu                     | 106 ++++++++++
 test/test_expint_nvrtc_double.cpp             | 190 +++++++++++++++++
 test/test_expint_nvrtc_float.cpp              | 190 +++++++++++++++++
 test/test_gegenbauer_double.cu                | 125 +++++++++++
 test/test_gegenbauer_float.cu                 | 124 +++++++++++
 test/test_gegenbauer_nvrtc_double.cpp         | 190 +++++++++++++++++
 test/test_gegenbauer_nvrtc_float.cpp          | 190 +++++++++++++++++
 test/test_hankel.cpp                          |   7 +-
 test/test_hermite.cpp                         |   5 +-
 test/test_hermite.hpp                         |   6 +
 test/test_hermite_double.cu                   | 120 +++++++++++
 test/test_hermite_float.cu                    | 120 +++++++++++
 test/test_hermite_nvrtc_double.cpp            | 190 +++++++++++++++++
 test/test_hermite_nvrtc_float.cpp             | 190 +++++++++++++++++
 test/test_sph_hankel_1_double.cu              | 119 +++++++++++
 test/test_sph_hankel_1_float.cu               | 119 +++++++++++
 test/test_sph_hankel_1_nvrtc_double.cpp       | 199 ++++++++++++++++++
 test/test_sph_hankel_1_nvrtc_float.cpp        | 199 ++++++++++++++++++
 test/test_sph_hankel_2_double.cu              | 119 +++++++++++
 test/test_sph_hankel_2_float.cu               | 119 +++++++++++
 test/test_sph_hankel_2_nvrtc_double.cpp       | 199 ++++++++++++++++++
 test/test_sph_hankel_2_nvrtc_float.cpp        | 199 ++++++++++++++++++
 49 files changed, 4845 insertions(+), 239 deletions(-)
 create mode 100644 test/test_cyl_hankel_1_double.cu
 create mode 100644 test/test_cyl_hankel_1_float.cu
 create mode 100644 test/test_cyl_hankel_1_nvrtc_double.cpp
 create mode 100644 test/test_cyl_hankel_1_nvrtc_float.cpp
 create mode 100644 test/test_cyl_hankel_2_double.cu
 create mode 100644 test/test_cyl_hankel_2_float.cu
 create mode 100644 test/test_cyl_hankel_2_nvrtc_double.cpp
 create mode 100644 test/test_cyl_hankel_2_nvrtc_float.cpp
 create mode 100644 test/test_expint_double.cu
 create mode 100644 test/test_expint_float.cu
 create mode 100644 test/test_expint_nvrtc_double.cpp
 create mode 100644 test/test_expint_nvrtc_float.cpp
 create mode 100644 test/test_gegenbauer_double.cu
 create mode 100644 test/test_gegenbauer_float.cu
 create mode 100644 test/test_gegenbauer_nvrtc_double.cpp
 create mode 100644 test/test_gegenbauer_nvrtc_float.cpp
 create mode 100644 test/test_hermite_double.cu
 create mode 100644 test/test_hermite_float.cu
 create mode 100644 test/test_hermite_nvrtc_double.cpp
 create mode 100644 test/test_hermite_nvrtc_float.cpp
 create mode 100644 test/test_sph_hankel_1_double.cu
 create mode 100644 test/test_sph_hankel_1_float.cu
 create mode 100644 test/test_sph_hankel_1_nvrtc_double.cpp
 create mode 100644 test/test_sph_hankel_1_nvrtc_float.cpp
 create mode 100644 test/test_sph_hankel_2_double.cu
 create mode 100644 test/test_sph_hankel_2_float.cu
 create mode 100644 test/test_sph_hankel_2_nvrtc_double.cpp
 create mode 100644 test/test_sph_hankel_2_nvrtc_float.cpp

diff --git a/doc/sf/airy.qbk b/doc/sf/airy.qbk
index 5ff4c7cb5e..4756bee2d8 100644
--- a/doc/sf/airy.qbk
+++ b/doc/sf/airy.qbk
@@ -18,10 +18,10 @@ LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
   namespace boost { namespace math {
 
    template <class T>
-   ``__sf_result`` airy_ai(T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_ai(T x);
 
    template <class T, class Policy>
-   ``__sf_result`` airy_ai(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_ai(T x, const Policy&);
 
   }} // namespaces
   
@@ -78,10 +78,10 @@ This function is implemented in terms of the Bessel functions using the relation
   namespace boost { namespace math {
 
    template <class T>
-   ``__sf_result`` airy_bi(T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_bi(T x);
 
    template <class T, class Policy>
-   ``__sf_result`` airy_bi(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_bi(T x, const Policy&);
 
   }} // namespaces
   
@@ -132,10 +132,10 @@ This function is implemented in terms of the Bessel functions using the relation
   namespace boost { namespace math {
 
    template <class T>
-   ``__sf_result`` airy_ai_prime(T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_ai_prime(T x);
 
    template <class T, class Policy>
-   ``__sf_result`` airy_ai_prime(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_ai_prime(T x, const Policy&);
 
   }} // namespaces
   
@@ -186,10 +186,10 @@ This function is implemented in terms of the Bessel functions using the relation
   namespace boost { namespace math {
 
    template <class T>
-   ``__sf_result`` airy_bi_prime(T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_bi_prime(T x);
 
    template <class T, class Policy>
-   ``__sf_result`` airy_bi_prime(T x, const Policy&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` airy_bi_prime(T x, const Policy&);
 
   }} // namespaces
   
@@ -242,23 +242,23 @@ by providing an output iterator.
 The signature of the single value functions are:
 
   template <class T>
-  T airy_ai_zero(
+  BOOST_MATH_GPU_ENABLED T airy_ai_zero(
            int m);         // 1-based index of zero.
 
   template <class T>
-  T airy_bi_zero(
+  BOOST_MATH_GPU_ENABLED T airy_bi_zero(
            int m);         // 1-based index of zero.
 
 and for multiple zeros:
 
  template <class T, class OutputIterator>
- OutputIterator airy_ai_zero(
+ BOOST_MATH_GPU_ENABLED OutputIterator airy_ai_zero(
                       int start_index,           // 1-based index of first zero.
                       unsigned number_of_zeros,  // How many zeros to generate.
                       OutputIterator out_it);    // Destination for zeros.
 
  template <class T, class OutputIterator>
- OutputIterator airy_bi_zero(
+ BOOST_MATH_GPU_ENABLED OutputIterator airy_bi_zero(
                       int start_index,           // 1-based index of zero.
                       unsigned number_of_zeros,  // How many zeros to generate
                       OutputIterator out_it);    // Destination for zeros.
@@ -266,25 +266,25 @@ and for multiple zeros:
 There are also versions which allow control of the __policy_section for error handling and precision.
 
   template <class T>
-  T airy_ai_zero(
+  BOOST_MATH_GPU_ENABLED T airy_ai_zero(
            int m,          // 1-based index of zero.
            const Policy&); // Policy to use.
 
   template <class T>
-  T airy_bi_zero(
+  BOOST_MATH_GPU_ENABLED T airy_bi_zero(
            int m,          // 1-based index of zero.
            const Policy&); // Policy to use.
 
 
  template <class T, class OutputIterator>
- OutputIterator airy_ai_zero(
+ BOOST_MATH_GPU_ENABLED OutputIterator airy_ai_zero(
                       int start_index,           // 1-based index of first zero.
                       unsigned number_of_zeros,  // How many zeros to generate.
                       OutputIterator out_it,     // Destination for zeros.
                       const Policy& pol);        // Policy to use.
 
  template <class T, class OutputIterator>
- OutputIterator airy_bi_zero(
+ BOOST_MATH_GPU_ENABLED OutputIterator airy_bi_zero(
                       int start_index,           // 1-based index of zero.
                       unsigned number_of_zeros,  // How many zeros to generate.
                       OutputIterator out_it,     // Destination for zeros.
diff --git a/doc/sf/expint.qbk b/doc/sf/expint.qbk
index 89554730d5..f0abf090e7 100644
--- a/doc/sf/expint.qbk
+++ b/doc/sf/expint.qbk
@@ -11,10 +11,10 @@
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` expint(unsigned n, T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(unsigned n, T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` expint(unsigned n, T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(unsigned n, T z, const ``__Policy``&);
    
    }} // namespaces
    
@@ -26,10 +26,10 @@ the return type is `double` if T is an integer type, and T otherwise.
 [h4 Description]
 
    template <class T>
-   ``__sf_result`` expint(unsigned n, T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(unsigned n, T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` expint(unsigned n, T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(unsigned n, T z, const ``__Policy``&);
    
 Returns the [@http://mathworld.wolfram.com/En-Function.html exponential integral En]
 of z:
@@ -100,10 +100,10 @@ is used.
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` expint(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` expint(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(T z, const ``__Policy``&);
    
    }} // namespaces
    
@@ -115,10 +115,10 @@ the return type is `double` if T is an integer type, and T otherwise.
 [h4 Description]
 
    template <class T>
-   ``__sf_result`` expint(T z);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(T z);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` expint(T z, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` expint(T z, const ``__Policy``&);
    
 Returns the [@http://mathworld.wolfram.com/ExponentialIntegral.html exponential integral]
 of z:
diff --git a/doc/sf/gegenbauer.qbk b/doc/sf/gegenbauer.qbk
index a6afc53d82..69671917c8 100644
--- a/doc/sf/gegenbauer.qbk
+++ b/doc/sf/gegenbauer.qbk
@@ -16,13 +16,13 @@
    namespace boost{ namespace math{
 
    template<typename Real>
-   Real gegenbauer(unsigned n, Real lambda, Real x);
+   BOOST_MATH_GPU_ENABLED Real gegenbauer(unsigned n, Real lambda, Real x);
 
    template<typename Real>
-   Real gegenbauer_prime(unsigned n, Real lambda, Real x);
+   BOOST_MATH_GPU_ENABLED Real gegenbauer_prime(unsigned n, Real lambda, Real x);
 
    template<typename Real>
-   Real gegenbauer_derivative(unsigned n, Real lambda, Real x, unsigned k);
+   BOOST_MATH_GPU_ENABLED Real gegenbauer_derivative(unsigned n, Real lambda, Real x, unsigned k);
 
    }} // namespaces
 
diff --git a/doc/sf/hankel.qbk b/doc/sf/hankel.qbk
index 4d8a5eda1e..05d65201b1 100644
--- a/doc/sf/hankel.qbk
+++ b/doc/sf/hankel.qbk
@@ -3,18 +3,36 @@
 
 [h4 Synopsis]
 
+   #if !defined(__CUDACC__) && !defined(__CUDACC_RTC__)
+
    template <class T1, class T2>
-   std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x, const ``__Policy``&);
 
    template <class T1, class T2>
-   std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x);
    
    template <class T1, class T2, class ``__Policy``>
-   std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x, const ``__Policy``&);
    
+   #else // When using cuda we use namespace cuda::std:: instead of std::
+
+   template <class T1, class T2>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x);
+
+   template <class T1, class T2, class ``__Policy``>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_1(T1 v, T2 x, const ``__Policy``&);
+
+   template <class T1, class T2>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x);
+   
+   template <class T1, class T2, class ``__Policy``>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> cyl_hankel_2(T1 v, T2 x, const ``__Policy``&);
+
+   #endif
+
    
 [h4 Description]
 
@@ -77,18 +95,35 @@ routines for integer order are used.
 
 [h4 Synopsis]
 
+   #if !defined(__CUDACC__) && !defined(__CUDACC_RTC__)
+
    template <class T1, class T2>
-   std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x);
 
    template <class T1, class T2, class ``__Policy``>
-   std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x, const ``__Policy``&);
 
    template <class T1, class T2>
-   std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x);
+   
+   template <class T1, class T2, class ``__Policy``>
+   BOOST_MATH_GPU_ENABLED std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x, const ``__Policy``&);
    
+   #else // When using cuda we use namespace cuda::std:: instead of std::
+
+   template <class T1, class T2>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x);
+
    template <class T1, class T2, class ``__Policy``>
-   std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_1(T1 v, T2 x, const ``__Policy``&);
+
+   template <class T1, class T2>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x);
    
+   template <class T1, class T2, class ``__Policy``>
+   BOOST_MATH_GPU_ENABLED cuda::std::complex<``__sf_result``> sph_hankel_2(T1 v, T2 x, const ``__Policy``&);
+
+   #endif
    
 [h4 Description]
 
diff --git a/doc/sf/hermite.qbk b/doc/sf/hermite.qbk
index c88aadc344..965aa80928 100644
--- a/doc/sf/hermite.qbk
+++ b/doc/sf/hermite.qbk
@@ -9,13 +9,13 @@
    namespace boost{ namespace math{
    
    template <class T>
-   ``__sf_result`` hermite(unsigned n, T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite(unsigned n, T x);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` hermite(unsigned n, T x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite(unsigned n, T x, const ``__Policy``&);
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1);
       
    }} // namespaces
 
@@ -26,10 +26,10 @@ note than when there is a single template argument the result is the same type
 as that argument or `double` if the template argument is an integer type.
 
    template <class T>
-   ``__sf_result`` hermite(unsigned n, T x);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite(unsigned n, T x);
    
    template <class T, class ``__Policy``>
-   ``__sf_result`` hermite(unsigned n, T x, const ``__Policy``&);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite(unsigned n, T x, const ``__Policy``&);
    
 Returns the value of the Hermite Polynomial of order /n/ at point /x/:
 
@@ -43,7 +43,7 @@ Hermite Polynomials:
 [graph hermite]
    
    template <class T1, class T2, class T3>
-   ``__sf_result`` hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1);
+   BOOST_MATH_GPU_ENABLED ``__sf_result`` hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1);
    
 Implements the three term recurrence relation for the Hermite
 polynomials, this function can be used to create a sequence of
diff --git a/include/boost/math/special_functions/bessel.hpp b/include/boost/math/special_functions/bessel.hpp
index 0814734428..c32f251bcd 100644
--- a/include/boost/math/special_functions/bessel.hpp
+++ b/include/boost/math/special_functions/bessel.hpp
@@ -47,50 +47,6 @@
 
 namespace boost{ namespace math{
 
-// Since we cannot pull this in from math fwd we need a copy
-#ifdef BOOST_MATH_HAS_NVRTC
-
-namespace detail{
-
-      typedef boost::math::integral_constant<int, 0> bessel_no_int_tag;      // No integer optimisation possible.
-      typedef boost::math::integral_constant<int, 1> bessel_maybe_int_tag;   // Maybe integer optimisation.
-      typedef boost::math::integral_constant<int, 2> bessel_int_tag;         // Definite integer optimisation.
-
-      template <class T1, class T2, class Policy>
-      struct bessel_traits
-      {
-         using result_type = typename boost::math::conditional<
-            boost::math::is_integral<T1>::value,
-            typename tools::promote_args<T2>::type,
-            tools::promote_args_t<T1, T2>
-         >::type;
-
-         typedef typename policies::precision<result_type, Policy>::type precision_type;
-
-         using optimisation_tag = typename boost::math::conditional<
-            (precision_type::value <= 0 || precision_type::value > 64),
-            bessel_no_int_tag,
-            typename boost::math::conditional<
-               boost::math::is_integral<T1>::value,
-               bessel_int_tag,
-               bessel_maybe_int_tag
-            >::type
-         >::type;
-
-         using optimisation_tag128 = typename boost::math::conditional<
-            (precision_type::value <= 0 || precision_type::value > 113),
-            bessel_no_int_tag,
-            typename boost::math::conditional<
-               boost::math::is_integral<T1>::value,
-               bessel_int_tag,
-               bessel_maybe_int_tag
-            >::type
-         >::type;
-      };
-   } // detail
-
-#endif
-
 namespace detail{
 
 template <class T, class Policy>
diff --git a/include/boost/math/special_functions/expint.hpp b/include/boost/math/special_functions/expint.hpp
index 1475a9a88b..09e97bd4fc 100644
--- a/include/boost/math/special_functions/expint.hpp
+++ b/include/boost/math/special_functions/expint.hpp
@@ -1,4 +1,5 @@
 //  Copyright John Maddock 2007.
+//  Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -12,6 +13,10 @@
 #pragma warning(disable:4702) // Unreachable code (release mode only warning)
 #endif
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/cstdint.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/tuple.hpp>
 #include <boost/math/tools/precision.hpp>
 #include <boost/math/tools/promotion.hpp>
 #include <boost/math/tools/fraction.hpp>
@@ -20,7 +25,6 @@
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/digamma.hpp>
 #include <boost/math/special_functions/log1p.hpp>
-#include <boost/math/special_functions/pow.hpp>
 
 #if defined(__GNUC__) && defined(BOOST_MATH_USE_FLOAT128)
 //
@@ -35,13 +39,13 @@
 namespace boost{ namespace math{
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    expint(unsigned n, T z, const Policy& /*pol*/);
 
 namespace detail{
 
 template <class T>
-inline T expint_1_rational(const T& z, const std::integral_constant<int, 0>&)
+BOOST_MATH_GPU_ENABLED inline T expint_1_rational(const T& z, const boost::math::integral_constant<int, 0>&)
 {
    // this function is never actually called
    BOOST_MATH_ASSERT(0);
@@ -49,7 +53,7 @@ inline T expint_1_rational(const T& z, const std::integral_constant<int, 0>&)
 }
 
 template <class T>
-T expint_1_rational(const T& z, const std::integral_constant<int, 53>&)
+BOOST_MATH_GPU_ENABLED T expint_1_rational(const T& z, const boost::math::integral_constant<int, 53>&)
 {
    BOOST_MATH_STD_USING
    T result;
@@ -123,7 +127,7 @@ T expint_1_rational(const T& z, const std::integral_constant<int, 53>&)
 }
 
 template <class T>
-T expint_1_rational(const T& z, const std::integral_constant<int, 64>&)
+BOOST_MATH_GPU_ENABLED T expint_1_rational(const T& z, const boost::math::integral_constant<int, 64>&)
 {
    BOOST_MATH_STD_USING
    T result;
@@ -204,7 +208,7 @@ T expint_1_rational(const T& z, const std::integral_constant<int, 64>&)
 }
 
 template <class T>
-T expint_1_rational(const T& z, const std::integral_constant<int, 113>&)
+BOOST_MATH_GPU_ENABLED T expint_1_rational(const T& z, const boost::math::integral_constant<int, 113>&)
 {
    BOOST_MATH_STD_USING
    T result;
@@ -351,14 +355,15 @@ T expint_1_rational(const T& z, const std::integral_constant<int, 113>&)
    return result;
 }
 
+
 template <class T>
 struct expint_fraction
 {
-   typedef std::pair<T,T> result_type;
-   expint_fraction(unsigned n_, T z_) : b(n_ + z_), i(-1), n(n_){}
-   std::pair<T,T> operator()()
+   typedef boost::math::pair<T,T> result_type;
+   BOOST_MATH_GPU_ENABLED expint_fraction(unsigned n_, T z_) : b(n_ + z_), i(-1), n(n_){}
+   BOOST_MATH_GPU_ENABLED boost::math::pair<T,T> operator()()
    {
-      std::pair<T,T> result = std::make_pair(-static_cast<T>((i+1) * (n+i)), b);
+      boost::math::pair<T,T> result = boost::math::make_pair(-static_cast<T>((i+1) * (n+i)), b);
       b += 2;
       ++i;
       return result;
@@ -370,11 +375,11 @@ struct expint_fraction
 };
 
 template <class T, class Policy>
-inline T expint_as_fraction(unsigned n, T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T expint_as_fraction(unsigned n, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    BOOST_MATH_INSTRUMENT_VARIABLE(z)
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    expint_fraction<T> f(n, z);
    T result = tools::continued_fraction_b(
       f,
@@ -392,9 +397,9 @@ template <class T>
 struct expint_series
 {
    typedef T result_type;
-   expint_series(unsigned k_, T z_, T x_k_, T denom_, T fact_)
+   BOOST_MATH_GPU_ENABLED expint_series(unsigned k_, T z_, T x_k_, T denom_, T fact_)
       : k(k_), z(z_), x_k(x_k_), denom(denom_), fact(fact_){}
-   T operator()()
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       x_k *= -z;
       denom += 1;
@@ -410,10 +415,10 @@ struct expint_series
 };
 
 template <class T, class Policy>
-inline T expint_as_series(unsigned n, T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline T expint_as_series(unsigned n, T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
 
    BOOST_MATH_INSTRUMENT_VARIABLE(z)
 
@@ -443,10 +448,10 @@ inline T expint_as_series(unsigned n, T z, const Policy& pol)
 }
 
 template <class T, class Policy, class Tag>
-T expint_imp(unsigned n, T z, const Policy& pol, const Tag& tag)
+BOOST_MATH_GPU_ENABLED T expint_imp(unsigned n, T z, const Policy& pol, const Tag& tag)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::expint<%1%>(unsigned, %1%)";
+   constexpr auto function = "boost::math::expint<%1%>(unsigned, %1%)";
    if(z < 0)
       return policies::raise_domain_error<T>(function, "Function requires z >= 0 but got %1%.", z, pol);
    if(z == 0)
@@ -468,15 +473,21 @@ T expint_imp(unsigned n, T z, const Policy& pol, const Tag& tag)
 #  pragma warning(disable:4127) // conditional expression is constant
 #endif
    if(n == 0)
+   {
       result = exp(-z) / z;
+   }
    else if((n == 1) && (Tag::value))
    {
       result = expint_1_rational(z, tag);
    }
    else if(f)
+   {
       result = expint_as_series(n, z, pol);
+   }
    else
+   {
       result = expint_as_fraction(n, z, pol);
+   }
 #ifdef _MSC_VER
 #  pragma warning(pop)
 #endif
@@ -488,8 +499,8 @@ template <class T>
 struct expint_i_series
 {
    typedef T result_type;
-   expint_i_series(T z_) : k(0), z_k(1), z(z_){}
-   T operator()()
+   BOOST_MATH_GPU_ENABLED expint_i_series(T z_) : k(0), z_k(1), z(z_){}
+   BOOST_MATH_GPU_ENABLED T operator()()
    {
       z_k *= z / ++k;
       return z_k / k;
@@ -501,22 +512,22 @@ struct expint_i_series
 };
 
 template <class T, class Policy>
-T expint_i_as_series(T z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED T expint_i_as_series(T z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    T result = log(z); // (log(z) - log(1 / z)) / 2;
    result += constants::euler<T>();
    expint_i_series<T> s(z);
-   std::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
+   boost::math::uintmax_t max_iter = policies::get_max_series_iterations<Policy>();
    result = tools::sum_series(s, policies::get_epsilon<T, Policy>(), max_iter, result);
    policies::check_series_iterations<T>("boost::math::expint_i_series<%1%>(%1%)", max_iter, pol);
    return result;
 }
 
 template <class T, class Policy, class Tag>
-T expint_i_imp(T z, const Policy& pol, const Tag& tag)
+BOOST_MATH_GPU_ENABLED T expint_i_imp(T z, const Policy& pol, const Tag& tag)
 {
-   static const char* function = "boost::math::expint<%1%>(%1%)";
+   constexpr auto function = "boost::math::expint<%1%>(%1%)";
    if(z < 0)
       return -expint_imp(1, T(-z), pol, tag);
    if(z == 0)
@@ -525,10 +536,10 @@ T expint_i_imp(T z, const Policy& pol, const Tag& tag)
 }
 
 template <class T, class Policy>
-T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& tag)
+BOOST_MATH_GPU_ENABLED T expint_i_imp(T z, const Policy& pol, const boost::math::integral_constant<int, 53>& tag)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::expint<%1%>(%1%)";
+   constexpr auto function = "boost::math::expint<%1%>(%1%)";
    if(z < 0)
       return -expint_imp(1, T(-z), pol, tag);
    if(z == 0)
@@ -541,7 +552,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
       // Maximum Deviation Found:                     2.852e-18
       // Expected Error Term:                         2.852e-18
       // Max Error found at double precision =        Poly: 2.636335e-16   Cheb: 4.187027e-16
-      static const T P[10] = {
+      BOOST_MATH_STATIC const T P[10] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 2.98677224343598593013),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.356343618769377415068),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.780836076283730801839),
@@ -553,7 +564,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.798296365679269702435e-5),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.2777056254402008721e-6)
       };
-      static const T Q[8] = {
+      BOOST_MATH_STATIC const T Q[8] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 53, -1.17090412365413911947),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.62215109846016746276),
@@ -564,11 +575,11 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.138972589601781706598e-4)
       };
 
-      static const T c1 = BOOST_MATH_BIG_CONSTANT(T, 53, 1677624236387711.0);
-      static const T c2 = BOOST_MATH_BIG_CONSTANT(T, 53, 4503599627370496.0);
-      static const T r1 = static_cast<T>(c1 / c2);
-      static const T r2 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.131401834143860282009280387409357165515556574352422001206362e-16);
-      static const T r = static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 53, 0.372507410781366634461991866580119133535689497771654051555657435242200120636201854384926049951548942392));
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T c1 = BOOST_MATH_BIG_CONSTANT(T, 53, 1677624236387711.0);
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T c2 = BOOST_MATH_BIG_CONSTANT(T, 53, 4503599627370496.0);
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T r1 = static_cast<T>(c1 / c2);
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T r2 = BOOST_MATH_BIG_CONSTANT(T, 53, 0.131401834143860282009280387409357165515556574352422001206362e-16);
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T r = static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 53, 0.372507410781366634461991866580119133535689497771654051555657435242200120636201854384926049951548942392));
       T t = (z / 3) - 1;
       result = tools::evaluate_polynomial(P, t)
          / tools::evaluate_polynomial(Q, t);
@@ -588,8 +599,8 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
       // Maximum Deviation Found:                     6.546e-17
       // Expected Error Term:                         6.546e-17
       // Max Error found at double precision =        Poly: 6.890169e-17   Cheb: 6.772128e-17
-      static const T Y = 1.158985137939453125F;
-      static const T P[8] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 1.158985137939453125F;
+      BOOST_MATH_STATIC const T P[8] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.00139324086199402804173),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0349921221823888744966),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0264095520754134848538),
@@ -599,7 +610,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.554086272024881826253e-4),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.396487648924804510056e-5)
       };
-      static const T Q[8] = {
+      BOOST_MATH_STATIC const T Q[8] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.744625566823272107711),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.329061095011767059236),
@@ -621,8 +632,8 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
       // Expected Error Term:                         -1.842e-17
       // Max Error found at double precision =        Poly: 4.375868e-17   Cheb: 5.860967e-17
 
-      static const T Y = 1.0869731903076171875F;
-      static const T P[9] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 1.0869731903076171875F;
+      BOOST_MATH_STATIC const T P[9] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.00893891094356945667451),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0484607730127134045806),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0652810444222236895772),
@@ -633,7 +644,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.000209750022660200888349),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.138652200349182596186e-4)
       };
-      static const T Q[9] = {
+      BOOST_MATH_STATIC const T Q[9] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.97017214039061194971),
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.86232465043073157508),
@@ -657,8 +668,8 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
       // Max Error found at double precision =        Poly: 1.441088e-16   Cheb: 1.864792e-16
 
 
-      static const T Y = 1.03937530517578125F;
-      static const T P[9] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y = 1.03937530517578125F;
+      BOOST_MATH_STATIC const T P[9] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.00356165148914447597995),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0229930320357982333406),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0449814350482277917716),
@@ -669,7 +680,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.000192178045857733706044),
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.113161784705911400295e-9)
       };
-      static const T Q[9] = {
+      BOOST_MATH_STATIC const T Q[9] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 53, 2.84354408840148561131),
          BOOST_MATH_BIG_CONSTANT(T, 53, 3.6599610090072393012),
@@ -688,9 +699,9 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
    else
    {
       // Max Error found at double precision =        3.381886e-17
-      static const T exp40 = static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 53, 2.35385266837019985407899910749034804508871617254555467236651e17));
-      static const T Y= 1.013065338134765625F;
-      static const T P[6] = {
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T exp40 = static_cast<T>(BOOST_MATH_BIG_CONSTANT(T, 53, 2.35385266837019985407899910749034804508871617254555467236651e17));
+      BOOST_MATH_STATIC_LOCAL_VARIABLE const T Y= 1.013065338134765625F;
+      BOOST_MATH_STATIC const T P[6] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, -0.0130653381347656243849),
          BOOST_MATH_BIG_CONSTANT(T, 53, 0.19029710559486576682),
          BOOST_MATH_BIG_CONSTANT(T, 53, 94.7365094537197236011),
@@ -698,7 +709,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
          BOOST_MATH_BIG_CONSTANT(T, 53, 18932.0850014925993025),
          BOOST_MATH_BIG_CONSTANT(T, 53, -38703.1431362056714134)
       };
-      static const T Q[7] = {
+      BOOST_MATH_STATIC const T Q[7] = {
          BOOST_MATH_BIG_CONSTANT(T, 53, 1.0),
          BOOST_MATH_BIG_CONSTANT(T, 53, 61.9733592849439884145),
          BOOST_MATH_BIG_CONSTANT(T, 53, -2354.56211323420194283),
@@ -739,10 +750,10 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 53>& ta
 }
 
 template <class T, class Policy>
-T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 64>& tag)
+BOOST_MATH_GPU_ENABLED T expint_i_imp(T z, const Policy& pol, const boost::math::integral_constant<int, 64>& tag)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::expint<%1%>(%1%)";
+   constexpr auto function = "boost::math::expint<%1%>(%1%)";
    if(z < 0)
       return -expint_imp(1, T(-z), pol, tag);
    if(z == 0)
@@ -976,7 +987,7 @@ T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 64>& ta
 }
 
 template <class T, class Policy>
-void expint_i_imp_113a(T& result, const T& z, const Policy& pol)
+BOOST_MATH_GPU_ENABLED void expint_i_imp_113a(T& result, const T& z, const Policy& pol)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     1.230e-36
@@ -1044,7 +1055,7 @@ void expint_i_imp_113a(T& result, const T& z, const Policy& pol)
 }
 
 template <class T>
-void expint_i_113b(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113b(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     7.779e-36
@@ -1094,7 +1105,7 @@ void expint_i_113b(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113c(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113c(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     1.082e-34
@@ -1147,7 +1158,7 @@ void expint_i_113c(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113d(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113d(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     3.163e-35
@@ -1198,7 +1209,7 @@ void expint_i_113d(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113e(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113e(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     7.972e-36
@@ -1252,7 +1263,7 @@ void expint_i_113e(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113f(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113f(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     4.469e-36
@@ -1299,7 +1310,7 @@ void expint_i_113f(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113g(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113g(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     5.588e-35
@@ -1344,7 +1355,7 @@ void expint_i_113g(T& result, const T& z)
 }
 
 template <class T>
-void expint_i_113h(T& result, const T& z)
+BOOST_MATH_GPU_ENABLED void expint_i_113h(T& result, const T& z)
 {
    BOOST_MATH_STD_USING
    // Maximum Deviation Found:                     4.448e-36
@@ -1383,10 +1394,10 @@ void expint_i_113h(T& result, const T& z)
 }
 
 template <class T, class Policy>
-T expint_i_imp(T z, const Policy& pol, const std::integral_constant<int, 113>& tag)
+BOOST_MATH_GPU_ENABLED T expint_i_imp(T z, const Policy& pol, const boost::math::integral_constant<int, 113>& tag)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::expint<%1%>(%1%)";
+   constexpr auto function = "boost::math::expint<%1%>(%1%)";
    if(z < 0)
       return -expint_imp(1, T(-z), pol, tag);
    if(z == 0)
@@ -1491,12 +1502,12 @@ struct expint_i_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init(tag());
       }
-      static void do_init(const std::integral_constant<int, 0>&){}
-      static void do_init(const std::integral_constant<int, 53>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 0>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 53>&)
       {
          boost::math::expint(T(5), Policy());
          boost::math::expint(T(7), Policy());
@@ -1504,7 +1515,7 @@ struct expint_i_initializer
          boost::math::expint(T(38), Policy());
          boost::math::expint(T(45), Policy());
       }
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          boost::math::expint(T(5), Policy());
          boost::math::expint(T(7), Policy());
@@ -1512,7 +1523,7 @@ struct expint_i_initializer
          boost::math::expint(T(38), Policy());
          boost::math::expint(T(45), Policy());
       }
-      static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
       {
          boost::math::expint(T(5), Policy());
          boost::math::expint(T(7), Policy());
@@ -1524,12 +1535,14 @@ struct expint_i_initializer
          boost::math::expint(T(200), Policy());
          boost::math::expint(T(220), Policy());
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
    static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -1541,33 +1554,35 @@ struct expint_1_initializer
 {
    struct init
    {
-      init()
+      BOOST_MATH_GPU_ENABLED init()
       {
          do_init(tag());
       }
-      static void do_init(const std::integral_constant<int, 0>&){}
-      static void do_init(const std::integral_constant<int, 53>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 0>&){}
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 53>&)
       {
          boost::math::expint(1, T(0.5), Policy());
          boost::math::expint(1, T(2), Policy());
       }
-      static void do_init(const std::integral_constant<int, 64>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 64>&)
       {
          boost::math::expint(1, T(0.5), Policy());
          boost::math::expint(1, T(2), Policy());
       }
-      static void do_init(const std::integral_constant<int, 113>&)
+      BOOST_MATH_GPU_ENABLED static void do_init(const boost::math::integral_constant<int, 113>&)
       {
          boost::math::expint(1, T(0.5), Policy());
          boost::math::expint(1, T(2), Policy());
          boost::math::expint(1, T(6), Policy());
       }
-      void force_instantiate()const{}
+      BOOST_MATH_GPU_ENABLED void force_instantiate()const{}
    };
    static const init initializer;
-   static void force_instantiate()
+   BOOST_MATH_GPU_ENABLED static void force_instantiate()
    {
+      #ifndef BOOST_MATH_HAS_GPU_SUPPORT
       initializer.force_instantiate();
+      #endif
    }
 };
 
@@ -1575,8 +1590,8 @@ template <class T, class Policy, class tag>
 const typename expint_1_initializer<T, Policy, tag>::init expint_1_initializer<T, Policy, tag>::initializer;
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
-   expint_forwarder(T z, const Policy& /*pol*/, std::true_type const&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
+   expint_forwarder(T z, const Policy& /*pol*/, boost::math::true_type const&)
 {
    typedef typename tools::promote_args<T>::type result_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
@@ -1587,7 +1602,7 @@ inline typename tools::promote_args<T>::type
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 53 ? 53 :
       precision_type::value <= 64 ? 64 :
@@ -1603,8 +1618,8 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
-expint_forwarder(unsigned n, T z, const std::false_type&)
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
+expint_forwarder(unsigned n, T z, const boost::math::false_type&)
 {
    return boost::math::expint(n, z, policies::policy<>());
 }
@@ -1612,7 +1627,7 @@ expint_forwarder(unsigned n, T z, const std::false_type&)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    expint(unsigned n, T z, const Policy& /*pol*/)
 {
    typedef typename tools::promote_args<T>::type result_type;
@@ -1624,7 +1639,7 @@ inline typename tools::promote_args<T>::type
       policies::promote_double<false>,
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
-   typedef std::integral_constant<int,
+   typedef boost::math::integral_constant<int,
       precision_type::value <= 0 ? 0 :
       precision_type::value <= 53 ? 53 :
       precision_type::value <= 64 ? 64 :
@@ -1641,7 +1656,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T, class U>
-inline typename detail::expint_result<T, U>::type
+BOOST_MATH_GPU_ENABLED inline typename detail::expint_result<T, U>::type
    expint(T const z, U const u)
 {
    typedef typename policies::is_policy<U>::type tag_type;
@@ -1649,7 +1664,7 @@ inline typename detail::expint_result<T, U>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type
    expint(T z)
 {
    return expint(z, policies::policy<>());
diff --git a/include/boost/math/special_functions/gegenbauer.hpp b/include/boost/math/special_functions/gegenbauer.hpp
index b7033cd14f..70324cf656 100644
--- a/include/boost/math/special_functions/gegenbauer.hpp
+++ b/include/boost/math/special_functions/gegenbauer.hpp
@@ -1,4 +1,5 @@
 //  (C) Copyright Nick Thompson 2019.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -6,21 +7,25 @@
 #ifndef BOOST_MATH_SPECIAL_GEGENBAUER_HPP
 #define BOOST_MATH_SPECIAL_GEGENBAUER_HPP
 
-#include <limits>
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/numeric_limits.hpp>
+
+#ifndef BOOST_MATH_NO_EXCEPTIONS
 #include <stdexcept>
-#include <type_traits>
+#endif
 
 namespace boost { namespace math {
 
 template<typename Real>
-Real gegenbauer(unsigned n, Real lambda, Real x)
+BOOST_MATH_GPU_ENABLED Real gegenbauer(unsigned n, Real lambda, Real x)
 {
-    static_assert(!std::is_integral<Real>::value, "Gegenbauer polynomials required floating point arguments.");
+    static_assert(!boost::math::is_integral<Real>::value, "Gegenbauer polynomials required floating point arguments.");
     if (lambda <= -1/Real(2)) {
 #ifndef BOOST_MATH_NO_EXCEPTIONS
        throw std::domain_error("lambda > -1/2 is required.");
 #else
-       return std::numeric_limits<Real>::quiet_NaN();
+       return boost::math::numeric_limits<Real>::quiet_NaN();
 #endif
     }
     // The only reason to do this is because of some instability that could be present for x < 0 that is not present for x > 0.
@@ -41,7 +46,7 @@ Real gegenbauer(unsigned n, Real lambda, Real x)
 
     Real yk = y1;
     Real k = 2;
-    Real k_max = n*(1+std::numeric_limits<Real>::epsilon());
+    Real k_max = n*(1+boost::math::numeric_limits<Real>::epsilon());
     Real gamma = 2*(lambda - 1);
     while(k < k_max)
     {
@@ -55,7 +60,7 @@ Real gegenbauer(unsigned n, Real lambda, Real x)
 
 
 template<typename Real>
-Real gegenbauer_derivative(unsigned n, Real lambda, Real x, unsigned k)
+BOOST_MATH_GPU_ENABLED Real gegenbauer_derivative(unsigned n, Real lambda, Real x, unsigned k)
 {
     if (k > n) {
         return Real(0);
@@ -70,7 +75,7 @@ Real gegenbauer_derivative(unsigned n, Real lambda, Real x, unsigned k)
 }
 
 template<typename Real>
-Real gegenbauer_prime(unsigned n, Real lambda, Real x) {
+BOOST_MATH_GPU_ENABLED Real gegenbauer_prime(unsigned n, Real lambda, Real x) {
     return gegenbauer_derivative<Real>(n, lambda, x, 1);
 }
 
diff --git a/include/boost/math/special_functions/hankel.hpp b/include/boost/math/special_functions/hankel.hpp
index 51b8390d99..730c7afa03 100644
--- a/include/boost/math/special_functions/hankel.hpp
+++ b/include/boost/math/special_functions/hankel.hpp
@@ -1,4 +1,5 @@
 // Copyright John Maddock 2012.
+// Copyright Matt Borland 2024.
 // Use, modification and distribution are subject to the
 // Boost Software License, Version 1.0.
 // (See accompanying file LICENSE_1_0.txt
@@ -7,26 +8,31 @@
 #ifndef BOOST_MATH_HANKEL_HPP
 #define BOOST_MATH_HANKEL_HPP
 
+#include <boost/math/tools/config.hpp>
+#include <boost/math/tools/complex.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/special_functions/bessel.hpp>
+#include <boost/math/special_functions/detail/iconv.hpp>
+#include <boost/math/constants/constants.hpp>
+#include <boost/math/policies/error_handling.hpp>
 
 namespace boost{ namespace math{
 
 namespace detail{
 
 template <class T, class Policy>
-std::complex<T> hankel_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol, int sign)
+BOOST_MATH_GPU_ENABLED boost::math::complex<T> hankel_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol, int sign)
 {
    BOOST_MATH_STD_USING
-   static const char* function = "boost::math::cyl_hankel_1<%1%>(%1%,%1%)";
+   constexpr auto function = "boost::math::cyl_hankel_1<%1%>(%1%,%1%)";
 
    if(x < 0)
    {
       bool isint_v = floor(v) == v;
       T j, y;
       bessel_jy(v, -x, &j, &y, need_j | need_y, pol);
-      std::complex<T> cx(x), cv(v);
-      std::complex<T> j_result, y_result;
+      boost::math::complex<T> cx(x), cv(v);
+      boost::math::complex<T> j_result, y_result;
       if(isint_v)
       {
          int s = (iround(v) & 1) ? -1 : 1;
@@ -37,12 +43,12 @@ std::complex<T> hankel_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol
       {
          j_result = pow(cx, v) * pow(-cx, -v) * j;
          T p1 = pow(-x, v);
-         std::complex<T> p2 = pow(cx, v);
+         boost::math::complex<T> p2 = pow(cx, v);
          y_result = p1 * y / p2
             + (p2 / p1 - p1 / p2) * j / tan(constants::pi<T>() * v);
       }
       // multiply y_result by i:
-      y_result = std::complex<T>(-sign * y_result.imag(), sign * y_result.real());
+      y_result = boost::math::complex<T>(-sign * y_result.imag(), sign * y_result.real());
       return j_result + y_result;
    }
 
@@ -51,25 +57,25 @@ std::complex<T> hankel_imp(T v, T x, const bessel_no_int_tag&, const Policy& pol
       if(v == 0)
       {
          // J is 1, Y is -INF
-         return std::complex<T>(1, sign * -policies::raise_overflow_error<T>(function, nullptr, pol));
+         return boost::math::complex<T>(1, sign * -policies::raise_overflow_error<T>(function, nullptr, pol));
       }
       else
       {
          // At least one of J and Y is complex infinity:
-         return std::complex<T>(policies::raise_overflow_error<T>(function, nullptr, pol), sign * policies::raise_overflow_error<T>(function, nullptr, pol));
+         return boost::math::complex<T>(policies::raise_overflow_error<T>(function, nullptr, pol), sign * policies::raise_overflow_error<T>(function, nullptr, pol));
       }
    }
 
    T j, y;
    bessel_jy(v, x, &j, &y, need_j | need_y, pol);
-   return std::complex<T>(j, sign * y);
+   return boost::math::complex<T>(j, sign * y);
 }
 
 template <class T, class Policy>
-std::complex<T> hankel_imp(int v, T x, const bessel_int_tag&, const Policy& pol, int sign);
+BOOST_MATH_GPU_ENABLED boost::math::complex<T> hankel_imp(int v, T x, const bessel_int_tag&, const Policy& pol, int sign);
 
 template <class T, class Policy>
-inline std::complex<T> hankel_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol, int sign)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<T> hankel_imp(T v, T x, const bessel_maybe_int_tag&, const Policy& pol, int sign)
 {
    BOOST_MATH_STD_USING  // ADL of std names.
    int ival = detail::iconv(v, pol);
@@ -81,57 +87,57 @@ inline std::complex<T> hankel_imp(T v, T x, const bessel_maybe_int_tag&, const P
 }
 
 template <class T, class Policy>
-inline std::complex<T> hankel_imp(int v, T x, const bessel_int_tag&, const Policy& pol, int sign)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<T> hankel_imp(int v, T x, const bessel_int_tag&, const Policy& pol, int sign)
 {
    BOOST_MATH_STD_USING
-   if((std::abs(v) < 200) && (x > 0))
-      return std::complex<T>(bessel_jn(v, x, pol), sign * bessel_yn(v, x, pol));
+   if((abs(v) < 200) && (x > 0))
+      return boost::math::complex<T>(bessel_jn(v, x, pol), sign * bessel_yn(v, x, pol));
    return hankel_imp(static_cast<T>(v), x, bessel_no_int_tag(), pol, sign);
 }
 
 template <class T, class Policy>
-inline std::complex<T> sph_hankel_imp(T v, T x, const Policy& pol, int sign)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<T> sph_hankel_imp(T v, T x, const Policy& pol, int sign)
 {
    BOOST_MATH_STD_USING
-   return constants::root_half_pi<T>() * hankel_imp(v + 0.5f, x, bessel_no_int_tag(), pol, sign) / sqrt(std::complex<T>(x));
+   return constants::root_half_pi<T>() * hankel_imp(v + 0.5f, x, bessel_no_int_tag(), pol, sign) / sqrt(boost::math::complex<T>(x));
 }
 
 } // namespace detail
 
 template <class T1, class T2, class Policy>
-inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_1(T1 v, T2 x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_1(T1 v, T2 x, const Policy& pol)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
    typedef typename detail::bessel_traits<T1, T2, Policy>::optimisation_tag tag_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
-   return policies::checked_narrowing_cast<std::complex<result_type>, Policy>(detail::hankel_imp<value_type>(v, static_cast<value_type>(x), tag_type(), pol, 1), "boost::math::cyl_hankel_1<%1%>(%1%,%1%)");
+   return policies::checked_narrowing_cast<boost::math::complex<result_type>, Policy>(detail::hankel_imp<value_type>(v, static_cast<value_type>(x), tag_type(), pol, 1), "boost::math::cyl_hankel_1<%1%>(%1%,%1%)");
 }
 
 template <class T1, class T2>
-inline std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_1(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_1(T1 v, T2 x)
 {
    return cyl_hankel_1(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_2(T1 v, T2 x, const Policy& pol)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_2(T1 v, T2 x, const Policy& pol)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
    typedef typename detail::bessel_traits<T1, T2, Policy>::optimisation_tag tag_type;
    typedef typename policies::evaluation<result_type, Policy>::type value_type;
-   return policies::checked_narrowing_cast<std::complex<result_type>, Policy>(detail::hankel_imp<value_type>(v, static_cast<value_type>(x), tag_type(), pol, -1), "boost::math::cyl_hankel_1<%1%>(%1%,%1%)");
+   return policies::checked_narrowing_cast<boost::math::complex<result_type>, Policy>(detail::hankel_imp<value_type>(v, static_cast<value_type>(x), tag_type(), pol, -1), "boost::math::cyl_hankel_1<%1%>(%1%,%1%)");
 }
 
 template <class T1, class T2>
-inline std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_2(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_2(T1 v, T2 x)
 {
    return cyl_hankel_2(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_1(T1 v, T2 x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_1(T1 v, T2 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -143,17 +149,17 @@ inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type>
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   return policies::checked_narrowing_cast<std::complex<result_type>, Policy>(detail::sph_hankel_imp<value_type>(static_cast<value_type>(v), static_cast<value_type>(x), forwarding_policy(), 1), "boost::math::sph_hankel_1<%1%>(%1%,%1%)");
+   return policies::checked_narrowing_cast<boost::math::complex<result_type>, Policy>(detail::sph_hankel_imp<value_type>(static_cast<value_type>(v), static_cast<value_type>(x), forwarding_policy(), 1), "boost::math::sph_hankel_1<%1%>(%1%,%1%)");
 }
 
 template <class T1, class T2>
-inline std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_1(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_1(T1 v, T2 x)
 {
    return sph_hankel_1(v, x, policies::policy<>());
 }
 
 template <class T1, class T2, class Policy>
-inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_2(T1 v, T2 x, const Policy&)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_2(T1 v, T2 x, const Policy&)
 {
    BOOST_FPU_EXCEPTION_GUARD
    typedef typename detail::bessel_traits<T1, T2, Policy>::result_type result_type;
@@ -165,11 +171,11 @@ inline std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type>
       policies::discrete_quantile<>,
       policies::assert_undefined<> >::type forwarding_policy;
 
-   return policies::checked_narrowing_cast<std::complex<result_type>, Policy>(detail::sph_hankel_imp<value_type>(static_cast<value_type>(v), static_cast<value_type>(x), forwarding_policy(), -1), "boost::math::sph_hankel_1<%1%>(%1%,%1%)");
+   return policies::checked_narrowing_cast<boost::math::complex<result_type>, Policy>(detail::sph_hankel_imp<value_type>(static_cast<value_type>(v), static_cast<value_type>(x), forwarding_policy(), -1), "boost::math::sph_hankel_1<%1%>(%1%,%1%)");
 }
 
 template <class T1, class T2>
-inline std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_2(T1 v, T2 x)
+BOOST_MATH_GPU_ENABLED inline boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_2(T1 v, T2 x)
 {
    return sph_hankel_2(v, x, policies::policy<>());
 }
diff --git a/include/boost/math/special_functions/hermite.hpp b/include/boost/math/special_functions/hermite.hpp
index 81ccb2ac66..3d77fc03e3 100644
--- a/include/boost/math/special_functions/hermite.hpp
+++ b/include/boost/math/special_functions/hermite.hpp
@@ -1,5 +1,6 @@
 
 //  (C) Copyright John Maddock 2006.
+//  (C) Copyright Matt Borland 2024.
 //  Use, modification and distribution are subject to the
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -11,8 +12,9 @@
 #pragma once
 #endif
 
-#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/tools/config.hpp>
+#include <boost/math/tools/promotion.hpp>
+#include <boost/math/special_functions/math_fwd.hpp>
 #include <boost/math/policies/error_handling.hpp>
 
 namespace boost{
@@ -20,7 +22,7 @@ namespace math{
 
 // Recurrence relation for Hermite polynomials:
 template <class T1, class T2, class T3>
-inline typename tools::promote_args<T1, T2, T3>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T1, T2, T3>::type 
    hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1)
 {
    using promoted_type = tools::promote_args_t<T1, T2, T3>;
@@ -31,7 +33,7 @@ namespace detail{
 
 // Implement Hermite polynomials via recurrence:
 template <class T>
-T hermite_imp(unsigned n, T x)
+BOOST_MATH_GPU_ENABLED T hermite_imp(unsigned n, T x)
 {
    T p0 = 1;
    T p1 = 2 * x;
@@ -43,7 +45,7 @@ T hermite_imp(unsigned n, T x)
 
    while(c < n)
    {
-      std::swap(p0, p1);
+      BOOST_MATH_GPU_SAFE_SWAP(p0, p1);
       p1 = static_cast<T>(hermite_next(c, x, p0, p1));
       ++c;
    }
@@ -53,7 +55,7 @@ T hermite_imp(unsigned n, T x)
 } // namespace detail
 
 template <class T, class Policy>
-inline typename tools::promote_args<T>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type 
    hermite(unsigned n, T x, const Policy&)
 {
    typedef typename tools::promote_args<T>::type result_type;
@@ -62,7 +64,7 @@ inline typename tools::promote_args<T>::type
 }
 
 template <class T>
-inline typename tools::promote_args<T>::type 
+BOOST_MATH_GPU_ENABLED inline typename tools::promote_args<T>::type 
    hermite(unsigned n, T x)
 {
    return boost::math::hermite(n, x, policies::policy<>());
diff --git a/include/boost/math/special_functions/math_fwd.hpp b/include/boost/math/special_functions/math_fwd.hpp
index 35f8dd1bb9..91dde74ccc 100644
--- a/include/boost/math/special_functions/math_fwd.hpp
+++ b/include/boost/math/special_functions/math_fwd.hpp
@@ -27,6 +27,7 @@
 #include <boost/math/tools/config.hpp>
 #include <boost/math/tools/promotion.hpp> // for argument promotion.
 #include <boost/math/tools/type_traits.hpp>
+#include <boost/math/tools/complex.hpp>
 #include <boost/math/policies/policy.hpp>
 
 #ifdef BOOST_MATH_HAS_NVRTC
@@ -50,7 +51,53 @@ namespace detail{
       >::type;
    };
 
-   } // namespace detail
+   template <class T, class U>
+   struct expint_result
+   {
+      using type = typename boost::math::conditional<
+         policies::is_policy<U>::value,
+         tools::promote_args_t<T>,
+         typename tools::promote_args<U>::type
+      >::type;
+   };
+
+   typedef boost::math::integral_constant<int, 0> bessel_no_int_tag;      // No integer optimisation possible.
+   typedef boost::math::integral_constant<int, 1> bessel_maybe_int_tag;   // Maybe integer optimisation.
+   typedef boost::math::integral_constant<int, 2> bessel_int_tag;         // Definite integer optimisation.
+
+   template <class T1, class T2, class Policy>
+   struct bessel_traits
+   {
+      using result_type = typename boost::math::conditional<
+         boost::math::is_integral<T1>::value,
+         typename tools::promote_args<T2>::type,
+         tools::promote_args_t<T1, T2>
+      >::type;
+
+      typedef typename policies::precision<result_type, Policy>::type precision_type;
+
+      using optimisation_tag = typename boost::math::conditional<
+         (precision_type::value <= 0 || precision_type::value > 64),
+         bessel_no_int_tag,
+         typename boost::math::conditional<
+            boost::math::is_integral<T1>::value,
+            bessel_int_tag,
+            bessel_maybe_int_tag
+         >::type
+      >::type;
+
+      using optimisation_tag128 = typename boost::math::conditional<
+         (precision_type::value <= 0 || precision_type::value > 113),
+         bessel_no_int_tag,
+         typename boost::math::conditional<
+            boost::math::is_integral<T1>::value,
+            bessel_int_tag,
+            bessel_maybe_int_tag
+         >::type
+      >::type;
+   };
+
+} // namespace detail
 
 } // namespace math
 } // namespace boost
@@ -284,15 +331,15 @@ namespace boost
       laguerre(unsigned n, T1 m, T2 x);
 
    template <class T>
-   tools::promote_args_t<T>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T>
       hermite(unsigned n, T x);
 
    template <class T, class Policy>
-   tools::promote_args_t<T>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T>
       hermite(unsigned n, T x, const Policy& pol);
 
    template <class T1, class T2, class T3>
-   tools::promote_args_t<T1, T2, T3>
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T1, T2, T3>
       hermite_next(unsigned n, T1 x, T2 Hn, T3 Hnm1);
 
    template<class T1, class T2, class T3>
@@ -808,28 +855,28 @@ namespace boost
                          const Policy&);
 
    template <class T1, class T2>
-   std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_1(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_1(T1 v, T2 x);
 
    template <class T1, class T2, class Policy>
-   std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_1(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_1(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2, class Policy>
-   std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_2(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> cyl_hankel_2(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_2(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> cyl_hankel_2(T1 v, T2 x);
 
    template <class T1, class T2, class Policy>
-   std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_1(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_1(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_1(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_1(T1 v, T2 x);
 
    template <class T1, class T2, class Policy>
-   std::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_2(T1 v, T2 x, const Policy& pol);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, Policy>::result_type> sph_hankel_2(T1 v, T2 x, const Policy& pol);
 
    template <class T1, class T2>
-   std::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_2(T1 v, T2 x);
+   BOOST_MATH_GPU_ENABLED boost::math::complex<typename detail::bessel_traits<T1, T2, policies::policy<> >::result_type> sph_hankel_2(T1 v, T2 x);
 
    template <class T, class Policy>
    BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> airy_ai(T x, const Policy&);
@@ -936,7 +983,7 @@ namespace boost
    template <class T, class U>
    struct expint_result
    {
-      typedef typename std::conditional<
+      typedef typename boost::math::conditional<
          policies::is_policy<U>::value,
          tools::promote_args_t<T>,
          typename tools::promote_args<U>::type
@@ -946,13 +993,13 @@ namespace boost
    } // namespace detail
 
    template <class T, class Policy>
-   tools::promote_args_t<T> expint(unsigned n, T z, const Policy&);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> expint(unsigned n, T z, const Policy&);
 
    template <class T, class U>
-   typename detail::expint_result<T, U>::type expint(T const z, U const u);
+   BOOST_MATH_GPU_ENABLED typename detail::expint_result<T, U>::type expint(T const z, U const u);
 
    template <class T>
-   tools::promote_args_t<T> expint(T z);
+   BOOST_MATH_GPU_ENABLED tools::promote_args_t<T> expint(T z);
 
    // Zeta:
    template <class T, class Policy>
@@ -1346,7 +1393,7 @@ namespace boost
    laguerre(unsigned n, T1 m, T2 x) { return ::boost::math::laguerre(n, m, x, Policy()); }\
 \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> \
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> \
    hermite(unsigned n, T x){ return ::boost::math::hermite(n, x, Policy()); }\
 \
    using boost::math::hermite_next;\
@@ -1620,11 +1667,11 @@ template <class OutputIterator, class T>\
    using boost::math::changesign;\
    \
    template <class T, class U>\
-   inline typename boost::math::tools::promote_args_t<T,U> expint(T const& z, U const& u)\
+   BOOST_MATH_GPU_ENABLED inline typename boost::math::tools::promote_args_t<T,U> expint(T const& z, U const& u)\
    { return boost::math::expint(z, u, Policy()); }\
    \
    template <class T>\
-   inline boost::math::tools::promote_args_t<T> expint(T z){ return boost::math::expint(z, Policy()); }\
+   BOOST_MATH_GPU_ENABLED inline boost::math::tools::promote_args_t<T> expint(T z){ return boost::math::expint(z, Policy()); }\
    \
    template <class T>\
    inline boost::math::tools::promote_args_t<T> zeta(T s){ return boost::math::zeta(s, Policy()); }\
@@ -1669,19 +1716,19 @@ template <class OutputIterator, class T>\
    inline boost::math::tools::promote_args_t<RT1, RT2> owens_t(RT1 a, RT2 z){ return boost::math::owens_t(a, z, Policy()); }\
    \
    template <class T1, class T2>\
-   inline std::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> cyl_hankel_1(T1 v, T2 x)\
+   inline BOOST_MATH_GPU_ENABLED boost::math::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> cyl_hankel_1(T1 v, T2 x)\
    {  return boost::math::cyl_hankel_1(v, x, Policy()); }\
    \
    template <class T1, class T2>\
-   inline std::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> cyl_hankel_2(T1 v, T2 x)\
+   inline BOOST_MATH_GPU_ENABLED boost::math::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> cyl_hankel_2(T1 v, T2 x)\
    { return boost::math::cyl_hankel_2(v, x, Policy()); }\
    \
    template <class T1, class T2>\
-   inline std::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> sph_hankel_1(T1 v, T2 x)\
+   inline BOOST_MATH_GPU_ENABLED boost::math::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> sph_hankel_1(T1 v, T2 x)\
    { return boost::math::sph_hankel_1(v, x, Policy()); }\
    \
    template <class T1, class T2>\
-   inline std::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> sph_hankel_2(T1 v, T2 x)\
+   inline BOOST_MATH_GPU_ENABLED boost::math::complex<typename boost::math::detail::bessel_traits<T1, T2, Policy >::result_type> sph_hankel_2(T1 v, T2 x)\
    { return boost::math::sph_hankel_2(v, x, Policy()); }\
    \
    template <class T>\
diff --git a/include/boost/math/tools/complex.hpp b/include/boost/math/tools/complex.hpp
index f93d2958d1..88db8e8a76 100644
--- a/include/boost/math/tools/complex.hpp
+++ b/include/boost/math/tools/complex.hpp
@@ -14,11 +14,93 @@
 #include <boost/math/tools/is_detected.hpp>
 
 #ifdef BOOST_MATH_ENABLE_CUDA
+
 #include <cuda/std/utility>
-#endif
+#include <cuda/std/complex>
+
+namespace boost {
+namespace math {
+
+template <typename T>
+using complex = cuda::std::complex<T>;
+
+using cuda::std::real;
+using cuda::std::imag;
+using cuda::std::abs;
+using cuda::std::arg;
+using cuda::std::norm;
+using cuda::std::conj;
+using cuda::std::proj;
+using cuda::std::polar;
+
+using cuda::std::exp;
+using cuda::std::log;
+using cuda::std::log10;
+
+using cuda::std::pow;
+using cuda::std::sqrt;
+
+using cuda::std::sin;
+using cuda::std::cos;
+using cuda::std::tan;
+using cuda::std::asin;
+using cuda::std::acos;
+using cuda::std::atan;
+
+using cuda::std::sinh;
+using cuda::std::cosh;
+using cuda::std::tanh;
+using cuda::std::asinh;
+using cuda::std::acosh;
+using cuda::std::atanh;
+
+} // namespace math
+} // namespace boost
+
+#else
 
-#ifndef BOOST_MATH_HAS_NVRTC
 #include <utility>
+#include <complex>
+
+namespace boost {
+namespace math {
+
+template <typename T>
+using complex = std::complex<T>;
+
+using std::real;
+using std::imag;
+using std::abs;
+using std::arg;
+using std::norm;
+using std::conj;
+using std::proj;
+using std::polar;
+
+using std::exp;
+using std::log;
+using std::log10;
+
+using std::pow;
+using std::sqrt;
+
+using std::sin;
+using std::cos;
+using std::tan;
+using std::asin;
+using std::acos;
+using std::atan;
+
+using std::sinh;
+using std::cosh;
+using std::tanh;
+using std::asinh;
+using std::acosh;
+using std::atanh;
+
+} // namespace math
+} // namespace boost
+
 #endif
 
 namespace boost {
diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 99bc4ee27e..b3a8c2cf89 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -678,6 +678,7 @@ namespace boost{ namespace math{
 #include <cuda/std/cstdint>
 #include <cuda/std/array>
 #include <cuda/std/tuple>
+#include <cuda/std/complex>
 
 #  define BOOST_MATH_CUDA_ENABLED __host__ __device__
 #  define BOOST_MATH_HAS_GPU_SUPPORT
diff --git a/test/cuda_jamfile b/test/cuda_jamfile
index 0ba47dace3..02dcea8382 100644
--- a/test/cuda_jamfile
+++ b/test/cuda_jamfile
@@ -304,6 +304,14 @@ run test_cyl_neumann_double.cu ;
 run test_cyl_neumann_float.cu ;
 run test_sph_neumann_double.cu ;
 run test_sph_neumann_float.cu ;
+run test_cyl_hankel_1_double.cu ;
+run test_cyl_hankel_1_float.cu ;
+run test_cyl_hankel_2_double.cu ;
+run test_cyl_hankel_2_float.cu ;
+run test_sph_hankel_1_double.cu ;
+run test_sph_hankel_1_float.cu ;
+run test_sph_hankel_2_double.cu ;
+run test_sph_hankel_2_float.cu ;
 
 run test_cbrt_double.cu ;
 run test_cbrt_float.cu ;
@@ -339,9 +347,18 @@ run test_erfc_float.cu ;
 run test_erfc_inv_double.cu ;
 run test_erfc_inv_float.cu ;
 
+run test_expint_double.cu ;
+run test_expint_float.cu ;
+
 run test_expm1_double.cu ;
 run test_expm1_float.cu ;
 
+run test_gegenbauer_double.cu ;
+run test_gegenbauer_float.cu ;
+
+run test_hermite_double.cu ;
+run test_hermite_float.cu ;
+
 run test_lgamma_double.cu ;
 run test_lgamma_float.cu ;
 run test_tgamma_double.cu ;
diff --git a/test/nvrtc_jamfile b/test/nvrtc_jamfile
index eb5da37c83..e049a24d2b 100644
--- a/test/nvrtc_jamfile
+++ b/test/nvrtc_jamfile
@@ -9,9 +9,6 @@ project : requirements
     [ requires cxx14_decltype_auto cxx14_generic_lambdas cxx14_return_type_deduction cxx14_variable_templates cxx14_constexpr ]
     ;
 
-run test_heumann_lambda_nvrtc_double.cpp ;
-run test_heumann_lambda_nvrtc_float.cpp ;
-
 # Quad
 run test_exp_sinh_quad_nvrtc_float.cpp ;
 run test_exp_sinh_quad_nvrtc_double.cpp ;
@@ -306,6 +303,14 @@ run test_cyl_neumann_nvrtc_double.cpp ;
 run test_cyl_neumann_nvrtc_float.cpp ;
 run test_sph_neumann_nvrtc_double.cpp ;
 run test_sph_neumann_nvrtc_float.cpp ;
+run test_cyl_hankel_1_nvrtc_double.cpp ;
+run test_cyl_hankel_1_nvrtc_float.cpp ;
+run test_cyl_hankel_2_nvrtc_double.cpp ;
+run test_cyl_hankel_2_nvrtc_float.cpp ;
+run test_sph_hankel_1_nvrtc_double.cpp ;
+run test_sph_hankel_1_nvrtc_float.cpp ;
+run test_sph_hankel_2_nvrtc_double.cpp ;
+run test_sph_hankel_2_nvrtc_float.cpp ;
 
 run test_cbrt_nvrtc_double.cpp ;
 run test_cbrt_nvrtc_float.cpp ;
@@ -335,6 +340,11 @@ run test_ellint_d_nvrtc_double.cpp ;
 run test_ellint_d_nvrtc_float.cpp ;
 run test_jacobi_zeta_nvrtc_double.cpp ;
 run test_jacobi_zeta_nvrtc_float.cpp ;
+run test_heumann_lambda_nvrtc_double.cpp ;
+run test_heumann_lambda_nvrtc_float.cpp ;
+
+run test_expint_nvrtc_double.cpp ;
+run test_expint_nvrtc_float.cpp ;
 
 run test_expm1_nvrtc_double.cpp ;
 run test_expm1_nvrtc_float.cpp ;
@@ -351,6 +361,12 @@ run test_gamma_p_inv_nvrtc_float.cpp ;
 run test_tgamma_ratio_nvrtc_double.cpp ;
 run test_tgamma_ratio_nvrtc_float.cpp ;
 
+run test_gegenbauer_nvrtc_double.cpp ;
+run test_gegenbauer_nvrtc_float.cpp ;
+
+run test_hermite_nvrtc_double.cpp ;
+run test_hermite_nvrtc_float.cpp ;
+
 run test_log1p_nvrtc_double.cpp ;
 run test_log1p_nvrtc_float.cpp ;
 
diff --git a/test/sycl_jamfile b/test/sycl_jamfile
index ff6d84fde5..582eaea407 100644
--- a/test/sycl_jamfile
+++ b/test/sycl_jamfile
@@ -71,8 +71,14 @@ run test_sign.cpp ;
 
 run test_round.cpp ;
 
+run test_expint.cpp ;
+
 run test_expm1_simple.cpp ;
 
+run gegenbauer_test.cpp ;
+
+run test_hankel.cpp ;
+
 run test_log1p_simple.cpp ;
 
 run test_digamma_simple.cpp ;
@@ -85,3 +91,5 @@ run test_gamma.cpp ;
 run test_igamma.cpp ;
 run test_igamma_inv.cpp ;
 run test_igamma_inva.cpp ;
+
+run test_hermite.cpp ;
diff --git a/test/test_cyl_hankel_1_double.cu b/test/test_cyl_hankel_1_double.cu
new file mode 100644
index 0000000000..1349469341
--- /dev/null
+++ b/test/test_cyl_hankel_1_double.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_1(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::cyl_hankel_1(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_hankel_1_float.cu b/test/test_cyl_hankel_1_float.cu
new file mode 100644
index 0000000000..da78c375c6
--- /dev/null
+++ b/test/test_cyl_hankel_1_float.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_1(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::cyl_hankel_1(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_hankel_1_nvrtc_double.cpp b/test/test_cyl_hankel_1_nvrtc_double.cpp
new file mode 100644
index 0000000000..298436d063
--- /dev/null
+++ b/test/test_cyl_hankel_1_nvrtc_double.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_cyl_hankel_1_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_1(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_hankel_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_hankel_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_hankel_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_hankel_1(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_hankel_1_nvrtc_float.cpp b/test/test_cyl_hankel_1_nvrtc_float.cpp
new file mode 100644
index 0000000000..d505c7bc4c
--- /dev/null
+++ b/test/test_cyl_hankel_1_nvrtc_float.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_cyl_hankel_1_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_1(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_hankel_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_hankel_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_hankel_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_hankel_1(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_hankel_2_double.cu b/test/test_cyl_hankel_2_double.cu
new file mode 100644
index 0000000000..55b643173a
--- /dev/null
+++ b/test/test_cyl_hankel_2_double.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_2(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::cyl_hankel_2(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_hankel_2_float.cu b/test/test_cyl_hankel_2_float.cu
new file mode 100644
index 0000000000..5766ebeb48
--- /dev/null
+++ b/test/test_cyl_hankel_2_float.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_2(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::cyl_hankel_2(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_cyl_hankel_2_nvrtc_double.cpp b/test/test_cyl_hankel_2_nvrtc_double.cpp
new file mode 100644
index 0000000000..f7589d2016
--- /dev/null
+++ b/test/test_cyl_hankel_2_nvrtc_double.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_cyl_hankel_2_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_2(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_hankel_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_hankel_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_hankel_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_hankel_2(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_cyl_hankel_2_nvrtc_float.cpp b/test/test_cyl_hankel_2_nvrtc_float.cpp
new file mode 100644
index 0000000000..54216d39c9
--- /dev/null
+++ b/test/test_cyl_hankel_2_nvrtc_float.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_cyl_hankel_2_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::cyl_hankel_2(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_cyl_hankel_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_cyl_hankel_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_cyl_hankel_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::cyl_hankel_2(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_expint.cpp b/test/test_expint.cpp
index 3f44a80915..3eede5e389 100644
--- a/test/test_expint.cpp
+++ b/test/test_expint.cpp
@@ -3,7 +3,14 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
+
+#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#endif
+
 #include "test_expint.hpp"
 
 //
@@ -78,7 +85,11 @@ void expected_results()
       ".*",                          // platform
       "float|double|long double",    // test type(s)
       ".*Ei.*",                      // test data group
+      #ifndef SYCL_LANGUAGE_VERSION
       ".*", 6, 3);                   // test function
+      #else
+      ".*", 10, 3);
+      #endif
    if(std::numeric_limits<long double>::digits > 100)
    {
       add_expected_result(
diff --git a/test/test_expint.hpp b/test/test_expint.hpp
index 491db2fcdc..d6524810e4 100644
--- a/test/test_expint.hpp
+++ b/test/test_expint.hpp
@@ -4,13 +4,19 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/expint.hpp>
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/tools/stats.hpp>
-#include <boost/math/tools/test.hpp>
+#include "../include_private/boost/math/tools/test.hpp"
 #include <boost/math/constants/constants.hpp>
 #include <boost/type_traits/is_floating_point.hpp>
 #include <boost/array.hpp>
diff --git a/test/test_expint_double.cu b/test/test_expint_double.cu
new file mode 100644
index 0000000000..d82e90a937
--- /dev/null
+++ b/test/test_expint_double.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::expint(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = dist(rng);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::expint(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                return EXIT_FAILURE;
+            }
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_expint_float.cu b/test/test_expint_float.cu
new file mode 100644
index 0000000000..dd1fccd1d7
--- /dev/null
+++ b/test/test_expint_float.cu
@@ -0,0 +1,106 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::expint(in[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    std::mt19937_64 rng(42);
+    std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector[i] = dist(rng);
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch vectorAdd kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::expint(input_vector[i]));
+    double t = w.elapsed();
+    // check the results
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 300)
+            {
+                std::cerr << "Result verification failed at element " << i << "!" << std::endl;
+                return EXIT_FAILURE;
+            }
+        }
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_expint_nvrtc_double.cpp b/test/test_expint_nvrtc_double.cpp
new file mode 100644
index 0000000000..3ab45e6a1a
--- /dev/null
+++ b/test/test_expint_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/expint.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/expint.hpp>
+extern "C" __global__ 
+void test_expint_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::expint(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expint_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expint_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expint_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::expint(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_expint_nvrtc_float.cpp b/test/test_expint_nvrtc_float.cpp
new file mode 100644
index 0000000000..bff58580eb
--- /dev/null
+++ b/test/test_expint_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/expint.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/expint.hpp>
+extern "C" __global__ 
+void test_expint_kernel(const float_type *in1, const float_type*, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::expint(in1[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_expint_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_expint_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_expint_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::expint(h_in1[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gegenbauer_double.cu b/test/test_gegenbauer_double.cu
new file mode 100644
index 0000000000..21278d7a82
--- /dev/null
+++ b/test/test_gegenbauer_double.cu
@@ -0,0 +1,125 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+//  Gegenbauer prime uses all methods internally so it's the easy choice
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/special_functions/gegenbauer.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gegenbauer_prime(2, in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::gegenbauer_prime(2, input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+            // Most elements are under 50 but extremely small numbers very more greatly
+            if (eps > 1000)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i]
+                          << "\n  Host: " << results[i]
+                          << "\n   Eps: " << eps << std::endl;
+                ++failure_counter;
+                if (failure_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gegenbauer_float.cu b/test/test_gegenbauer_float.cu
new file mode 100644
index 0000000000..b7affaecd4
--- /dev/null
+++ b/test/test_gegenbauer_float.cu
@@ -0,0 +1,124 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+//
+//  Gegenbauer prime uses all methods internally so it's the easy choice
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include <boost/math/special_functions/gegenbauer.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::gegenbauer_prime(2, in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::gegenbauer_prime(2, input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            const auto eps = boost::math::epsilon_difference(output_vector[i], results[i]);
+            if (eps > 1000)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i]
+                          << "\n  Host: " << results[i]
+                          << "\n   Eps: " << eps << std::endl;
+                ++failure_counter;
+                if (failure_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_gegenbauer_nvrtc_double.cpp b/test/test_gegenbauer_nvrtc_double.cpp
new file mode 100644
index 0000000000..0c8416cb61
--- /dev/null
+++ b/test/test_gegenbauer_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gegenbauer.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gegenbauer.hpp>
+extern "C" __global__ 
+void test_gegenbauer_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gegenbauer(2, in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gegenbauer_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gegenbauer_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gegenbauer_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gegenbauer(2, h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_gegenbauer_nvrtc_float.cpp b/test/test_gegenbauer_nvrtc_float.cpp
new file mode 100644
index 0000000000..c0d3484175
--- /dev/null
+++ b/test/test_gegenbauer_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/gegenbauer.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/gegenbauer.hpp>
+extern "C" __global__ 
+void test_gegenbauer_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::gegenbauer(2, in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_gegenbauer_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_gegenbauer_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_gegenbauer_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::gegenbauer(2, h_in1[i], h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_hankel.cpp b/test/test_hankel.cpp
index f8bd173da8..a93e90c4d1 100644
--- a/test/test_hankel.cpp
+++ b/test/test_hankel.cpp
@@ -3,9 +3,13 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
+#endif
 
 #define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#include <boost/math/tools/config.hpp>
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
@@ -85,6 +89,7 @@ void test_hankel(T, const char* name)
 //
 // Instantiate a few instances to check our error handling code can cope with std::complex:
 //
+#ifndef SYCL_LANGUAGE_VERSION
 typedef boost::math::policies::policy<
    boost::math::policies::overflow_error<boost::math::policies::throw_on_error>,
    boost::math::policies::denorm_error<boost::math::policies::throw_on_error>,
@@ -120,7 +125,7 @@ typedef boost::math::policies::policy<
    boost::math::policies::indeterminate_result_error<boost::math::policies::ignore_error> > pol3;
 
 template std::complex<double> boost::math::cyl_hankel_1<double, double, pol3>(double, double, const pol3&);
-
+#endif
 
 BOOST_AUTO_TEST_CASE( test_main )
 {
diff --git a/test/test_hermite.cpp b/test/test_hermite.cpp
index d1127feec2..c7dd8b8c40 100644
--- a/test/test_hermite.cpp
+++ b/test/test_hermite.cpp
@@ -5,8 +5,11 @@
 //  Boost Software License, Version 1.0. (See accompanying file
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
+#ifndef SYCL_LANGUAGE_VERSION
 #include <pch_light.hpp>
-#include"test_hermite.hpp"
+#endif
+
+#include "test_hermite.hpp"
 
 //
 // DESCRIPTION:
diff --git a/test/test_hermite.hpp b/test/test_hermite.hpp
index 0b00677eec..8f7c55ff10 100644
--- a/test/test_hermite.hpp
+++ b/test/test_hermite.hpp
@@ -11,11 +11,17 @@
 // Constants are too big for float case, but this doesn't matter for test.
 #endif
 
+#include <boost/math/tools/config.hpp>
+
+#ifndef BOOST_MATH_NO_REAL_CONCEPT_TESTS
 #include <boost/math/concepts/real_concept.hpp>
+#endif
+
 #define BOOST_TEST_MAIN
 #include <boost/test/unit_test.hpp>
 #include <boost/test/tools/floating_point_comparison.hpp>
 #include <boost/math/special_functions/math_fwd.hpp>
+#include <boost/math/special_functions/hermite.hpp>
 #include <boost/math/constants/constants.hpp>
 #include <boost/array.hpp>
 #include "functor.hpp"
diff --git a/test/test_hermite_double.cu b/test/test_hermite_double.cu
new file mode 100644
index 0000000000..a53766171a
--- /dev/null
+++ b/test/test_hermite_double.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::hermite(1U, in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::hermite(1U, input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 1000)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_hermite_float.cu b/test/test_hermite_float.cu
new file mode 100644
index 0000000000..c48560bbe5
--- /dev/null
+++ b/test/test_hermite_float.cu
@@ -0,0 +1,120 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, float_type *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::hermite(1U, in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<float_type> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<float_type> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results.push_back(boost::math::hermite(1U, input_vector2[i]));
+    double t = w.elapsed();
+    // check the results
+    int fail_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        if (std::isfinite(results[i]))
+        {
+            if (boost::math::epsilon_difference(output_vector[i], results[i]) > 1000)
+            {
+                std::cerr << "Result verification failed at element " << i << "!\n"
+                          << "Device: " << output_vector[i] << '\n'
+                          << "  Host: " << results[i] << '\n'
+                          << "   Eps: " << boost::math::epsilon_difference(output_vector[i], results[i]) << std::endl;
+                fail_counter++;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+    }
+
+    if (fail_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_hermite_nvrtc_double.cpp b/test/test_hermite_nvrtc_double.cpp
new file mode 100644
index 0000000000..569d975cb6
--- /dev/null
+++ b/test/test_hermite_nvrtc_double.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/hermite.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hermite.hpp>
+extern "C" __global__ 
+void test_hermite_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::hermite(1U, in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_hermite_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_hermite_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_hermite_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::hermite(1U, h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_hermite_nvrtc_float.cpp b/test/test_hermite_nvrtc_float.cpp
new file mode 100644
index 0000000000..e2e907c519
--- /dev/null
+++ b/test/test_hermite_nvrtc_float.cpp
@@ -0,0 +1,190 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/special_functions/hermite.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hermite.hpp>
+extern "C" __global__ 
+void test_hermite_kernel(const float_type *in1, const float_type* in2, float_type *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::hermite(1U, in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_hermite_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_hermite_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_hermite_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2, *h_out;
+        float_type *d_in1, *d_in2, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new float_type[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(float_type)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(float_type), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::hermite(1U, h_in2[i]);
+            
+            if (std::isfinite(res))
+            {
+                if (boost::math::epsilon_difference(res, h_out[i]) > 300)
+                {
+                    std::cout << "error at line: " << i
+                            << "\nParallel: " << h_out[i]
+                            << "\n  Serial: " << res
+                            << "\n    Dist: " << boost::math::epsilon_difference(res, h_out[i]) << std::endl;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_hankel_1_double.cu b/test/test_sph_hankel_1_double.cu
new file mode 100644
index 0000000000..ea9ec23063
--- /dev/null
+++ b/test/test_sph_hankel_1_double.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_1(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::sph_hankel_1(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_hankel_1_float.cu b/test/test_sph_hankel_1_float.cu
new file mode 100644
index 0000000000..4b01fe02a5
--- /dev/null
+++ b/test/test_sph_hankel_1_float.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_1(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::sph_hankel_1(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_hankel_1_nvrtc_double.cpp b/test/test_sph_hankel_1_nvrtc_double.cpp
new file mode 100644
index 0000000000..3ff1da8b20
--- /dev/null
+++ b/test/test_sph_hankel_1_nvrtc_double.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_sph_hankel_1_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_1(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_hankel_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_hankel_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_hankel_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_hankel_1(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_hankel_1_nvrtc_float.cpp b/test/test_sph_hankel_1_nvrtc_float.cpp
new file mode 100644
index 0000000000..0b07966537
--- /dev/null
+++ b/test/test_sph_hankel_1_nvrtc_float.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_sph_hankel_1_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_1(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_hankel_1_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_hankel_1_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_hankel_1_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_hankel_1(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_hankel_2_double.cu b/test/test_sph_hankel_2_double.cu
new file mode 100644
index 0000000000..6631f73a02
--- /dev/null
+++ b/test/test_sph_hankel_2_double.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef double float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_2(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::sph_hankel_2(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_hankel_2_float.cu b/test/test_sph_hankel_2_float.cu
new file mode 100644
index 0000000000..1910aef045
--- /dev/null
+++ b/test/test_sph_hankel_2_float.cu
@@ -0,0 +1,119 @@
+
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions.hpp>
+#include "cuda_managed_ptr.hpp"
+#include "stopwatch.hpp"
+
+// For the CUDA runtime routines (prefixed with "cuda_")
+#include <cuda_runtime.h>
+
+typedef float float_type;
+
+/**
+ * CUDA Kernel Device code
+ *
+ */
+__global__ void cuda_test(const float_type *in1, const float_type *in2, boost::math::complex<float_type> *out, int numElements)
+{
+    using std::cos;
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_2(in1[i], in2[i]);
+    }
+}
+
+/**
+ * Host main routine
+ */
+int main(void)
+{
+    // Error code to check return values for CUDA calls
+    cudaError_t err = cudaSuccess;
+
+    // Print the vector length to be used, and compute its size
+    int numElements = 50000;
+    std::cout << "[Vector operation on " << numElements << " elements]" << std::endl;
+
+    // Allocate the managed input vector A
+    cuda_managed_ptr<float_type> input_vector1(numElements);
+
+    // Allocate the managed input vector B
+    cuda_managed_ptr<float_type> input_vector2(numElements);
+
+    // Allocate the managed output vector C
+    cuda_managed_ptr<boost::math::complex<float_type>> output_vector(numElements);
+
+    // Initialize the input vectors
+    for (int i = 0; i < numElements; ++i)
+    {
+        input_vector1[i] = rand()/(float_type)RAND_MAX;
+        input_vector2[i] = rand()/(float_type)RAND_MAX;
+    }
+
+    // Launch the Vector Add CUDA Kernel
+    int threadsPerBlock = 256;
+    int blocksPerGrid =(numElements + threadsPerBlock - 1) / threadsPerBlock;
+    std::cout << "CUDA kernel launch with " << blocksPerGrid << " blocks of " << threadsPerBlock << " threads" << std::endl;
+
+    watch w;
+
+    cuda_test<<<blocksPerGrid, threadsPerBlock>>>(input_vector1.get(), input_vector2.get(), output_vector.get(), numElements);
+    cudaDeviceSynchronize();
+
+    std::cout << "CUDA kernal done in: " << w.elapsed() << "s" << std::endl;
+
+    err = cudaGetLastError();
+
+    if (err != cudaSuccess)
+    {
+        std::cerr << "Failed to launch CUDA kernel (error code " << cudaGetErrorString(err) << ")!" << std::endl;
+        return EXIT_FAILURE;
+    }
+
+    // Verify that the result vector is correct
+    std::vector<boost::math::complex<float_type>> results;
+    results.reserve(numElements);
+    w.reset();
+    for(int i = 0; i < numElements; ++i)
+       results[i] = boost::math::sph_hankel_2(input_vector1[i], input_vector2[i]);
+    double t = w.elapsed();
+    // check the results
+    int failure_counter = 0;
+    for(int i = 0; i < numElements; ++i)
+    {
+        const auto eps = boost::math::epsilon_difference(output_vector[i].real(), results[i].real());
+        if (eps > 10)
+        {
+            std::cerr << "Result verification failed at element " << i << "!\n"
+                        << "Device: " << output_vector[i].real() << ", " << output_vector[i].imag()
+                        << "\n  Host: " << results[i].real() << ", " << results[i].imag()
+                        << "\n   Eps: " << eps << std::endl;
+            ++failure_counter;
+            if (failure_counter > 100)
+            {
+                break;
+            }
+        }
+    }
+
+    if (failure_counter > 0)
+    {
+        return EXIT_FAILURE;
+    }
+
+    std::cout << "Test PASSED, normal calculation time: " << t << "s" << std::endl;
+    std::cout << "Done\n";
+
+    return 0;
+}
diff --git a/test/test_sph_hankel_2_nvrtc_double.cpp b/test/test_sph_hankel_2_nvrtc_double.cpp
new file mode 100644
index 0000000000..fa57fcbb16
--- /dev/null
+++ b/test/test_sph_hankel_2_nvrtc_double.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef double float_type;
+
+const char* cuda_kernel = R"(
+typedef double float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_sph_hankel_2_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_2(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_hankel_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_hankel_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_hankel_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_hankel_2(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}
diff --git a/test/test_sph_hankel_2_nvrtc_float.cpp b/test/test_sph_hankel_2_nvrtc_float.cpp
new file mode 100644
index 0000000000..be6fd0d097
--- /dev/null
+++ b/test/test_sph_hankel_2_nvrtc_float.cpp
@@ -0,0 +1,199 @@
+//  Copyright John Maddock 2016.
+//  Copyright Matt Borland 2024.
+//  Use, modification and distribution are subject to the
+//  Boost Software License, Version 1.0. (See accompanying file
+//  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#define BOOST_MATH_PROMOTE_DOUBLE_POLICY false
+
+// Must be included first
+#include <nvrtc.h>
+#include <cuda.h>
+#include <cuda_runtime.h>
+
+#include <iostream>
+#include <iomanip>
+#include <vector>
+#include <random>
+#include <exception>
+#include <boost/math/tools/complex.hpp>
+#include <boost/math/special_functions/hankel.hpp>
+#include <boost/math/special_functions/relative_difference.hpp>
+
+typedef float float_type;
+
+const char* cuda_kernel = R"(
+typedef float float_type;
+#include <cuda/std/type_traits>
+#include <boost/math/special_functions/hankel.hpp>
+extern "C" __global__ 
+void test_sph_hankel_2_kernel(const float_type *in1, const float_type* in2, boost::math::complex<float_type> *out, int numElements)
+{
+    int i = blockDim.x * blockIdx.x + threadIdx.x;
+    if (i < numElements)
+    {
+        out[i] = boost::math::sph_hankel_2(in1[i], in2[i]);
+    }
+}
+)";
+
+void checkCUDAError(cudaError_t result, const char* msg)
+{
+    if (result != cudaSuccess)
+    {
+        std::cerr << msg << ": " << cudaGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkCUError(CUresult result, const char* msg)
+{
+    if (result != CUDA_SUCCESS)
+    {
+        const char* errorStr;
+        cuGetErrorString(result, &errorStr);
+        std::cerr << msg << ": " << errorStr << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+void checkNVRTCError(nvrtcResult result, const char* msg)
+{
+    if (result != NVRTC_SUCCESS)
+    {
+        std::cerr << msg << ": " << nvrtcGetErrorString(result) << std::endl;
+        exit(EXIT_FAILURE);
+    }
+}
+
+int main() 
+{
+    try
+    {
+        // Initialize CUDA driver API
+        checkCUError(cuInit(0), "Failed to initialize CUDA");
+
+        // Create CUDA context
+        CUcontext context;
+        CUdevice device;
+        checkCUError(cuDeviceGet(&device, 0), "Failed to get CUDA device");
+        checkCUError(cuCtxCreate(&context, 0, device), "Failed to create CUDA context");
+
+        nvrtcProgram prog;
+        nvrtcResult res;
+
+        res = nvrtcCreateProgram(&prog, cuda_kernel, "test_sph_hankel_2_kernel.cu", 0, nullptr, nullptr);
+        checkNVRTCError(res, "Failed to create NVRTC program");
+
+        nvrtcAddNameExpression(prog, "test_sph_hankel_2_kernel");
+
+        #ifdef BOOST_MATH_NVRTC_CI_RUN
+        const char* opts[] = {"--std=c++14", "--gpu-architecture=compute_75", "--include-path=/home/runner/work/cuda-math/boost-root/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #else
+        const char* opts[] = {"--std=c++14", "--include-path=/home/mborland/Documents/boost/libs/cuda-math/include/", "-I/usr/local/cuda/include"};
+        #endif
+
+        // Compile the program
+        res = nvrtcCompileProgram(prog, sizeof(opts) / sizeof(const char*), opts);
+        if (res != NVRTC_SUCCESS) 
+        {
+            size_t log_size;
+            nvrtcGetProgramLogSize(prog, &log_size);
+            char* log = new char[log_size];
+            nvrtcGetProgramLog(prog, log);
+            std::cerr << "Compilation failed:\n" << log << std::endl;
+            delete[] log;
+            exit(EXIT_FAILURE);
+        }
+
+        // Get PTX from the program
+        size_t ptx_size;
+        nvrtcGetPTXSize(prog, &ptx_size);
+        char* ptx = new char[ptx_size];
+        nvrtcGetPTX(prog, ptx);
+
+        // Load PTX into CUDA module
+        CUmodule module;
+        CUfunction kernel;
+        checkCUError(cuModuleLoadDataEx(&module, ptx, 0, 0, 0), "Failed to load module");
+        checkCUError(cuModuleGetFunction(&kernel, module, "test_sph_hankel_2_kernel"), "Failed to get kernel function");
+
+        int numElements = 5000;
+        float_type *h_in1, *h_in2;
+        float_type *d_in1, *d_in2;
+        boost::math::complex<float_type> *h_out, *d_out;
+
+        // Allocate memory on the host
+        h_in1 = new float_type[numElements];
+        h_in2 = new float_type[numElements];
+        h_out = new boost::math::complex<float_type>[numElements];
+
+        // Initialize input arrays
+        std::mt19937_64 rng(42);
+        std::uniform_real_distribution<float_type> dist(0.0f, 1.0f);
+        for (int i = 0; i < numElements; ++i) 
+        {
+            h_in1[i] = static_cast<float_type>(dist(rng));
+            h_in2[i] = static_cast<float_type>(dist(rng));
+        }
+
+        checkCUDAError(cudaMalloc(&d_in1, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in1");
+        checkCUDAError(cudaMalloc(&d_in2, numElements * sizeof(float_type)), "Failed to allocate device memory for d_in2");
+        checkCUDAError(cudaMalloc(&d_out, numElements * sizeof(boost::math::complex<float_type>)), "Failed to allocate device memory for d_out");
+
+        checkCUDAError(cudaMemcpy(d_in1, h_in1, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in1");
+        checkCUDAError(cudaMemcpy(d_in2, h_in2, numElements * sizeof(float_type), cudaMemcpyHostToDevice), "Failed to copy data to device for d_in2");
+
+        int blockSize = 256;
+        int numBlocks = (numElements + blockSize - 1) / blockSize;
+        void* args[] = { &d_in1, &d_in2, &d_out, &numElements };
+        checkCUError(cuLaunchKernel(kernel, numBlocks, 1, 1, blockSize, 1, 1, 0, 0, args, 0), "Kernel launch failed");
+
+        checkCUDAError(cudaMemcpy(h_out, d_out, numElements * sizeof(boost::math::complex<float_type>), cudaMemcpyDeviceToHost), "Failed to copy data back to host for h_out");
+
+        // Verify Result
+        int fail_counter = 0;
+        for (int i = 0; i < numElements; ++i) 
+        {
+            const auto res = boost::math::sph_hankel_2(h_in1[i], h_in2[i]);
+            if (boost::math::epsilon_difference(res.real(), h_out[i].real()) > 300)
+            {
+                std::cout << "error at line: " << i
+                        << "\nParallel: " << h_out[i].real() << ", " << h_out[i].imag()
+                        << "\n  Serial: " << res.real() << ", " << res.imag()
+                        << "\n    Dist: " << boost::math::epsilon_difference(res.real(), h_out[i].real()) << std::endl;
+                ++fail_counter;
+                if (fail_counter > 100)
+                {
+                    break;
+                }
+            }
+        }
+
+        cudaFree(d_in1);
+        cudaFree(d_in2);
+        cudaFree(d_out);
+        delete[] h_in1;
+        delete[] h_in2;
+        delete[] h_out;
+
+        nvrtcDestroyProgram(&prog);
+        delete[] ptx;
+
+        cuCtxDestroy(context);
+
+        if (fail_counter > 0)
+        {
+            return 1;
+        }
+
+        std::cout << "Kernel executed successfully." << std::endl;
+        return 0;
+    }
+    catch(const std::exception& e)
+    {
+        std::cerr << "Stopped with exception: " << e.what() << std::endl;
+        return EXIT_FAILURE;
+    }
+}

From 7bd5348abcb38491e3deb268be089a085f6c4efe Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 18 Sep 2024 09:59:26 -0400
Subject: [PATCH 385/399] Remove using statements for complex functions

---
 include/boost/math/tools/complex.hpp | 60 ----------------------------
 1 file changed, 60 deletions(-)

diff --git a/include/boost/math/tools/complex.hpp b/include/boost/math/tools/complex.hpp
index 88db8e8a76..ec51440116 100644
--- a/include/boost/math/tools/complex.hpp
+++ b/include/boost/math/tools/complex.hpp
@@ -24,36 +24,6 @@ namespace math {
 template <typename T>
 using complex = cuda::std::complex<T>;
 
-using cuda::std::real;
-using cuda::std::imag;
-using cuda::std::abs;
-using cuda::std::arg;
-using cuda::std::norm;
-using cuda::std::conj;
-using cuda::std::proj;
-using cuda::std::polar;
-
-using cuda::std::exp;
-using cuda::std::log;
-using cuda::std::log10;
-
-using cuda::std::pow;
-using cuda::std::sqrt;
-
-using cuda::std::sin;
-using cuda::std::cos;
-using cuda::std::tan;
-using cuda::std::asin;
-using cuda::std::acos;
-using cuda::std::atan;
-
-using cuda::std::sinh;
-using cuda::std::cosh;
-using cuda::std::tanh;
-using cuda::std::asinh;
-using cuda::std::acosh;
-using cuda::std::atanh;
-
 } // namespace math
 } // namespace boost
 
@@ -68,36 +38,6 @@ namespace math {
 template <typename T>
 using complex = std::complex<T>;
 
-using std::real;
-using std::imag;
-using std::abs;
-using std::arg;
-using std::norm;
-using std::conj;
-using std::proj;
-using std::polar;
-
-using std::exp;
-using std::log;
-using std::log10;
-
-using std::pow;
-using std::sqrt;
-
-using std::sin;
-using std::cos;
-using std::tan;
-using std::asin;
-using std::acos;
-using std::atan;
-
-using std::sinh;
-using std::cosh;
-using std::tanh;
-using std::asinh;
-using std::acosh;
-using std::atanh;
-
 } // namespace math
 } // namespace boost
 

From 9f21419b2dcd7be3387423c015c76b5ccd451c32 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Wed, 18 Sep 2024 12:51:00 -0400
Subject: [PATCH 386/399] Fix overflow policy definition location on MS
 platforms

---
 test/test_hermite.cpp | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/test/test_hermite.cpp b/test/test_hermite.cpp
index c7dd8b8c40..60dafdb8f1 100644
--- a/test/test_hermite.cpp
+++ b/test/test_hermite.cpp
@@ -9,6 +9,10 @@
 #include <pch_light.hpp>
 #endif
 
+#ifndef BOOST_MATH_OVERFLOW_ERROR_POLICY
+#define BOOST_MATH_OVERFLOW_ERROR_POLICY ignore_error
+#endif
+
 #include "test_hermite.hpp"
 
 //

From a89e2a3613759b18fe8b3e458c0847a434ec7059 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 3 Oct 2024 09:28:26 -0400
Subject: [PATCH 387/399] Add missing link library for compile tests

---
 test/compile_test/CMakeLists.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/CMakeLists.txt b/test/compile_test/CMakeLists.txt
index d4d3a5dcdd..f6d26dd320 100644
--- a/test/compile_test/CMakeLists.txt
+++ b/test/compile_test/CMakeLists.txt
@@ -5,4 +5,4 @@
 file(GLOB SOURCES "*.cpp")
 add_library(boost_math-compile_tests STATIC ${SOURCES})
 target_compile_features(boost_math-compile_tests PRIVATE cxx_std_17)
-target_link_libraries(boost_math-compile_tests PUBLIC Boost::math)
+target_link_libraries(boost_math-compile_tests PUBLIC Boost::math Boost::multiprecision)

From 3b8354f038995657330e00e6a4a9e6ab9afd4b0e Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 3 Oct 2024 20:58:54 -0400
Subject: [PATCH 388/399] Change path for include test of remez

---
 test/compile_test/tools_remez_inc_test.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/tools_remez_inc_test.cpp b/test/compile_test/tools_remez_inc_test.cpp
index 938bd76615..98841b687a 100644
--- a/test/compile_test/tools_remez_inc_test.cpp
+++ b/test/compile_test/tools_remez_inc_test.cpp
@@ -8,5 +8,5 @@
 //
 
 #ifndef BOOST_MATH_STANDALONE
-#include <boost/math/tools/remez.hpp>
+#include "../../include_private/boost/math/tools/remez.hpp"
 #endif

From a0997ae285922ef9105d0b91a7afe185ec133e64 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 3 Oct 2024 21:00:22 -0400
Subject: [PATCH 389/399] Fix path to solve tool

---
 include_private/boost/math/tools/remez.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include_private/boost/math/tools/remez.hpp b/include_private/boost/math/tools/remez.hpp
index 8f817d7ce3..3fdd473969 100644
--- a/include_private/boost/math/tools/remez.hpp
+++ b/include_private/boost/math/tools/remez.hpp
@@ -10,7 +10,7 @@
 #pragma once
 #endif
 
-#include <boost/math/tools/solve.hpp>
+#include "solve.hpp"
 #include <boost/math/tools/minima.hpp>
 #include <boost/math/tools/roots.hpp>
 #include <boost/math/tools/polynomial.hpp>

From 5b52283584035dc910f83b317cb3ea6d37c6a203 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 3 Oct 2024 21:01:42 -0400
Subject: [PATCH 390/399] Link to numeric_ublas for include of solve.hpp

---
 test/compile_test/CMakeLists.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/CMakeLists.txt b/test/compile_test/CMakeLists.txt
index f6d26dd320..ddd764dfa8 100644
--- a/test/compile_test/CMakeLists.txt
+++ b/test/compile_test/CMakeLists.txt
@@ -5,4 +5,4 @@
 file(GLOB SOURCES "*.cpp")
 add_library(boost_math-compile_tests STATIC ${SOURCES})
 target_compile_features(boost_math-compile_tests PRIVATE cxx_std_17)
-target_link_libraries(boost_math-compile_tests PUBLIC Boost::math Boost::multiprecision)
+target_link_libraries(boost_math-compile_tests PUBLIC Boost::math Boost::multiprecision Boost::numeric_ublas)

From a6afa23eb2c957d3930b87693669241a72444cc9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 10 Oct 2024 09:11:44 -0400
Subject: [PATCH 391/399] Make sure we don't activate float128 use when
 explicitly disabled

---
 include/boost/math/tools/config.hpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index b3a8c2cf89..93d6af8641 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -465,7 +465,7 @@ struct non_type {};
 #if defined(BOOST_MATH_STANDALONE) && defined(_GLIBCXX_USE_FLOAT128) && defined(__GNUC__) && defined(__GNUC_MINOR__) && defined(__GNUC_PATCHLEVEL__) && !defined(__STRICT_ANSI__) \
    && !defined(BOOST_MATH_DISABLE_FLOAT128) && !defined(BOOST_MATH_USE_FLOAT128)
 #  define BOOST_MATH_USE_FLOAT128
-#elif defined(BOOST_HAS_FLOAT128) && !defined(BOOST_MATH_USE_FLOAT128)
+#elif defined(BOOST_HAS_FLOAT128) && !defined(BOOST_MATH_USE_FLOAT128) && !defined(BOOST_MATH_DISABLE_FLOAT128)
 #  define BOOST_MATH_USE_FLOAT128
 #endif
 #ifdef BOOST_MATH_USE_FLOAT128

From 7569652ec3715be5900d952c3c5f9abb740b01f5 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 10 Oct 2024 09:45:51 -0400
Subject: [PATCH 392/399] Fix solve include test

---
 test/compile_test/tools_solve_inc_test.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/tools_solve_inc_test.cpp b/test/compile_test/tools_solve_inc_test.cpp
index ee5f79d37a..715cdcc37a 100644
--- a/test/compile_test/tools_solve_inc_test.cpp
+++ b/test/compile_test/tools_solve_inc_test.cpp
@@ -7,5 +7,5 @@
 // #includes all the files that it needs to.
 //
 #ifndef BOOST_MATH_STANDALONE
-#include <boost/math/tools/solve.hpp>
+#include "../../include_private/boost/math/tools/solve.hpp"
 #endif

From 2ff0e0719e8603c0c8080e419ae4e7415dcfe479 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 10 Oct 2024 09:46:46 -0400
Subject: [PATCH 393/399] Fix path for test_data include test

---
 test/compile_test/tools_test_data_inc_test.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/tools_test_data_inc_test.cpp b/test/compile_test/tools_test_data_inc_test.cpp
index 6be425d64d..66d4a1ccde 100644
--- a/test/compile_test/tools_test_data_inc_test.cpp
+++ b/test/compile_test/tools_test_data_inc_test.cpp
@@ -7,7 +7,7 @@
 // #includes all the files that it needs to.
 //
 #ifndef BOOST_MATH_STANDALONE
-#include <boost/math/tools/test_data.hpp>
+#include "../../include_private/boost/math/tools/test_data.hpp"
 
 #define T double
 

From 810ec3d618311991a2ca0be6cf95729c8a5b1ee3 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 10 Oct 2024 09:50:49 -0400
Subject: [PATCH 394/399] Fix path of test tools

---
 test/compile_test/tools_test_inc_test.cpp | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/compile_test/tools_test_inc_test.cpp b/test/compile_test/tools_test_inc_test.cpp
index 10fea03a1d..01b0968d9b 100644
--- a/test/compile_test/tools_test_inc_test.cpp
+++ b/test/compile_test/tools_test_inc_test.cpp
@@ -9,7 +9,7 @@
 #include <array>
 
 #ifndef BOOST_MATH_STANDALONE
-#include <boost/math/tools/test.hpp>
+#include "../../include_private/boost/math/tools/test.hpp"
 //
 // Note this header includes no other headers, this is
 // important if this test is to be meaningful:

From 5970659e51873e4c43951d872ddf801b17633ccf Mon Sep 17 00:00:00 2001
From: Alexander Grund <Flamefire@users.noreply.github.com>
Date: Tue, 15 Oct 2024 15:21:58 +0200
Subject: [PATCH 395/399] CML: Add project to IDEs (#1209)

Make IDEs show the headers as a separate target.
---
 CMakeLists.txt | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 4c4fc1ddc8..7965bd1ea9 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -12,6 +12,10 @@ add_library(boost_math INTERFACE)
 add_library(Boost::math ALIAS boost_math)
 
 target_include_directories(boost_math INTERFACE include)
+if(NOT CMAKE_VERSION VERSION_LESS "3.19")
+  file(GLOB_RECURSE headers include/*.hpp)
+  target_sources(boost_math PRIVATE ${headers})
+endif()
 
 include(CMakeDependentOption)
 

From a4282229f5db14f4ad0b98917afdddd12ee2afd0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Reimar=20D=C3=B6ffinger?=
 <rdoeffinger@users.noreply.github.com>
Date: Wed, 16 Oct 2024 17:16:12 +0200
Subject: [PATCH 396/399] Fix many, many obvious test bugs (#1212)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Needed for tests to pass with 128 bit long double types

Co-authored-by: Reimar Döffinger <reimar.doeffinger@arm.com>
---
 test/ccmath_abs_test.cpp         |  4 +-
 test/ccmath_isinf_test.cpp       |  1 +
 test/ccmath_sqrt_test.cpp        |  1 +
 test/daubechies_scaling_test.cpp | 12 ++---
 test/test_airy.cpp               |  2 +-
 test/test_autodiff_2.cpp         | 13 ++++-
 test/test_beta.hpp               |  2 +-
 test/test_float_io.cpp           |  4 +-
 test/test_owens_t.hpp            | 44 ++++++++-------
 test/test_skew_normal.cpp        | 91 ++++++++++++++------------------
 10 files changed, 87 insertions(+), 87 deletions(-)

diff --git a/test/ccmath_abs_test.cpp b/test/ccmath_abs_test.cpp
index 467b7a5a15..6f09b3e0b3 100644
--- a/test/ccmath_abs_test.cpp
+++ b/test/ccmath_abs_test.cpp
@@ -76,9 +76,7 @@ int main()
 
     // Types that are convertible to int
     test<short>();
-#if CHAR_MIN != 0
-    test<char>();
-#endif
+    test<signed char>();
 
     // fabs
     fabs_test<float>();
diff --git a/test/ccmath_isinf_test.cpp b/test/ccmath_isinf_test.cpp
index 1f6b61d2fa..3ee5d1375a 100644
--- a/test/ccmath_isinf_test.cpp
+++ b/test/ccmath_isinf_test.cpp
@@ -5,6 +5,7 @@
 
 #include <cmath>
 #include <cfloat>
+#include <cstdint>
 #include <limits>
 #include <boost/math/ccmath/isinf.hpp>
 #include <boost/core/lightweight_test.hpp>
diff --git a/test/ccmath_sqrt_test.cpp b/test/ccmath_sqrt_test.cpp
index af2911bb85..eb2cf039dc 100644
--- a/test/ccmath_sqrt_test.cpp
+++ b/test/ccmath_sqrt_test.cpp
@@ -4,6 +4,7 @@
 //  LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 
 #include <cmath>
+#include <cstdint>
 #include <limits>
 #include <type_traits>
 #include <boost/math/ccmath/sqrt.hpp>
diff --git a/test/daubechies_scaling_test.cpp b/test/daubechies_scaling_test.cpp
index 3fd0937ece..e2dda727e4 100644
--- a/test/daubechies_scaling_test.cpp
+++ b/test/daubechies_scaling_test.cpp
@@ -297,8 +297,8 @@ void test_first_derivative()
    // Limited precision test data means we can't test long double here...
 #else
     auto phi1_3 = boost::math::detail::daubechies_scaling_integer_grid<long double, 3, 1>();
-    std::array<long double, 6> lin_3{0.0L, 1.638452340884085725014976L, -2.232758190463137395017742L,
-                                     0.5501593582740176149905562L, 0.04414649130503405501220997L, 0.0L};
+    std::array<long double, 6> lin_3{0.0L, 1.638452340884085725014976113635604107L, -2.23275819046313739501774225255380757L,
+                                     0.550159358274017614990556164200803310L, 0.044146491305034055012209974717400368L, 0.0L};
     for (size_t i = 0; i < lin_3.size(); ++i)
     {
         if(!CHECK_ULP_CLOSE(lin_3[i], phi1_3[i], 0))
@@ -308,8 +308,8 @@ void test_first_derivative()
     }
 
     auto phi1_4 = boost::math::detail::daubechies_scaling_integer_grid<long double, 4, 1>();
-    std::array<long double, 8> lin_4 = {0.0L, 1.776072007522184640093776L, -2.785349397229543142492785L, 1.192452536632278174347632L,
-                                       -0.1313745151846729587935189L, -0.05357102822023923595359996L,0.001770396479992522798495351L, 0.0L};
+    std::array<long double, 8> lin_4 = {0.0L, 1.776072007522184640093776071522502761L, -2.785349397229543142492784905731245880L, 1.192452536632278174347632339082851360L,
+                                       -0.131374515184672958793518896272545740L, -0.053571028220239235953599959390993709L,0.001770396479992522798495350789431024L, 0.0L};
 
     for (size_t i = 0; i < lin_4.size(); ++i)
     {
@@ -319,8 +319,8 @@ void test_first_derivative()
         }
     }
 
-    std::array<long double, 10> lin_5 = {0.0L, 1.558326313047001366564379L, -2.436012783189551921436896L, 1.235905129801454293947039L, -0.3674377136938866359947561L,
-                                        -0.02178035117564654658884556L,0.03234719350814368885815854L,-0.001335619912770701035229331L,-0.00001216838474354431384970525L,0.0L};
+    std::array<long double, 10> lin_5 = {0.0L, 1.558326313047001366564379221011472479L, -2.436012783189551921436895932290077033L, 1.235905129801454293947038906779457610L, -0.367437713693886635994756136622838186L,
+                                        -0.021780351175646546588845564309594589L,0.032347193508143688858158541500450925L,-0.001335619912770701035229330817898250L,-0.000012168384743544313849705250972915L,0.0L};
     auto phi1_5 = boost::math::detail::daubechies_scaling_integer_grid<long double, 5, 1>();
     for (size_t i = 0; i < lin_5.size(); ++i)
     {
diff --git a/test/test_airy.cpp b/test/test_airy.cpp
index 548d4de159..335c5fd92c 100644
--- a/test/test_airy.cpp
+++ b/test/test_airy.cpp
@@ -55,7 +55,7 @@ void test_airy(T, const char* name)
    }};
 
    T tol = boost::math::tools::epsilon<T>() * 800;
-   if ((std::numeric_limits<T>::digits > 100) || (std::numeric_limits<T>::digits == 0))
+   if (boost::math::tools::digits<T>() > 100)
       tol *= 2;
 
    #ifdef SYCL_LANGUAGE_VERSION
diff --git a/test/test_autodiff_2.cpp b/test/test_autodiff_2.cpp
index 79ee24ba0d..7315e7dc1b 100644
--- a/test/test_autodiff_2.cpp
+++ b/test/test_autodiff_2.cpp
@@ -522,6 +522,17 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(asinh_test, T, bin_float_types) {
                     -39 / (16 * boost::math::constants::root_two<T>()), eps);
 }
 
+template<typename T>
+static T atan2_wrap(T x, T y)
+{
+    return atan2(x, y);
+}
+
+static long double atan2_wrap(long double x, long double y)
+{
+    return std::atan2(x, y);
+}
+
 BOOST_AUTO_TEST_CASE_TEMPLATE(atan2_function, T, all_float_types) {
   using test_constants = test_constants_t<T>;
   using std::atan2;
@@ -536,7 +547,7 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(atan2_function, T, all_float_types) {
     auto y = y_sampler.next();
 
     auto autodiff_v = atan2(make_fvar<T, m>(x), make_fvar<T, m>(y));
-    auto anchor_v = atan2(x, y);
+    auto anchor_v = atan2_wrap(x, y);
     BOOST_CHECK_CLOSE(autodiff_v, anchor_v,
                       5000 * test_constants::pct_epsilon());
   }
diff --git a/test/test_beta.hpp b/test/test_beta.hpp
index 3019c17e71..362bf51bf2 100644
--- a/test/test_beta.hpp
+++ b/test/test_beta.hpp
@@ -105,7 +105,7 @@ void test_spots(T)
    BOOST_CHECK_CLOSE(::boost::math::beta(small, static_cast<T>(4)), 1/small, tolerance);
    BOOST_CHECK_CLOSE(::boost::math::beta(small, small / 2), boost::math::tgamma(small) * boost::math::tgamma(small / 2) / boost::math::tgamma(small + small / 2), tolerance);
    BOOST_CHECK_CLOSE(::boost::math::beta(static_cast<T>(4), static_cast<T>(20)), static_cast<T>(0.00002823263692828910220214568040654997176736L), tolerance);
-   if ((std::numeric_limits<T>::digits < 100) && (std::numeric_limits<T>::digits != 0))
+   if (boost::math::tools::digits<T>() < 100)
    {
       // Inexact input, so disable for ultra precise long doubles:
       BOOST_CHECK_CLOSE(::boost::math::beta(static_cast<T>(0.0125L), static_cast<T>(0.000023L)), static_cast<T>(43558.24045647538375006349016083320744662L), tolerance * 2);
diff --git a/test/test_float_io.cpp b/test/test_float_io.cpp
index e1b5c67a12..4c1ee1760a 100644
--- a/test/test_float_io.cpp
+++ b/test/test_float_io.cpp
@@ -384,10 +384,10 @@ T generate_random()
       val += gen();
    }
    e_type e;
-   val = frexp(val, &e);
+   val = std::frexp(val, &e);
 
    static boost::random::uniform_int_distribution<e_type> ui(0, std::numeric_limits<T>::max_exponent - 10);
-   return ldexp(val, ui(gen));
+   return std::ldexp(val, ui(gen));
 }
 
 template <class T>
diff --git a/test/test_owens_t.hpp b/test/test_owens_t.hpp
index 995446e5fd..a65ba4af94 100644
--- a/test/test_owens_t.hpp
+++ b/test/test_owens_t.hpp
@@ -41,30 +41,28 @@ void test_spots(RealType)
    using ::boost::math::normal_distribution;
    BOOST_MATH_STD_USING // ADL of std names.
 
-   if(std::numeric_limits<RealType>::digits && (std::numeric_limits<RealType>::digits < 100))
-   {
-
-      // Checks of six sub-methods T1 to T6.
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.0625L), static_cast<RealType>(0.25L)), static_cast<RealType>(3.89119302347013668966224771378e-2L), tolerance);  // T1
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(6.5L), static_cast<RealType>(0.4375L)), static_cast<RealType>(2.00057730485083154100907167685E-11L), tolerance); // T2
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(7L), static_cast<RealType>(0.96875L)), static_cast<RealType>(6.39906271938986853083219914429E-13L), tolerance); // T3
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(4.78125L), static_cast<RealType>(0.0625L)), static_cast<RealType>(1.06329748046874638058307112826E-7L), tolerance); // T4
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(2.L), static_cast<RealType>(0.5L)), static_cast<RealType>(8.62507798552150713113488319155E-3L), tolerance); // T5
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(1.L), static_cast<RealType>(0.9999975L)), static_cast<RealType>(6.67418089782285927715589822405E-2L), tolerance); // T6
-      //BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(L), static_cast<RealType>(L)), static_cast<RealType>(L), tolerance);
-
-      //   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(L), static_cast<RealType>(L)), static_cast<RealType>(L), tolerance);
-
-      // Spots values using Mathematica
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(6.5L), static_cast<RealType>(0.4375L)), static_cast<RealType>(2.00057730485083154100907167684918851101649922551817956120806662022118024594547E-11L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.4375L), static_cast<RealType>(6.5L)), static_cast<RealType>(0.16540130125449396247498691826626273249659241838438244251206819782787761751256L), tolerance);
+   // Checks of six sub-methods T1 to T6.
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.0625L), static_cast<RealType>(0.25L)), static_cast<RealType>(3.89119302347013668966224771378499505568e-2L), tolerance);  // T1
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(6.5L), static_cast<RealType>(0.4375L)), static_cast<RealType>(2.00057730485083154100907167684918851101649922551817956120806662022118025e-11L), tolerance); // T2
+   if (boost::math::tools::digits<RealType>() < 100) // too large error for 128 bit long double
+      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(7L), static_cast<RealType>(0.96875L)), static_cast<RealType>(6.3990627193898685308321991442891601376479719094145923322318222572484602e-13L), tolerance); // T3
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(4.78125L), static_cast<RealType>(0.0625L)), static_cast<RealType>(1.06329748046874638058307112826015825291136503488102191050906959246644943e-7L), tolerance); // T4
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(2.L), static_cast<RealType>(0.5L)), static_cast<RealType>(8.6250779855215071311348831915463718787564119039085429110080944948781288e-3L), tolerance); // T5
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(1.L), static_cast<RealType>(0.9999975L)), static_cast<RealType>(6.6741808978228592771558982240461689232406934240709035854119334966793020e-2L), tolerance); // T6
+   //BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(L), static_cast<RealType>(L)), static_cast<RealType>(L), tolerance);
+
+   //   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(L), static_cast<RealType>(L)), static_cast<RealType>(L), tolerance);
+
+   // Spots values using Mathematica
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(6.5L), static_cast<RealType>(0.4375L)), static_cast<RealType>(2.00057730485083154100907167684918851101649922551817956120806662022118024594547E-11L), tolerance);
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.4375L), static_cast<RealType>(6.5L)), static_cast<RealType>(0.16540130125449396247498691826626273249659241838438244251206819782787761751256L), tolerance);
+   if (boost::math::tools::digits<RealType>() < 100) // too large error for 128 bit long double
       BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(7.L), static_cast<RealType>(0.96875L)), static_cast<RealType>(6.39906271938986853083219914428916013764797190941459233223182225724846022843930e-13L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.96875L), static_cast<RealType>(7.L)), static_cast<RealType>(0.08316748474602973770533230453272140919966614259525787470390475393923633179072L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(4.78125L), static_cast<RealType>(0.0625L)), static_cast<RealType>(1.06329748046874638058307112826015825291136503488102191050906959246644942646701e-7L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.0625L), static_cast<RealType>(4.78125L)), static_cast<RealType>(0.21571185819897989857261253680409017017649352928888660746045361855686569265171L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(2.L), static_cast<RealType>(0.5L)), static_cast<RealType>(0.00862507798552150713113488319154637187875641190390854291100809449487812876461L), tolerance);
-      BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.5L), static_cast<RealType>(2L)), static_cast<RealType>(0.14158060365397839346662819588111542648867283386549027383784843786494855594607L), tolerance);
-   }
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.96875L), static_cast<RealType>(7.L)), static_cast<RealType>(0.08316748474602973770533230453272140919966614259525787470390475393923633179072L), tolerance);
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(4.78125L), static_cast<RealType>(0.0625L)), static_cast<RealType>(1.06329748046874638058307112826015825291136503488102191050906959246644942646701e-7L), tolerance);
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.0625L), static_cast<RealType>(4.78125L)), static_cast<RealType>(0.21571185819897989857261253680409017017649352928888660746045361855686569265171L), tolerance);
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(2.L), static_cast<RealType>(0.5L)), static_cast<RealType>(0.00862507798552150713113488319154637187875641190390854291100809449487812876461L), tolerance);
+   BOOST_CHECK_CLOSE_FRACTION(owens_t(static_cast<RealType>(0.5L), static_cast<RealType>(2L)), static_cast<RealType>(0.14158060365397839346662819588111542648867283386549027383784843786494855594607L), tolerance);
    // check basic properties
    BOOST_CHECK_EQUAL(owens_t(static_cast<RealType>(0.5L), static_cast<RealType>(2L)), owens_t(static_cast<RealType>(-0.5L), static_cast<RealType>(2L)));
    BOOST_CHECK_EQUAL(owens_t(static_cast<RealType>(0.5L), static_cast<RealType>(2L)), -owens_t(static_cast<RealType>(0.5L), static_cast<RealType>(-2L)));
diff --git a/test/test_skew_normal.cpp b/test/test_skew_normal.cpp
index 5f0657fbd1..617a8f6fab 100644
--- a/test/test_skew_normal.cpp
+++ b/test/test_skew_normal.cpp
@@ -356,7 +356,7 @@ void test_spots(RealType)
 
         BOOST_CHECK_CLOSE(      // mean:
            mean(dist)
-           , static_cast<RealType>(-0.579908992539856825862549L), tol10 * 2);
+           , static_cast<RealType>(-0.5799089925398568258625490172876619L), tol10 * 2);
 
         std::cout << std::setprecision(17) << "Variance = " << variance(dist) << std::endl;
          BOOST_CHECK_CLOSE(      // variance: N[variance[skewnormaldistribution[1.1, 2.2, -3.3]], 50]
@@ -365,27 +365,27 @@ void test_spots(RealType)
 
         BOOST_CHECK_CLOSE(      // skewness:
            skewness(dist)
-           , static_cast<RealType>(-0.709854548171537509192897824663L), tol100);
+           , static_cast<RealType>(-0.709854548171537509192897824663027155L), tol100);
         BOOST_CHECK_CLOSE(      // kurtosis:
            kurtosis(dist)
-           , static_cast<RealType>(3.5538752625241790601377L), tol100);
+           , static_cast<RealType>(3.55387526252417906013770535120683805L), tol100);
         BOOST_CHECK_CLOSE(      // kurtosis excess:
            kurtosis_excess(dist)
-           , static_cast<RealType>(0.5538752625241790601377L), tol100);
+           , static_cast<RealType>(0.553875262524179060137705351206838143L), tol100);
 
         BOOST_CHECK_CLOSE(
           pdf(dist, static_cast<RealType>(0.4L)),
-          static_cast<RealType>(0.294140110156599539564571L),
+          static_cast<RealType>(0.294140110156599539564571034730246656L),
           tol10);
 
         BOOST_CHECK_CLOSE(
           cdf(dist, static_cast<RealType>(0.4L)),
-          static_cast<RealType>(0.7339186189278737976326676452L),
+          static_cast<RealType>(0.733918618927873797632667645226588243L),
           tol100);
 
         BOOST_CHECK_CLOSE(
           quantile(dist, static_cast<RealType>(0.3L)),
-          static_cast<RealType>(-1.180104068086875314419247L),
+          static_cast<RealType>(-1.18010406808687531441924729956233392L),
           tol100);
 
 
@@ -395,72 +395,63 @@ void test_spots(RealType)
 
        // cout << "pdf(dist, 0) = " << pdf(dist, 0) <<  ", pdf(dist, 0.45) = " << pdf(dist, 0.45) << endl;
        // BOOST_CHECK_CLOSE(mode(dist), boost::math::constants::root_two<RealType>() / 2, tol5);
-        BOOST_CHECK_CLOSE(mode(dist), static_cast<RealType>(0.41697299497388863932L), tol100);
+        BOOST_CHECK_CLOSE(mode(dist), static_cast<RealType>(0.416972994973888639318345129445233074L), tol100);
       }
 
 
       }
-      if(std::numeric_limits< RealType>::digits && (std::numeric_limits<RealType>::digits < 100))
-      {
-        dist = skew_normal_distribution<RealType>(static_cast<RealType>(1.1l), static_cast<RealType>(0.02l), static_cast<RealType>(0.03l));
+      dist = skew_normal_distribution<RealType>(static_cast<RealType>(1.1l), static_cast<RealType>(0.02l), static_cast<RealType>(0.03l));
 
-        BOOST_CHECK_CLOSE(      // mean:
+      BOOST_CHECK_CLOSE(      // mean:
            mean(dist)
-           , static_cast<RealType>(1.1004785154529557886162L), tol10);
-        BOOST_CHECK_CLOSE(      // variance:
+           , static_cast<RealType>(1.1004785154529557886162056250600829L), tol10);
+      BOOST_CHECK_CLOSE(      // variance:
           variance(dist)
-           , static_cast<RealType>(0.00039977102296128251645L), tol10);
+           , static_cast<RealType>(0.000399771022961282516451686289719995601L), tol10);
 
-        BOOST_CHECK_CLOSE(      // skewness:
+      BOOST_CHECK_CLOSE(      // skewness:
            skewness(dist)
-           , static_cast<RealType>(5.8834811259890359782e-006L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis:
+           , static_cast<RealType>(5.88348112598903597820852388986073439e-006L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis:
            kurtosis(dist)
-           , static_cast<RealType>(3.L + 9.2903475812137800239002e-008L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis excess:
+           , static_cast<RealType>(3.L + 9.290347581213780023900209941e-008L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis excess:
            kurtosis_excess(dist)
-           , static_cast<RealType>(9.2903475812137800239002e-008L), tol100);
-      }
-      if (std::numeric_limits< RealType>::digits && (std::numeric_limits<RealType>::digits < 100))
-      {
-        dist = skew_normal_distribution<RealType>(static_cast<RealType>(10.1l), static_cast<RealType>(5.l), static_cast<RealType>(-0.03l));
-        BOOST_CHECK_CLOSE(      // mean:
+           , static_cast<RealType>(9.29034758121378002390020993765449518e-008L), tol100);
+      dist = skew_normal_distribution<RealType>(static_cast<RealType>(10.1l), static_cast<RealType>(5.l), static_cast<RealType>(-0.03l));
+      BOOST_CHECK_CLOSE(      // mean:
            mean(dist)
-           , static_cast<RealType>(9.9803711367610528459485937L), tol10);
-        BOOST_CHECK_CLOSE(      // variance:
+           , static_cast<RealType>(9.98037113676105284594859373497928476L), tol10);
+      BOOST_CHECK_CLOSE(      // variance:
           variance(dist)
-           , static_cast<RealType>(24.98568893508015727823L), tol10);
+           , static_cast<RealType>(24.9856889350801572782303931074997234L), tol10);
 
-        BOOST_CHECK_CLOSE(      // skewness:
+      BOOST_CHECK_CLOSE(      // skewness:
            skewness(dist)
-           , static_cast<RealType>(-5.8834811259890359782085e-006L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis:
+           , static_cast<RealType>(-5.88348112598903597820852388986073439e-006L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis:
            kurtosis(dist)
-           , static_cast<RealType>(3.L + 9.2903475812137800239002e-008L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis excess:
+           , static_cast<RealType>(3.L + 9.290347581213780023900209941e-008L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis excess:
            kurtosis_excess(dist)
-           , static_cast<RealType>(9.2903475812137800239002e-008L), tol100);
-      }
-      if (std::numeric_limits< RealType>::digits && (std::numeric_limits<RealType>::digits < 100))
-      {
-        dist = skew_normal_distribution<RealType>(static_cast<RealType>(-10.1l), static_cast<RealType>(5.l), static_cast<RealType>(30.l));
-        BOOST_CHECK_CLOSE(      // mean:
+           , static_cast<RealType>(9.29034758121378002390020993765449518e-008L), tol100);
+      dist = skew_normal_distribution<RealType>(static_cast<RealType>(-10.1l), static_cast<RealType>(5.l), static_cast<RealType>(30.l));
+      BOOST_CHECK_CLOSE(      // mean:
            mean(dist)
-           , static_cast<RealType>(-6.11279169674138408531365L), 2 * tol10);
-        BOOST_CHECK_CLOSE(      // variance:
+           , static_cast<RealType>(-6.11279169674138408531365149047090859L), 2 * tol10);
+      BOOST_CHECK_CLOSE(      // variance:
           variance(dist)
-          , static_cast<RealType>(9.10216994642554914628242L), tol10 * 2);
+          , static_cast<RealType>(9.10216994642554914628242097277880642L), tol10 * 2);
 
-        BOOST_CHECK_CLOSE(      // skewness:
+      BOOST_CHECK_CLOSE(      // skewness:
            skewness(dist)
-           , static_cast<RealType>(0.99072425443686904424L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis:
+           , static_cast<RealType>(0.990724254436869044244695246354219556L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis:
            kurtosis(dist)
-           , static_cast<RealType>(3.L + 0.8638862008406084244563L), tol100);
-        BOOST_CHECK_CLOSE(      // kurtosis excess:
+           , static_cast<RealType>(3.L + 0.8638862008406084244563090239530549L), tol100);
+      BOOST_CHECK_CLOSE(      // kurtosis excess:
            kurtosis_excess(dist)
-           , static_cast<RealType>(0.8638862008406084244563L), tol100);
-      }
+           , static_cast<RealType>(0.863886200840608424456309023953054896L), tol100);
 
       BOOST_MATH_CHECK_THROW(cdf(skew_normal_distribution<RealType>(0, 0, 0), 0), std::domain_error);
       BOOST_MATH_CHECK_THROW(cdf(skew_normal_distribution<RealType>(0, -1, 0), 0), std::domain_error);

From e690b0029685c3ac9c293410059fbf14d33c07c9 Mon Sep 17 00:00:00 2001
From: Matt Borland <matt@mattborland.com>
Date: Thu, 17 Oct 2024 13:39:33 -0400
Subject: [PATCH 397/399] Fix compile test CML and add CMake testing (#1213)

* Add boost standard CMake Testing

* Add include private

* Change CI command

* Use boost test and change target
---
 .github/workflows/ci.yml         | 49 ++++++++++++++++++++++++++++++++
 test/compile_test/CMakeLists.txt |  7 ++---
 2 files changed, 52 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index ee72988440..fb0154b969 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -546,6 +546,55 @@ jobs:
       - name: Test
         run: ../../../b2 toolset=$TOOLSET ${{ matrix.suite }} define=CI_SUPPRESS_KNOWN_ISSUES define=SLOW_COMPILER define=BOOST_MATH_STANDALONE define=BOOST_MP_STANDALONE
         working-directory: ../boost-root/libs/math/test
+
+  posix-cmake-test:
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - os: ubuntu-22.04
+
+    runs-on: ${{matrix.os}}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install packages
+        if: matrix.install
+        run: sudo apt install ${{matrix.install}} libgmp-dev libmpfr-dev libfftw3-dev
+
+      - name: Setup Boost
+        run: |
+          echo GITHUB_REPOSITORY: $GITHUB_REPOSITORY
+          LIBRARY=${GITHUB_REPOSITORY#*/}
+          echo LIBRARY: $LIBRARY
+          echo "LIBRARY=$LIBRARY" >> $GITHUB_ENV
+          echo GITHUB_BASE_REF: $GITHUB_BASE_REF
+          echo GITHUB_REF: $GITHUB_REF
+          REF=${GITHUB_BASE_REF:-$GITHUB_REF}
+          REF=${REF#refs/heads/}
+          echo REF: $REF
+          BOOST_BRANCH=develop && [ "$REF" == "master" ] && BOOST_BRANCH=master || true
+          echo BOOST_BRANCH: $BOOST_BRANCH
+          cd ..
+          git clone -b $BOOST_BRANCH --depth 1 https://github.com/boostorg/boost.git boost-root
+          cd boost-root
+          mkdir -p libs/$LIBRARY
+          cp -r $GITHUB_WORKSPACE/* libs/$LIBRARY
+          git submodule update --init tools/boostdep
+          python tools/boostdep/depinst/depinst.py --git_args "--jobs 3" $LIBRARY
+
+      - name: Configure
+        run: |
+          cd ../boost-root
+          mkdir __build__ && cd __build__
+          cmake -DBOOST_INCLUDE_LIBRARIES=$LIBRARY -DBUILD_TESTING=ON ..
+
+      - name: Build tests
+        run: |
+          cd ../boost-root/__build__
+          cmake --build . --target tests
+
   sycl-cmake-test:
     strategy:
       fail-fast: false
diff --git a/test/compile_test/CMakeLists.txt b/test/compile_test/CMakeLists.txt
index ddd764dfa8..acfa292228 100644
--- a/test/compile_test/CMakeLists.txt
+++ b/test/compile_test/CMakeLists.txt
@@ -2,7 +2,6 @@
 # Distributed under the Boost Software License, Version 1.0.
 # https://www.boost.org/LICENSE_1_0.txt
 
-file(GLOB SOURCES "*.cpp")
-add_library(boost_math-compile_tests STATIC ${SOURCES})
-target_compile_features(boost_math-compile_tests PRIVATE cxx_std_17)
-target_link_libraries(boost_math-compile_tests PUBLIC Boost::math Boost::multiprecision Boost::numeric_ublas)
+include_directories(../../include_private)
+file(GLOB SRC_FILES CONFIGURE_DEPENDS "*.cpp")
+boost_test(TYPE "compile" SOURCES ${SRC_FILES} COMPILE_DEFINITIONS BOOST_MATH_STANDALONE COMPILE_FEATURES cxx_std_17 LINK_LIBRARIES Boost::math Boost::multiprecision Boost::numeric_ublas Boost::unit_test_framework )

From 097b73c9bfe7528dec04cf144d9ebaf7d9d97882 Mon Sep 17 00:00:00 2001
From: NickelWenzel <55748692+NickelWenzel@users.noreply.github.com>
Date: Thu, 24 Oct 2024 15:01:17 +0200
Subject: [PATCH 398/399] fix: define BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
 for emscripten (#1216)

---
 include/boost/math/tools/config.hpp | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/tools/config.hpp b/include/boost/math/tools/config.hpp
index 93d6af8641..12f3411c2f 100644
--- a/include/boost/math/tools/config.hpp
+++ b/include/boost/math/tools/config.hpp
@@ -220,12 +220,16 @@
 
 #include <boost/math/tools/user.hpp>
 
-#if (defined(__NetBSD__) || defined(__EMSCRIPTEN__)\
+#if (defined(__NetBSD__)\
    || (defined(__hppa) && !defined(__OpenBSD__)) || (defined(__NO_LONG_DOUBLE_MATH) && (DBL_MANT_DIG != LDBL_MANT_DIG))) \
    && !defined(BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS)
 //#  define BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
 #endif
 
+#if defined(__EMSCRIPTEN__) && !defined(BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS)
+#  define BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
+#endif
+
 #ifdef __IBMCPP__
 //
 // For reasons I don't understand, the tests with IMB's compiler all

From 2cd9c4d8352873796108c191bd2d088f3624c5d8 Mon Sep 17 00:00:00 2001
From: Pavel P <pavlov.pavel@gmail.com>
Date: Tue, 29 Oct 2024 00:46:58 +0500
Subject: [PATCH 399/399] Fix icx warning: explicit comparison with infinity in
 fast floating point mode with intel compiler (#1218)

fixes #1217
---
 include/boost/math/ccmath/isinf.hpp | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

diff --git a/include/boost/math/ccmath/isinf.hpp b/include/boost/math/ccmath/isinf.hpp
index f1e00e34f5..ecf0d620ab 100644
--- a/include/boost/math/ccmath/isinf.hpp
+++ b/include/boost/math/ccmath/isinf.hpp
@@ -22,7 +22,14 @@ constexpr bool isinf BOOST_MATH_PREVENT_MACRO_SUBSTITUTION(T x) noexcept
     {
         if constexpr (std::numeric_limits<T>::is_signed)
         {
+#if defined(__clang_major__) && __clang_major__ >= 6
+#pragma clang diagnostic push
+#pragma clang diagnostic ignored "-Wtautological-constant-compare"
+#endif
             return x == std::numeric_limits<T>::infinity() || -x == std::numeric_limits<T>::infinity();
+#if defined(__clang_major__) && __clang_major__ >= 6
+#pragma clang diagnostic pop
+#endif
         }
         else
         {
@@ -32,7 +39,7 @@ constexpr bool isinf BOOST_MATH_PREVENT_MACRO_SUBSTITUTION(T x) noexcept
     else
     {
         using boost::math::isinf;
-        
+
         if constexpr (!std::is_integral_v<T>)
         {
             return (isinf)(x);